diff --git a/GSA_distrib/4.0.3/GSA.zip b/GSA_distrib/4.0.3/GSA.zip
deleted file mode 100644
index 77d88674d13025fe11a51951e163b67207c05708..0000000000000000000000000000000000000000
Binary files a/GSA_distrib/4.0.3/GSA.zip and /dev/null differ
diff --git a/GSA_distrib/4.0.3/LPTAU.m b/GSA_distrib/4.0.3/LPTAU.m
deleted file mode 100644
index 7427de885c114d4e0cbed949322d62072bb92f34..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/LPTAU.m
+++ /dev/null
@@ -1,512 +0,0 @@
-function VECTOR = LPTAU(I, N)
-%
-% I.M. SOBOL', V.I. TURCHANINOV, Yu.L. LEVITAN, B.V. SHUKHMAN
-% KELDYSH INSTITUTE OF APPLIED MATHEMATICS
-% RUSSIAN ACADEMY OF SCIENCES
-%
-% QUASIRANDOM SEQUENCE GENERATORS
-% -------------------------------
-%
-% 28.11.1991
-%
-% NOTE TO THE USER BY the NEA Data Bank:
-% This quasi random number generator has been made available to
-% you on condition that its identity is preserved when used
-% in computer programs. If its use leads to scientific publication
-% of results you should cite it in the references, in addition
-% no commercial use should be made unless agreed upon with the
-% main author (Prof. I.M. Sobol')
-%
-% ABSTRACT
-% ........
-%
-% POINTS BELONGING TO LP-TAU SEQUENCES UNIFORMLY DISTRIBUTED IN THE
-% N-DIMENSIONAL UNIT CUBE ARE OFTEN USED IN NUMERICAL MATHEMATICS:
-%
-% - AS NODES FOR MULTIDIMENSIONAL INTEGRATION;
-% - AS SEARCHING POINTS IN GLOBAL OPTIMIZATION;
-% - AS TRIAL POINTS IN MULTI-CRITERIA DECISION MAKING;
-% - AS QUASIRANDOM POINTS FOR QUASI-MONTECARLO ALGORITHMS;
-% - ETC.
-%
-% THIS SUBROUTINE CONTAINS THE ALGORITHM FOR FAST GENERATION OF
-% LP-TAU SEQUENCES THAT ARE SUITABLE FOR MULTI-PROCESSOR COMPUTATIONS.
-% THE DIMENSIONS N.LE.51, THE NUMBER OF POINTS N.LT.2**30.
-% THE PROGRAMMING LANGUAGE IS FORTRAN-77. THIS SUBROUTINE IS AVAILABLE
-% ALSO IN %-LANGUAGE.
-% THE REPORT DESCRIBING THE ALGORITHM CONTAINS THE DESCRIPTION OF THE
-% ALGORITHM AND CERTAIN IMPORTANT PROPERTIES OF LP-TAU SEQUENCES AND
-% THEIR GENERALIZATIONS ARE DISCUSSED.
-%
-% REFERENCE:
-% I.M. SOBOL', V.I. TURCHANINOV, Yu.L. LEVITAN, B.V. SHUKHMAN
-% KELDYSH INSTITUTE OF APPLIED MATHEMATICS
-% RUSSIAN ACADEMY OF SCIENCES
-%
-% QUASIRANDOM SEQUENCE GENERATORS
-% MOSCOW 1992, IPM ZAK. NO.30 (100 COPIES)
-%
-% ------------------------------------------------------------------------
-%
-% INPUT PARAMETERS:
-%
-% I - NUMBER OF THE POINT (I=(0,2**30-1)),
-% N - DIMENSION OF THE POINT (0<N<52);
-%
-% OUTPUT PARAMETER:
-%
-% VECTOR(N) - N-VECTOR CONTAINING THE CARTESIAN CO-ORDINATES OF
-% THE I-TH POINT.
-%
-%
-% TO CALL THE SUBROUTINE WRITE:
-%
-% CALL LPTAU(I,N,VECTOR)
-% WHERE I, N: INTEGER CAPABLE OF STORING 2**30 (INTEGER*4 ON IBM
-% OR OTHER 32 BIT/WORD MACHINES)
-% VECTOR: DOUBLE PRECISION ARRAY WHOSE LENGTH < 52.
-%
-% INTEGER QP
-% QP = QUANTITY POWER
-%
-% PARAMETER (MAXDIM=51, QP=30, MAXNUM=2**30-1)
-MAXDIM=51; QP=30; MAXNUM=2^30-1;
-%
-% THE DIMENSION OF THE POINT CANNOT EXCEED MAXDIM
-% THE TOTAL NUMBER OF GENERATED POINTS CANNOT EXCEED 2**QP
-% MAXNUM=2**30-1 // 1073741823
-%
-% DOUBLE PRECISION VECTOR(N)
-% INTEGER I,N
-%
-% INTEGER PRVNUM,PRVDIM
-% INTEGER DIRECT(MAXDIM,QP), MASKV(MAXDIM)
-% DOUBLE PRECISION SCALE
-%
-% Translated into MATLAB by M. Ratto
-VECTOR=zeros(1,N);
-SCALE =9.31322574615478516E-10;
-
-persistent PRVNUM PRVDIM MASKV DIRECT
-if isempty(PRVNUM), PRVNUM=-2; end,
-if isempty(PRVDIM), PRVDIM=0; end,
-
-if isempty(DIRECT), ...
- DIRECT(1:MAXDIM,1)=[
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912]';
- DIRECT(1:MAXDIM,2)=[
- 805306368, 268435456, 805306368, 268435456, 805306368, ...
- 268435456, 805306368, 268435456, 268435456, 805306368, ...
- 268435456, 805306368, 268435456, 805306368, 268435456, ...
- 805306368, 805306368, 268435456, 805306368, 268435456, ...
- 805306368, 268435456, 805306368, 268435456, 268435456, ...
- 805306368, 268435456, 805306368, 268435456, 805306368, ...
- 268435456, 805306368, 805306368, 268435456, 805306368, ...
- 268435456, 805306368, 268435456, 805306368, 268435456, ...
- 268435456, 805306368, 268435456, 805306368, 268435456, ...
- 805306368, 268435456, 805306368, 805306368, 268435456, ...
- 805306368]';
- DIRECT(1:MAXDIM,3)=[
- 939524096, 939524096, 134217728, 671088640, 402653184, ...
- 402653184, 671088640, 134217728, 671088640, 402653184, ...
- 939524096, 134217728, 671088640, 939524096, 134217728, ...
- 671088640, 134217728, 939524096, 939524096, 402653184, ...
- 402653184, 134217728, 671088640, 402653184, 671088640, ...
- 402653184, 402653184, 671088640, 134217728, 134217728, ...
- 939524096, 939524096, 939524096, 939524096, 134217728, ...
- 671088640, 402653184, 402653184, 671088640, 134217728, ...
- 671088640, 402653184, 939524096, 134217728, 671088640, ...
- 939524096, 134217728, 671088640, 134217728, 939524096, ...
- 939524096]';
- DIRECT(1:MAXDIM,4)=[
- 1006632960, 67108864, 603979776, 1006632960, 335544320, ...
- 469762048, 872415232, 738197504, 469762048, 872415232, ...
- 1006632960, 67108864, 872415232, 469762048, 469762048, ...
- 469762048, 1006632960, 335544320, 872415232, 603979776, ...
- 201326592, 67108864, 335544320, 67108864, 201326592, ...
- 738197504, 1006632960, 738197504, 603979776, 335544320, ...
- 738197504, 67108864, 1006632960, 67108864, 603979776, ...
- 1006632960, 335544320, 469762048, 872415232, 738197504, ...
- 469762048, 872415232, 1006632960, 67108864, 872415232, ...
- 469762048, 469762048, 469762048, 1006632960, 335544320, ...
- 872415232]';
- DIRECT(1:MAXDIM,5)=[
- 1040187392, 637534208, 1040187392, 838860800, 167772160, ...
- 234881024, 167772160, 1040187392, 436207616, 33554432, ...
- 570425344, 1040187392, 503316480, 838860800, 973078528, ...
- 167772160, 234881024, 436207616, 771751936, 100663296, ...
- 234881024, 905969664, 771751936, 33554432, 838860800, ...
- 973078528, 905969664, 33554432, 301989888, 838860800, ...
- 100663296, 234881024, 1040187392, 637534208, 1040187392, ...
- 838860800, 167772160, 234881024, 167772160, 1040187392, ...
- 436207616, 33554432, 570425344, 1040187392, 503316480, ...
- 838860800, 973078528, 167772160, 234881024, 436207616, ...
- 771751936]';
- DIRECT(1:MAXDIM,6)=[
- 1056964608, 352321536, 50331648, 419430400, 956301312, ...
- 889192448, 620756992, 117440512, 956301312, 922746880, ...
- 822083584, 218103808, 587202560, 385875968, 452984832, ...
- 218103808, 184549376, 285212672, 150994944, 956301312, ...
- 352321536, 654311424, 553648128, 352321536, 788529152, ...
- 956301312, 587202560, 251658240, 218103808, 721420288, ...
- 251658240, 1056964608, 520093696, 889192448, 587202560, ...
- 956301312, 419430400, 352321536, 83886080, 654311424, ...
- 419430400, 385875968, 285212672, 754974720, 50331648, ...
- 922746880, 989855744, 754974720, 721420288, 822083584, ...
- 687865856]';
- DIRECT(1:MAXDIM,7)=[
- 1065353216, 1065353216, 578813952, 25165824, 125829120, ...
- 964689920, 327155712, 310378496, 360710144, 360710144, ...
- 159383552, 444596224, 947912704, 662700032, 444596224, ...
- 528482304, 578813952, 578813952, 75497472, 1065353216, ...
- 92274688, 511705088, 897581056, 847249408, 662700032, ...
- 931135488, 411041792, 713031680, 696254464, 528482304, ...
- 209715200, 578813952, 1065353216, 1065353216, 578813952, ...
- 25165824, 125829120, 964689920, 327155712, 310378496, ...
- 360710144, 360710144, 159383552, 444596224, 947912704, ...
- 662700032, 444596224, 528482304, 578813952, 578813952, ...
- 75497472]';
- DIRECT(1:MAXDIM,8)=[
- 1069547520, 4194304, 826277888, 624951296, 616562688, ...
- 801112064, 952107008, 406847488, 398458880, 331350016, ...
- 356515840, 46137344, 1010827264, 1069547520, 734003200, ...
- 113246208, 490733568, 633339904, 910163968, 801112064, ...
- 893386752, 851443712, 801112064, 918552576, 742391808, ...
- 499122176, 62914560, 264241152, 708837376, 717225984, ...
- 759169024, 499122176, 272629760, 423624704, 155189248, ...
- 239075328, 205520896, 943718400, 373293056, 457179136, ...
- 406847488, 71303168, 473956352, 54525952, 624951296, ...
- 104857600, 1019215872, 901775360, 213909504, 281018368, ...
- 851443712]';
- DIRECT(1:MAXDIM,9)=[
- 1071644672, 543162368, 190840832, 329252864, 853540864, ...
- 132120576, 778043392, 73400320, 178257920, 522190848, ...
- 639631360, 534773760, 991952896, 333447168, 48234496, ...
- 1059061760, 761266176, 673185792, 220200960, 396361728, ...
- 362807296, 815792128, 819986432, 346030080, 39845888, ...
- 752877568, 387973120, 643825664, 291504128, 274726912, ...
- 568328192, 526385152, 673185792, 98566144, 396361728, ...
- 727711744, 1042284544, 106954752, 299892736, 912261120, ...
- 44040192, 895483904, 333447168, 551550976, 467664896, ...
- 618659840, 606076928, 274726912, 245366784, 446693376, ...
- 421527552]';
- DIRECT(1:MAXDIM,10)=[
- 1072693248, 273678336, 644874240, 753926144, 495976448, ...
- 869269504, 355467264, 57671680, 816840704, 961544192, ...
- 804257792, 495976448, 347078656, 426770432, 1066401792, ...
- 372244480, 84934656, 208666624, 313524224, 598736896, ...
- 487587840, 965738496, 1011875840, 296747008, 393216000, ...
- 523239424, 720371712, 823132160, 128974848, 407896064, ...
- 747634688, 850395136, 873463808, 504365056, 481296384, ...
- 686817280, 592445440, 995098624, 498073600, 969932800, ...
- 586153984, 1039138816, 814743552, 523239424, 294649856, ...
- 305135616, 506462208, 11534336, 449839104, 619708416, ...
- 479199232]';
- DIRECT(1:MAXDIM,11)=[
- 1073217536, 947388416, 1070071808, 977797120, 365428736, ...
- 702021632, 461897728, 829947904, 425197568, 634912768, ...
- 437780480, 582483968, 792199168, 315097088, 611844096, ...
- 667418624, 166199296, 513277952, 187170816, 1036517376, ...
- 25690112, 201850880, 443023360, 990380032, 63438848, ...
- 211288064, 983040000, 1069023232, 421003264, 742916096, ...
- 487063552, 363331584, 973602816, 286785536, 171442176, ...
- 669515776, 110624768, 383254528, 289931264, 352845824, ...
- 878182400, 655884288, 836239360, 765984768, 549978112, ...
- 655884288, 85458944, 591921152, 563609600, 277348352, ...
- 919076864]';
- DIRECT(1:MAXDIM,12)=[
- 1073479680, 71565312, 2359296, 891551744, 158597120, ...
- 383516672, 1019478016, 947126272, 621019136, 714866688, ...
- 738459648, 265027584, 468975616, 131858432, 504627200, ...
- 581173248, 266600448, 865861632, 658243584, 546045952, ...
- 521404416, 304873472, 1060896768, 163840000, 305922048, ...
- 257163264, 50069504, 773062656, 59506688, 779354112, ...
- 165937152, 587988992, 486801408, 160694272, 90439680, ...
- 423362560, 536608768, 614203392, 56885248, 999030784, ...
- 10747904, 764674048, 25952256, 989069312, 352583680, ...
- 799801344, 261357568, 873201664, 40108032, 769392640, ...
- 254541824]';
- DIRECT(1:MAXDIM,13)=[
- 1073610752, 644218880, 538836992, 455475200, 1062600704, ...
- 139329536, 205651968, 905052160, 797048832, 452329472, ...
- 973471744, 627703808, 614072320, 803078144, 637403136, ...
- 835059712, 949878784, 662044672, 767950848, 426901504, ...
- 448659456, 23986176, 1016201216, 524943360, 525991936, ...
- 618790912, 781058048, 761659392, 458096640, 226361344, ...
- 950665216, 952500224, 516030464, 337510400, 496107520, ...
- 830865408, 944111616, 636354560, 978452480, 921567232, ...
- 533594112, 7471104, 678035456, 471203840, 1065746432, ...
- 575275008, 996540416, 909246464, 879362048, 637927424, ...
- 25821184]';
- DIRECT(1:MAXDIM,14)=[
- 1073676288, 357892096, 808648704, 2424832, 2555904, ...
- 624230400, 69271552, 456851456, 1052966912, 600637440, ...
- 487260160, 794624000, 386727936, 467599360, 798031872, ...
- 630652928, 340983808, 493944832, 37945344, 264175616, ...
- 263520256, 833421312, 235077632, 464846848, 534839296, ...
- 992411648, 10813440, 367067136, 116457472, 115015680, ...
- 928710656, 619773952, 813760512, 1043398656, 967770112, ...
- 912850944, 72155136, 1009057792, 668532736, 462356480, ...
- 267321344, 795803648, 635764736, 574160896, 1003421696, ...
- 181075968, 56688640, 388562944, 190906368, 657915904, ...
- 474939392]';
- DIRECT(1:MAXDIM,15)=[
- 1073709056, 1073709056, 137003008, 547782656, 545095680, ...
- 26836992, 34701312, 354385920, 925663232, 656965632, ...
- 327581696, 894795776, 110067712, 1038057472, 209354752, ...
- 596541440, 42631168, 471433216, 52527104, 666861568, ...
- 706707456, 674070528, 824410112, 305496064, 136282112, ...
- 847740928, 531464192, 222920704, 379289600, 507740160, ...
- 11894784, 1053392896, 129990656, 557547520, 666468352, ...
- 1061912576, 576684032, 1041334272, 380469248, 114196480, ...
- 133070848, 517046272, 129990656, 790396928, 563773440, ...
- 388333568, 661749760, 446791680, 737378304, 229998592, ...
- 348225536]';
- DIRECT(1:MAXDIM,16)=[
- 1073725440, 16384, 605372416, 275234816, 817971200, ...
- 603963392, 555335680, 721534976, 997801984, 1028767744, ...
- 407060480, 375275520, 256688128, 1021165568, 303349760, ...
- 1022476288, 234143744, 106708992, 732971008, 733954048, ...
- 789889024, 879575040, 764657664, 762658816, 1010843648, ...
- 941080576, 827932672, 98942976, 1051738112, 624934912, ...
- 993280000, 134070272, 201375744, 567558144, 882163712, ...
- 649084928, 356564992, 489439232, 637091840, 60637184, ...
- 199278592, 815677440, 927678464, 94519296, 419184640, ...
- 933838848, 426655744, 911130624, 171393024, 561332224, ...
- 471613440]';
- DIRECT(1:MAXDIM,17)=[
- 1073733632, 536895488, 1043685376, 679944192, 417505280, ...
- 301981696, 832561152, 210542592, 167501824, 1071341568, ...
- 229302272, 970661888, 732176384, 576659456, 402464768, ...
- 451584000, 368467968, 928260096, 933847040, 29319168, ...
- 582934528, 772612096, 330014720, 647323648, 174071808, ...
- 1008689152, 295919616, 353869824, 177774592, 580198400, ...
- 381837312, 638574592, 637558784, 679370752, 504012800, ...
- 747118592, 429973504, 1032609792, 932667392, 583360512, ...
- 969498624, 1056333824, 660955136, 247488512, 153509888, ...
- 242180096, 205840384, 797499392, 824565760, 234348544, ...
- 842326016]';
- DIRECT(1:MAXDIM,18)=[
- 1073737728, 268455936, 52785152, 1020628992, 345018368, ...
- 452972544, 704442368, 255987712, 750759936, 697692160, ...
- 196677632, 764604416, 485625856, 522022912, 680620032, ...
- 362270720, 838103040, 83972096, 629133312, 46108672, ...
- 867561472, 725422080, 184504320, 751112192, 191918080, ...
- 306425856, 507310080, 30453760, 281858048, 604000256, ...
- 208662528, 319557632, 318779392, 476139520, 863719424, ...
- 567062528, 521179136, 712790016, 610299904, 293687296, ...
- 1023086592, 549089280, 1065242624, 707751936, 363024384, ...
- 16674816, 197136384, 1037561856, 195112960, 372707328, ...
- 992751616]';
- DIRECT(1:MAXDIM,19)=[
- 1073739776, 939554816, 580732928, 854333440, 172619776, ...
- 511694848, 936142848, 518199296, 593348608, 225527808, ...
- 900982784, 180279296, 168904704, 62814208, 754485248, ...
- 730691584, 1005996032, 411174912, 249866240, 641669120, ...
- 1008719872, 749066240, 860993536, 94177280, 432564224, ...
- 226355200, 925784064, 995657728, 967731200, 436226048, ...
- 913799168, 549894144, 964696064, 843315200, 445863936, ...
- 1047422976, 548947968, 492066816, 953870336, 1002653696, ...
- 861440000, 385636352, 325253120, 187353088, 653584384, ...
- 1008269312, 748693504, 1013016576, 55814144, 255170560, ...
- 260708352]';
- DIRECT(1:MAXDIM,20)=[
- 1073740800, 67126272, 829514752, 423777280, 968297472, ...
- 205511680, 147076096, 926669824, 202300416, 118395904, ...
- 381332480, 1002738688, 743042048, 292551680, 584567808, ...
- 284339200, 183936000, 616762368, 435221504, 159376384, ...
- 907322368, 595696640, 247497728, 553735168, 826051584, ...
- 564454400, 446024704, 214236160, 33661952, 251685888, ...
- 660327424, 284244992, 859868160, 722502656, 622844928, ...
- 324342784, 682374144, 400579584, 405353472, 605187072, ...
- 840682496, 212956160, 157891584, 193201152, 437990400, ...
- 573578240, 368053248, 580197376, 937905152, 565527552, ...
- 89064448]';
- DIRECT(1:MAXDIM,21)=[
- 1073741312, 637560320, 189496832, 27474432, 129338880, ...
- 908054016, 641870336, 186375680, 302677504, 763663872, ...
- 103878144, 325187072, 858254848, 922041856, 261924352, ...
- 954978816, 292822528, 849512960, 210311680, 933232128, ...
- 691981824, 155417088, 627070464, 416795136, 182081024, ...
- 513433088, 848658944, 515770880, 627273216, 629169664, ...
- 414566912, 147450368, 698353152, 244844032, 226578944, ...
- 1020087808, 886978048, 389697024, 1007004160, 839646720, ...
- 621924864, 549962240, 609583616, 735976960, 87342592, ...
- 1058542080, 163066368, 307997184, 876471808, 794280448, ...
- 675386880]';
- DIRECT(1:MAXDIM,22)=[
- 1073741568, 352343296, 644236032, 636735232, 615860480, ...
- 959444224, 287380736, 1007410432, 890187008, 399480576, ...
- 520092928, 643311360, 816901376, 695310080, 1019229440, ...
- 77034240, 733295872, 1035127552, 986582784, 332381952, ...
- 334852352, 364956416, 596672256, 800381696, 480316672, ...
- 574863104, 647347968, 702910208, 499965184, 364968704, ...
- 120862976, 1023256320, 995114240, 13951232, 32520448, ...
- 702127360, 45176064, 444945664, 237860096, 152839936, ...
- 530633984, 429135616, 267272448, 884808960, 933712640, ...
- 61605632, 174335744, 564911360, 302327552, 650589440, ...
- 450649344]';
- DIRECT(1:MAXDIM,23)=[
- 1073741696, 1065385856, 1073734272, 331949184, 842310784, ...
- 799537536, 965852032, 369351808, 662886016, 86119808, ...
- 865109888, 299633792, 422735488, 181087360, 174252416, ...
- 1041212544, 840196224, 750314368, 391053440, 903306880, ...
- 742365312, 236995200, 42492800, 946000512, 771692416, ...
- 897405824, 613803136, 924258688, 808338304, 1038125440, ...
- 683814272, 177186176, 766008960, 704549248, 194555008, ...
- 306383744, 496592512, 416020864, 655186816, 1032204928, ...
- 694773632, 577910144, 45797760, 910332544, 536014976, ...
- 675946368, 987635840, 788223872, 353993856, 96313472, ...
- 85248640]';
- DIRECT(1:MAXDIM,24)=[
- 1073741760, 4210752, 12608, 744788544, 494377792, ...
- 115601344, 769248448, 990895808, 851706304, 979326784, ...
- 692061120, 429015104, 217132864, 736067008, 55694400, ...
- 456152640, 631601984, 787264192, 898599104, 478383808, ...
- 507774272, 458270272, 392995136, 872482496, 124824768, ...
- 1034161344, 362141632, 1053833280, 943810496, 428920128, ...
- 795835200, 835462848, 961843520, 606198080, 785652672, ...
- 154954432, 491617344, 297351232, 580735552, 634587968, ...
- 185277760, 141505600, 417673280, 106907456, 395575616, ...
- 566958656, 352651200, 415242688, 26635200, 1030317504, ...
- 247212992]';
- DIRECT(1:MAXDIM,25)=[
- 1073741792, 543187040, 536882016, 981766752, 357858144, ...
- 810665952, 369083488, 613015520, 86115232, 845149216, ...
- 606076960, 1018241504, 35245536, 635403744, 236633696, ...
- 407451232, 427671904, 460141792, 116344544, 990246688, ...
- 1024892576, 883429408, 150655392, 173476896, 197666464, ...
- 1016740448, 605376608, 970487008, 1006881248, 598265632, ...
- 1022861728, 489055392, 216680608, 371439072, 53140576, ...
- 965114400, 98534112, 209692256, 264598496, 321437280, ...
- 545303840, 324119904, 876587488, 778239712, 802033120, ...
- 44406496, 665829024, 803213920, 309742112, 735181344, ...
- 1036125600]';
- DIRECT(1:MAXDIM,26)=[
- 1073741808, 273698896, 805312112, 903123536, 153504624, ...
- 689632208, 432848944, 859888752, 510853776, 240805744, ...
- 250610192, 852489168, 139460144, 283082224, 222702928, ...
- 342181488, 922872432, 187528656, 360637424, 814514736, ...
- 301037840, 800872624, 272595184, 158627600, 238839088, ...
- 927181136, 710248688, 788854608, 1048376560, 484709072, ...
- 85709008, 1065469744, 429237328, 490778384, 848024144, ...
- 443114288, 687907504, 474573648, 45706416, 681465296, ...
- 805303216, 14567920, 369839504, 440402480, 797652624, ...
- 115959088, 929784560, 91226544, 205943056, 288358704, ...
- 950217296]';
- DIRECT(1:MAXDIM,27)=[
- 1073741816, 947419256, 134232008, 460100200, 1073685336, ...
- 398354904, 1069834248, 686054696, 108299224, 273898840, ...
- 731382552, 938170664, 86812552, 677346808, 602208712, ...
- 652635752, 209797064, 323968376, 384078968, 561178056, ...
- 923399256, 996597176, 942777416, 885167400, 89791048, ...
- 956122504, 87393464, 987661336, 993412952, 827749496, ...
- 903211272, 33649816, 594875176, 65052056, 822835240, ...
- 625704888, 1065374584, 612232920, 536299720, 1046858504, ...
- 939518840, 160843032, 654656088, 744496936, 872197704, ...
- 219111576, 829112632, 455614152, 1064192952, 313010856, ...
- 820754920]';
- DIRECT(1:MAXDIM,28)=[
- 1073741820, 71582788, 603989028, 37500, 120660, ...
- 182195932, 213921796, 473570692, 41763004, 156352828, ...
- 88343188, 698012780, 666108868, 337608156, 1054329884, ...
- 799472220, 641885244, 392104980, 502284340, 1002405628, ...
- 249907140, 75586228, 206587660, 565275348, 1021426548, ...
- 425987996, 598058580, 401940420, 919427316, 822049324, ...
- 115655868, 759299588, 562394644, 990942164, 1003212268, ...
- 598750292, 675334852, 675293340, 445665316, 903023756, ...
- 872412692, 172640916, 1051615436, 91229620, 94586692, ...
- 344873452, 7029156, 683421900, 434258804, 955002092, ...
- 436424380]';
- DIRECT(1:MAXDIM,29)=[
- 1073741822, 644245094, 1040195102, 537039474, 537089354, ...
- 642656334, 73402402, 664239174, 1014620426, 500917234, ...
- 1042677826, 347788318, 1069154738, 373259762, 362587674, ...
- 239395914, 132283950, 903121466, 445210638, 968851198, ...
- 230153254, 935549622, 308815630, 861891286, 496995094, ...
- 670740382, 657311830, 573565382, 248331478, 1064650798, ...
- 338312798, 669059078, 1065190902, 379125622, 111897166, ...
- 520650422, 740300390, 1046483950, 66254898, 992513134, ...
- 234871606, 610553330, 450553866, 566758134, 787800806, ...
- 1071709866, 971732606, 528102354, 790919122, 917384366, ...
- 656244162]';
- DIRECT(1:MAXDIM,30)=[
- 1073741823, 357913941, 50344755, 268538457, 805540473, ...
- 3487029, 3146769, 592038967, 729591963, 781578389, ...
- 66781679, 113956361, 331153483, 967802327, 935343371, ...
- 324351309, 609305915, 818137857, 131059769, 918519549, ...
- 827341719, 922770101, 456972047, 363883221, 1057014661, ...
- 900956063, 580478293, 520383687, 315470533, 227601711, ...
- 169598765, 909227271, 796983815, 349496709, 393974911, ...
- 378320037, 777004343, 927999269, 616377385, 345930959, ...
- 989849787, 627400495, 892675125, 260314121, 1041964063, ...
- 531367163, 195776757, 237309785, 949187605, 719002587, ...
- 495745187]';
-end
-
-%
-% TRAP FOR A WRONG SUBROUTINE CALL
-%
-if ((I<0) | (N<1) | (I>MAXNUM) | (N>MAXDIM)),
- disp('LP-TAU CALL FAILED')
- disp(' PRESS <ENTER> TO EXIT LPTAU')
- pause
- return
-end
-if ((PRVNUM+1==I) & (N<=PRVDIM)),
- %
- % RECURRENT GENERATION OF THE POINT
- %
- %
- % SEARCH POSITION OF THE RIGHTMOST "1"
- % IN THE BINARY REPRESENTATION OF I
- %
- L=0;
- POS=0;
- while L<QP & POS==0,
- L=L+1;
- POS=bitand(bitshift(I,-(L-1)),1);
- end
- %
- % RIGHTMOST POSITION IS L
- %
- for J=1:N
- MASKV(J)=bitxor(MASKV(J),DIRECT(J,L));
- VECTOR(J)=MASKV(J)*SCALE;
- end
-else
- %
- % GENERATION OF THE POINT FROM "I" AND "N"
- %
- MASKV=zeros(1,N);
- IM=bitxor(I,bitshift(I,-1));
- M=0;
- while IM~=0 & M<QP,
- M=M+1;
- if (bitand(IM,1)==1),
- for J=1:N
- MASKV(J)=bitxor(MASKV(J),DIRECT(J,M));
- end
- end
- IM=bitshift(IM,-1);
- end
- for J=1:N
- VECTOR(J)=MASKV(J)*SCALE;
- end
-end
-%
-PRVNUM=I;
-PRVDIM=N;
-return
-
-
diff --git a/GSA_distrib/4.0.3/Morris_Measure_Groups.m b/GSA_distrib/4.0.3/Morris_Measure_Groups.m
deleted file mode 100644
index c5a71b057a3d8029f6abdf621f82816465b7f4be..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/Morris_Measure_Groups.m
+++ /dev/null
@@ -1,130 +0,0 @@
-
-function [SAmeas, OutMatrix] = Morris_Measure_Groups(NumFact, Sample, Output, p, Group)
-
-% [SAmeas, OutMatrix] = Morris_Measure_Groups(NumFact, Sample, Output, p, Group)
-%
-% Given the Morris sample matrix, the output values and the group matrix compute the Morris measures
-% -------------------------------------------------------------------------
-% INPUTS
-% -------------------------------------------------------------------------
-% Group [NumFactor, NumGroups] := Matrix describing the groups.
-% Each column represents one group.
-% The element of each column are zero if the factor is not in the
-% group. Otherwise it is 1.
-
-% Sample := Matrix of the Morris sampled trajectories
-
-% Output := Matrix of the output(s) values in correspondence of each point
-% of each trajectory
-
-% k = Number of factors
-% -------------------------------------------------------------------------
-% OUTPUTS
-% OutMatrix (NumFactor*NumOutputs, 3)= [Mu*, Mu, StDev]
-% for each output it gives the three measures of each factor
-% -------------------------------------------------------------------------
-
-if nargin==0,
- disp(' ')
- disp('[SAmeas, OutMatrix] = Morris_Measure_Groups(NumFact, Sample, Output, p, Group);')
- return
-end
-
-OutMatrix=[];
-if nargin < 5, Group=[]; end
-
-NumGroups = size(Group,2);
-if nargin < 4 | isempty(p),
- p = 4;
-end
-Delt = p/(2*p-2);
-
-if NumGroups ~ 0
- sizea = NumGroups; % Number of groups
- GroupMat=Group;
- GroupMat = GroupMat';
-else
- sizea = NumFact;
-end
-r=size(Sample,1)/(sizea+1); % Number of trajectories
-
-% For Each Output
-for k=1:size(Output,2)
-
- OutValues=Output(:,k);
-
- % For each r trajectory
- for i=1:r
-
- % For each step j in the trajectory
- % Read the orientation matrix fact for the r-th sampling
- % Read the corresponding output values
- Single_Sample = Sample(i+(i-1)*sizea:i+(i-1)*sizea+sizea,:);
- Single_OutValues = OutValues(i+(i-1)*sizea:i+(i-1)*sizea+sizea,:);
- A = (Single_Sample(2:sizea+1,:)-Single_Sample(1:sizea,:))';
- Delta = A(find(A));
-
- % For each point of the fixed trajectory compute the values of the Morris function. The function
- % is partitioned in four parts, from order zero to order 4th.
- for j=1:sizea % For each point in the trajectory i.e for each factor
- % matrix of factor which changes
- if NumGroups ~ 0;
- AuxFind (:,1) = A(:,j);
-% AuxFind(find(A(:,j)),1)=1;
-% Pippo = sum((Group - repmat(AuxFind,1,NumGroups)),1);
-% Change_factor(j,i) = find(Pippo==0);
- Change_factor = find(abs(AuxFind)>1e-010);
- % If we deal with groups we can only estimate the new mu*
- % measure since factors in the same groups can move in
- % opposite direction and the definition of the standard
- % Morris mu cannopt be applied.
- % In the new version the elementary effect is defined with
- % the absolute value.
- %SAmeas(find(GroupMat(Change_factor(j,i),:)),i) = abs((Single_OutValues(j) - Single_OutValues(j+1) )/Delt); %(2/3));
- SAmeas(i,Change_factor') = abs((Single_OutValues(j) - Single_OutValues(j+1) )/Delt);
- else
- Change_factor(j,i) = find(Single_Sample(j+1,:)-Single_Sample(j,:));
- % If no groups --> we compute both the original and
- % modified measure
- if Delta(j) > 0 %=> +Delta
- SAmeas(Change_factor(j,i),i) = (Single_OutValues(j+1) - Single_OutValues(j) )/Delt; %(2/3);
- else %=> -Delta
- SAmeas(Change_factor(j,i),i) = (Single_OutValues(j) - Single_OutValues(j+1) )/Delt; %(2/3);
- end
- end
- end %for j=1:sizea
-
- end %for i=1:r
-
- if NumGroups ~ 0
- SAmeas = SAmeas';
- end
-
- % Compute Mu AbsMu and StDev
- if any(any(isnan(SAmeas)))
- for j=1:NumFact,
- SAm = SAmeas(j,:);
- SAm = SAm(find(~isnan(SAm)));
- rr=length(SAm);
- AbsMu(j,1) = sum(abs(SAm),2)/rr;
- if NumGroups == 0
- Mu(j,1) = sum(SAm,2)/rr;
- StDev(j,1) = sum((SAm - repmat(Mu(j),1,rr)).^2/(rr*(rr-1)),2).^0.5;
- end
- end
- else
- AbsMu = sum(abs(SAmeas),2)/r;
- if NumGroups == 0
- Mu = sum(SAmeas,2)/r;
- StDev = sum((SAmeas - repmat(Mu,1,r)).^2/(r*(r-1)),2).^0.5;
- end
- end
-
- % Define the output Matrix - if we have groups we cannot define the old
- % measure mu, only mu* makes sense
- if NumGroups > 0
- OutMatrix = [OutMatrix; AbsMu];
- else
- OutMatrix = [OutMatrix; AbsMu, Mu, StDev];
- end
-end % For Each Output
diff --git a/GSA_distrib/4.0.3/Sampling_Function_2.m b/GSA_distrib/4.0.3/Sampling_Function_2.m
deleted file mode 100644
index ccd3a87f91051686bea0d3a406e751223b076ca6..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/Sampling_Function_2.m
+++ /dev/null
@@ -1,174 +0,0 @@
-function [Outmatrix, OutFact] = Sampling_Function_2(p, k, r, UB, LB, GroupMat)
-%[Outmatrix, OutFact] = Sampling_Function_2(p, k, r, UB, LB, GroupMat)
-% Inputs: k (1,1) := number of factors examined or number of groups examined.
-% In case the groups are chosen the number of factors is stores in NumFact and
-% sizea becomes the number of created groups.
-% NumFact (1,1) := number of factors examined in the case when groups are chosen
-% r (1,1) := sample size
-% p (1,1) := number of intervals considered in [0, 1]
-% UB(sizea,1) := Upper Bound for each factor
-% LB(sizea,1) := Lower Bound for each factor
-% GroupNumber(1,1) := Number of groups (eventually 0)
-% GroupMat(NumFact,GroupNumber):= Matrix which describes the chosen groups. Each column represents a group and its elements
-% are set to 1 in correspondence of the factors that belong to the fixed group. All
-% the other elements are zero.
-% Local Variables:
-% sizeb (1,1) := sizea+1
-% sizec (1,1) := 1
-% randmult (sizea,1) := vector of random +1 and -1
-% perm_e(1,sizea) := vector of sizea random permutated indeces
-% fact(sizea) := vector containing the factor varied within each traj
-% DDo(sizea,sizea) := D* in Morris, 1991
-% A(sizeb,sizea) := Jk+1,k in Morris, 1991
-% B(sizeb,sizea) := B in Morris, 1991
-% Po(sizea,sizea) := P* in Morris, 1991
-% Bo(sizeb,sizea) := B* in Morris, 1991
-% Ao(sizeb,sizec) := Jk+1,1 in Morris, 1991
-% xo(sizec,sizea) := x* in Morris, 1991 (starting point for the trajectory)
-% In(sizeb,sizea) := for each loop orientation matrix. It corresponds to a trajectory
-% of k step in the parameter space and it provides a single elementary
-% effect per factor
-% MyInt()
-% Fact(sizea,1) := for each loop vector indicating which factor or group of factors has been changed
-% in each step of the trajectory
-% AuxMat(sizeb,sizea) := Delta*0.5*((2*B - A) * DD0 + A) in Morris, 1991. The AuxMat is used as in Morris design
-% for single factor analysis, while it constitutes an intermediate step for the group analysis.
-%
-% Output: Outmatrix(sizeb*r, sizea) := for the entire sample size computed In(i,j) matrices
-% OutFact(sizea*r,1) := for the entire sample size computed Fact(i,1) vectors
-%
-% Note: B0 is constructed as in Morris design when groups are not considered. When groups are considered the routine
-% follows the following steps:
-% 1- Creation of P0 and DD0 matrices defined in Morris for the groups. This means that the dimensions of these
-% 2 matrices are (GroupNumber,GroupNumber).
-% 2- Creation of AuxMat matrix with (GroupNumber+1,GroupNumber) elements.
-% 3- Definition of GroupB0 starting from AuxMat, GroupMat and P0.
-% 4- The final B0 for groups is obtained as [ones(sizeb,1)*x0' + GroupB0]. The P0 permutation is present in GroupB0
-% and it's not necessary to permute the matrix (ones(sizeb,1)*x0') because it's already randomly created.
-% Reference:
-% A. Saltelli, K. Chan, E.M. Scott, "Sensitivity Analysis" on page 68 ss
-%
-% F. Campolongo, J. Cariboni, JRC - IPSC Ispra, Varese, IT
-% Last Update: 15 November 2005 by J.Cariboni
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-
-% Parameters and initialisation of the output matrix
-sizea = k;
-Delta = p/(2*p-2);
-%Delta = 1/3
-NumFact = sizea;
-GroupNumber = size(GroupMat,2);
-
-if GroupNumber ~ 0;
- sizea = size(GroupMat,2);
-end
-
-sizeb = sizea + 1;
-sizec = 1;
-Outmatrix = [];
-OutFact = [];
-
-% For each i generate a trajectory
-for i=1:r
-
- % Construct DD0 - OLD VERSION - it does not need communication toolbox
- % RAND(N,M) is an NXM matrix with random entries, chosen from a uniform distribution on the interval (0.0,1.0).
- % Note that DD0 tells if the factor have to be increased or ddecreased
- % by Delta.
- randmult = ones(k,1);
- v = rand(k,1);
- randmult (find(v < 0.5))=-1;
- randmult = repmat(randmult,1,k);
- DD0 = randmult .* eye(k);
-
- % Construct DD0 - NEW VERSION - it needs communication toolbox
- % randsrc(m) generates an m-by-m matrix, each of whose entries independently takes the value -1 with probability 1/2,
- % and 1 with probability 1/2.
- % DD0 = randsrc(NumFact) .* eye(NumFact);
-
- % Construct B (lower triangular)
- B = ones(sizeb,sizea);
- for j = 1:sizea
- B(1:j,j)=0;
- end
-
- % Construct A0, A
- A0 = ones(sizeb,1);
- A = ones(sizeb,NumFact);
-
- % Construct the permutation matrix P0. In each column of P0 one randomly chosen element equals 1
- % while all the others equal zero.
- % P0 tells the order in which order factors are changed in each
- % trajectory. P0 is created as it follows:
- % 1) All the elements of P0 are set equal to zero ==> P0 = zeros (sizea, sizea);
- % 2) The function randperm create a random permutation of integer 1:sizea, without repetitions ==> perm_e;
- % 3) In each column of P0 the element indicated in perm_e is set equal to one.
- % Note that P0 is then used reading it by rows.
- P0 = zeros (sizea, sizea);
- perm_e = randperm(sizea); % RANDPERM(n) is a random permutation of the integers from 1 to n.
- for j = 1:sizea
- P0(perm_e(j),j) = 1;
- end
-
- % When groups are present the random permutation is done only on B. The effect is the same since
- % the added part (A0*x0') is completely random.
- if GroupNumber ~ 0
- B = B * (GroupMat*P0')';
- end
-
- % Compute AuxMat both for single factors and groups analysis. For Single factors analysis
- % AuxMat is added to (A0*X0) and then permutated through P0. When groups are active AuxMat is
- % used to build GroupB0. AuxMat is created considering DD0. If the element on DD0 diagonal
- % is 1 then AuxMat will start with zero and add Delta. If the element on DD0 diagonal is -1
- % then DD0 will start Delta and goes to zero.
- AuxMat = Delta*0.5*((2*B - A) * DD0 + A);
-
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
- % a --> Define the random vector x0 for the factors. Note that x0 takes value in the hypercube
- % [0,...,1-Delta]*[0,...,1-Delta]*[0,...,1-Delta]*[0,...,1-Delta]
- MyInt = repmat([0:(1/(p-1)):(1-Delta)],NumFact,1); % Construct all possible values of the factors
-
- % OLD VERSION - it needs communication toolbox
- % w = randint(NumFact,1,[1,size(MyInt,2)]);
-
- % NEW VERSION - construct a version of random integers
- % 1) create a vector of random integers
- % 2) divide [0,1] into the needed steps
- % 3) check in which interval the random numbers fall
- % 4) generate the corresponding integer
- v = repmat(rand(NumFact,1),1,size(MyInt,2)+1); % 1)
- IntUsed = repmat([0:1/size(MyInt,2):1],NumFact,1); % 2)
- DiffAuxVec = IntUsed - v; % 3)
-
- for ii = 1:size(DiffAuxVec,1)
- w(1,ii) = max(find(DiffAuxVec(ii,:)<0)); % 4)
- end
- x0 = MyInt(1,w)'; % Define x0
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
- % b --> Compute the matrix B*, here indicated as B0. Each row in B0 is a
- % trajectory for Morris Calculations. The dimension of B0 is (Numfactors+1,Numfactors)
- if GroupNumber ~ 0
- B0 = (A0*x0' + AuxMat);
- else
- B0 = (A0*x0' + AuxMat)*P0;
- end
-
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
- % c --> Compute values in the original intervals
- % B0 has values x(i,j) in [0, 1/(p -1), 2/(p -1), ... , 1].
- % To obtain values in the original intervals [LB, UB] we compute
- % LB(j) + x(i,j)*(UB(j)-LB(j))
- In = repmat(LB,1,sizeb)' + B0 .* repmat((UB-LB),1,sizeb)';
-
- % Create the Factor vector. Each component of this vector indicate which factor or group of factor
- % has been changed in each step of the trajectory.
- for j=1:sizea
- Fact(1,j) = find(P0(j,:));
- end
- Fact(1,sizea+1) = 0;
-
- Outmatrix = [Outmatrix; In];
- OutFact = [OutFact; Fact'];
-
-end
\ No newline at end of file
diff --git a/GSA_distrib/4.0.3/beta_inv.m b/GSA_distrib/4.0.3/beta_inv.m
deleted file mode 100644
index d3c95836dd060c5dbcdc1f300131576955360dfb..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/beta_inv.m
+++ /dev/null
@@ -1,38 +0,0 @@
-function x = beta_inv(p, a, b)
-% PURPOSE: inverse of the cdf (quantile) of the beta(a,b) distribution
-%--------------------------------------------------------------
-% USAGE: x = beta_inv(p,a,b)
-% where: p = vector of probabilities
-% a = beta distribution parameter, a = scalar
-% b = beta distribution parameter b = scalar
-% NOTE: mean [beta(a,b)] = a/(a+b), variance = ab/((a+b)*(a+b)*(a+b+1))
-%--------------------------------------------------------------
-% RETURNS: x at each element of p for the beta(a,b) distribution
-%--------------------------------------------------------------
-% SEE ALSO: beta_d, beta_pdf, beta_inv, beta_rnd
-%--------------------------------------------------------------
-
-% Anders Holtsberg, 18-11-93
-% Copyright (c) Anders Holtsberg
-% documentation modified by LeSage to
-% match the format of the econometrics toolbox
-
-if (nargin ~= 3)
- error('Wrong # of arguments to beta_inv');
-end
-
-if any(any((a<=0)|(b<=0)))
- error('beta_inv parameter a or b is nonpositive');
-end
-if any(any(abs(2*p-1)>1))
- error('beta_inv: A probability should be 0<=p<=1');
-end
-
-x = a ./ (a+b);
-dx = 1;
-while any(any(abs(dx)>256*eps*max(x,1)))
- dx = (betainc(x,a,b) - p) ./ beta_pdf(x,a,b);
- x = x - dx;
- x = x + (dx - x) / 2 .* (x<0);
-end
-
\ No newline at end of file
diff --git a/GSA_distrib/4.0.3/beta_pdf.m b/GSA_distrib/4.0.3/beta_pdf.m
deleted file mode 100644
index 8412fbdce51af35e893bcb501b60230e49e3e1b0..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/beta_pdf.m
+++ /dev/null
@@ -1,32 +0,0 @@
-function pdf = beta_pdf(x, a, b)
-% PURPOSE: pdf of the beta(a,b) distribution
-%--------------------------------------------------------------
-% USAGE: pdf = beta_pdf(x,a,b)
-% where: x = vector of components
-% a = beta distribution parameter, a = scalar
-% b = beta distribution parameter b = scalar
-% NOTE: mean[(beta(a,b)] = a/(a+b), variance = ab/((a+b)*(a+b)*(a+b+1))
-%--------------------------------------------------------------
-% RETURNS: pdf at each element of x of the beta(a,b) distribution
-%--------------------------------------------------------------
-% SEE ALSO: beta_d, beta_pdf, beta_inv, beta_rnd
-%--------------------------------------------------------------
-
-% Anders Holtsberg, 18-11-93
-% Copyright (c) Anders Holtsberg
-% documentation modified by LeSage to
-% match the format of the econometrics toolbox
-
-
-if (nargin ~=3)
- error('Wrong # of arguments to beta_pdf');
-end
-
-if any(any((a<=0)|(b<=0)))
- error('Parameter a or b is nonpositive');
-end
-
-I = find((x<0)|(x>1));
-
-pdf = x.^(a-1) .* (1-x).^(b-1) ./ beta(a,b);
-pdf(I) = 0*I;
diff --git a/GSA_distrib/4.0.3/cumplot.m b/GSA_distrib/4.0.3/cumplot.m
deleted file mode 100644
index a700d37842a1c4ddb3a9adb34a4780c90e5b5685..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/cumplot.m
+++ /dev/null
@@ -1,14 +0,0 @@
-function h = cumplot(x);
-%function h =cumplot(x)
-% Copyright (C) 2005 Marco Ratto
-
-
-n=length(x);
-x=[-inf; sort(x); Inf];
-y=[0:n n]./n;
-h0 = stairs(x,y);
-grid on,
-
-if nargout,
- h=h0;
-end
diff --git a/GSA_distrib/4.0.3/dat_fil_.m b/GSA_distrib/4.0.3/dat_fil_.m
deleted file mode 100644
index 0b3ac8f8e7499ca8f48b610df9a04c2fdcfe48c1..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/dat_fil_.m
+++ /dev/null
@@ -1,30 +0,0 @@
-function c = dat_fil_(data_file);
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-try
- eval(data_file);
-catch
- load(data_file);
-end
-clear data_file;
-
-a=who;
-
-for j=1:length(a)
- eval(['c.',a{j},'=',a{j},';']);
-end
\ No newline at end of file
diff --git a/GSA_distrib/4.0.3/dynare_MC.m b/GSA_distrib/4.0.3/dynare_MC.m
deleted file mode 100644
index 26a8135ea2195268b921364a9eecd77f275fdba8..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/dynare_MC.m
+++ /dev/null
@@ -1,142 +0,0 @@
-function dynare_MC(var_list_,OutDir)
-%
-% Adapted by M. Ratto from dynare_estimation.m and posteriorsmoother.m
-% (dynare_estimation.m and posteriorsmoother.m are part of DYNARE,
-% copyright M. Juillard)
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global M_ options_ oo_ estim_params_
-global bayestopt_
-
-if options_.filtered_vars ~= 0 & options_.filter_step_ahead == 0
- options_.filter_step_ahead = 1;
-end
-if options_.filter_step_ahead ~= 0
- options_.nk = max(options_.filter_step_ahead);
-else
- options_.nk = 0;
-end
-
-
-nvx = estim_params_.nvx;
-nvn = estim_params_.nvn;
-ncx = estim_params_.ncx;
-ncn = estim_params_.ncn;
-np = estim_params_.np ;
-npar = nvx+nvn+ncx+ncn+np;
-
-if isempty(options_.datafile)
- error('ESTIMATION: datafile option is missing')
-end
-
-if isempty(options_.varobs)
- error('ESTIMATION: VAROBS is missing')
-end
-
-%% Read and demean data
-rawdata = read_variables(options_.datafile,options_.varobs,[],options_.xls_sheet,options_.xls_range);
-
-options_ = set_default_option(options_,'nobs',size(rawdata,1)-options_.first_obs+1);
-gend = options_.nobs;
-
-rawdata = rawdata(options_.first_obs:options_.first_obs+gend-1,:);
-if options_.loglinear == 1 & ~options_.logdata
- rawdata = log(rawdata);
-end
-if options_.prefilter == 1
- bayestopt_.mean_varobs = mean(rawdata,1);
- data = transpose(rawdata-ones(gend,1)*bayestopt_.mean_varobs);
-else
- data = transpose(rawdata);
-end
-
-if ~isreal(rawdata)
- error(['There are complex values in the data. Probably a wrong' ...
- ' transformation'])
-end
-
-offset = npar-np;
-fname_=M_.fname;
-
-options_ = set_default_option(options_,'opt_gsa',1);
-options_gsa_ = options_.opt_gsa;
-
-if options_gsa_.pprior,
- namfile=[fname_,'_prior'];
-else
- namfile=[fname_,'_mc'];
-end
-load([OutDir,'\',namfile],'lpmat', 'lpmat0', 'istable')
-% load(options_.mode_file)
-%%
-%%
-%%
-x=[lpmat0(istable,:) lpmat(istable,:)];
-clear lpmat lpmat0 istable %iunstable egg yys T
-B = size(x,1);
-[atT,innov,measurement_error,filtered_state_vector,ys,trend_coeff, aK] = DsgeSmoother(x(1,:)',gend,data);
-n1=size(atT,1);
-
-nfil=B/40;
-stock_smooth = zeros(M_.endo_nbr,gend,40);
-stock_filter = zeros(M_.endo_nbr,gend+1,40);
-stock_ys = zeros(40, M_.endo_nbr);
-logpo2=zeros(B,1);
-%%
-h = waitbar(0,'MC smoother ...');
-delete([OutDir,'\',namfile,'_*.mat'])
-ib=0;
-ifil=0;
-opt_gsa=options_.opt_gsa;
-for b=1:B
- ib=ib+1;
- deep = x(b,:)';
- set_all_parameters(deep);
- dr = resol(oo_.steady_state,0);
- %deep(1:offset) = xparam1(1:offset);
- logpo2(b,1) = DsgeLikelihood(deep,gend,data);
- if opt_gsa.lik_only==0,
- [atT,innov,measurement_error,filtered_state_vector,ys,trend_coeff, aK] = DsgeSmoother(deep,gend,data);
- stock_smooth(:,:,ib)=atT(1:M_.endo_nbr,:);
-% stock_filter(:,:,ib)=filtered_state_vector(1:M_.endo_nbr,:);
- stock_filter(:,:,ib)=aK(1,1:M_.endo_nbr,:);
- stock_ys(ib,:)=ys';
- if ib==40,
- ib=0;
- ifil=ifil+1;
- save([OutDir,'\',namfile,'_',num2str(ifil)],'stock_smooth','stock_filter','stock_ys')
- stock_smooth = zeros(M_.endo_nbr,gend,40);
- stock_filter = zeros(M_.endo_nbr,gend+1,40);
- stock_ys = zeros(40, M_.endo_nbr);
- end
- end
- waitbar(b/B,h,['MC smoother ...',num2str(b),'/',num2str(B)]);
-end
-close(h)
-if opt_gsa.lik_only==0,
-if ib>0,
- ifil=ifil+1;
- stock_smooth = stock_smooth(:,:,1:ib);
- stock_filter = stock_filter(:,:,1:ib);
- stock_ys = stock_ys(1:ib,:);
- save([OutDir,'\',namfile,'_',num2str(ifil)],'stock_smooth','stock_filter','stock_ys')
-end
-end
-stock_gend=gend;
-stock_data=data;
-save([OutDir,'\',namfile],'x','logpo2','stock_gend','stock_data','-append')
diff --git a/GSA_distrib/4.0.3/filt_mc_.m b/GSA_distrib/4.0.3/filt_mc_.m
deleted file mode 100644
index 41d5e7ae886e467fcf21dfc13cf16bc0d4857cb3..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/filt_mc_.m
+++ /dev/null
@@ -1,708 +0,0 @@
-function [rmse_MC, ixx] = filt_mc_(OutDir)
-% function [rmse_MC, ixx] = filt_mc_(OutDir)
-% copyright Marco Ratto 2006
-% inputs (from opt_gsa structure)
-% vvarvecm = options_gsa_.var_rmse;
-% loadSA = options_gsa_.load_rmse;
-% pfilt = options_gsa_.pfilt_rmse;
-% alpha = options_gsa_.alpha_rmse;
-% alpha2 = options_gsa_.alpha2_rmse;
-% istart = options_gsa_.istart_rmse;
-% alphaPC = 0.5;
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global bayestopt_ estim_params_ M_ options_ oo_
-
-options_gsa_=options_.opt_gsa;
-vvarvecm = options_gsa_.var_rmse;
-loadSA = options_gsa_.load_rmse;
-pfilt = options_gsa_.pfilt_rmse;
-alpha = options_gsa_.alpha_rmse;
-alpha2 = options_gsa_.alpha2_rmse;
-istart = options_gsa_.istart_rmse;
-alphaPC = 0.5;
-
-fname_ = M_.fname;
-lgy_ = M_.endo_names;
-dr_ = oo_.dr;
-
-disp(' ')
-disp(' ')
-disp('Starting sensitivity analysis')
-disp('for the fit of EACH observed series ...')
-disp(' ')
-disp('Deleting old SA figures...')
-a=dir([OutDir,'\*.*']);
-tmp1='0';
-if options_.opt_gsa.ppost,
- tmp=['_rmse_post'];
-else
- if options_.opt_gsa.pprior
- tmp=['_rmse_prior'];
- else
- tmp=['_rmse_mc'];
- end
- if options_gsa_.lik_only,
- tmp1 = [tmp,'_post_SA'];
- tmp = [tmp,'_lik_SA'];
- end
-end
-for j=1:length(a),
- if strmatch([fname_,tmp],a(j).name),
- disp(a(j).name)
- delete([OutDir,'\',a(j).name])
- end,
- if strmatch([fname_,tmp1],a(j).name),
- disp(a(j).name)
- delete([OutDir,'\',a(j).name])
- end,
-end
-disp('done !')
-
-
-nshock=estim_params_.nvx + estim_params_.nvn + estim_params_.ncx + estim_params_.ncn;
-npar=estim_params_.np;
-if ~isempty(options_.mode_file),
- load(options_.mode_file,'xparam1'),
-end
-if options_.opt_gsa.ppost,
- c=load([fname_,'_mean'],'xparam1');
- xparam1_mean=c.xparam1;
- clear c
-elseif ~isempty(options_.mode_file) & ~isempty(ls([fname_,'_mean.mat']))
- c=load([fname_,'_mean'],'xparam1');
- xparam1_mean=c.xparam1;
- clear c
-end
-
-if options_.opt_gsa.ppost,
- fnamtmp=[fname_,'_post'];
- DirectoryName = CheckPath('metropolis');
-else
- if options_.opt_gsa.pprior
- fnamtmp=[fname_,'_prior'];
- else
- fnamtmp=[fname_,'_mc'];
- end
-end
-if ~loadSA,
- if exist('xparam1','var')
- set_all_parameters(xparam1);
- steady_;
- ys_mode=oo_.steady_state;
- end
- if exist('xparam1_mean','var')
- set_all_parameters(xparam1_mean);
- steady_;
- ys_mean=oo_.steady_state;
- end
-% eval(options_.datafile)
- obs = dat_fil_(options_.datafile);
- if ~options_.opt_gsa.ppost
- load([OutDir,'\',fnamtmp],'x','logpo2','stock_gend','stock_data');
- logpo2=-logpo2;
- else
- %load([DirectoryName '/' M_.fname '_data.mat']);
- [stock_gend, stock_data] = read_data;
- filfilt = dir([DirectoryName '/' M_.fname '_filter*.mat']);
- filparam = dir([DirectoryName '/' M_.fname '_param*.mat']);
- x=[];
- logpo2=[];
- sto_ys=[];
- for j=1:length(filparam),
- %load([DirectoryName '/' M_.fname '_param',int2str(j),'.mat']);
- if isempty(strmatch([M_.fname '_param_irf'],filparam(j).name))
- load([DirectoryName '/' filparam(j).name]);
- x=[x; stock];
- logpo2=[logpo2; stock_logpo];
- sto_ys=[sto_ys; stock_ys];
- clear stock stock_logpo stock_ys;
- end
- end
- end
- nruns=size(x,1);
- nfilt=floor(pfilt*nruns);
- if options_.opt_gsa.ppost | (options_.opt_gsa.ppost==0 & options_.opt_gsa.lik_only==0)
- disp(' ')
- disp('Computing RMSE''s...')
- fobs = options_.first_obs;
- nobs=options_.nobs;
- for i=1:size(vvarvecm,1),
- vj=deblank(vvarvecm(i,:));
- eval(['vobs =obs.',vj,'(fobs:fobs-1+nobs);'])
- if options_.prefilter == 1
- %eval([vj,'=',vj,'-bayestopt_.mean_varobs(i);'])
- %eval([vj,'=',vj,'-mean(',vj,',1);'])
- vobs = vobs-mean(vobs,1);
- end
-
- jxj = strmatch(vj,lgy_(dr_.order_var,:),'exact');
- js = strmatch(vj,lgy_,'exact');
- if exist('xparam1','var')
-% if isfield(oo_,'FilteredVariables')
-% eval(['rmse_mode(i) = sqrt(mean((vobs(istart:end)-oo_.steady_state(js)-oo_.FilteredVariables.',vj,'(istart:end-1)).^2));'])
-% else
- [alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK] = DsgeSmoother(xparam1,stock_gend,stock_data);
- y0 = squeeze(aK(1,jxj,:)) + ...
- kron(ys_mode(js,:),ones(size(aK,3),1));
-% y0 = ahat(jxj,:)' + ...
-% kron(ys_mode(js,:),ones(size(ahat,2),1));
- rmse_mode(i) = sqrt(mean((vobs(istart:end)-y0(istart:length(vobs))).^2));
-% end
- end
- y0=zeros(nobs+1,nruns);
- if options_.opt_gsa.ppost
- %y0=zeros(nobs+max(options_.filter_step_ahead),nruns);
- nbb=0;
- for j=1:length(filfilt),
- load([DirectoryName '/' M_.fname '_filter_step_ahead',num2str(j),'.mat']);
- nb = size(stock,4);
-% y0(:,nbb+1:nbb+nb)=squeeze(stock(1,js,:,:)) + ...
-% kron(sto_ys(nbb+1:nbb+nb,js)',ones(size(stock,3),1));
- y0(:,nbb+1:nbb+nb)=squeeze(stock(1,js,1:nobs+1,:)) + ...
- kron(sto_ys(nbb+1:nbb+nb,js)',ones(nobs+1,1));
- %y0(:,:,size(y0,3):size(y0,3)+size(stock,3))=stock;
- nbb=nbb+nb;
- clear stock;
- end
- else
- filfilt=ls([OutDir,'\',fnamtmp,'_*.mat']);
- nbb=0;
- for j=1:size(filfilt,1),
- load([OutDir,'\',fnamtmp,'_',num2str(j),'.mat'],'stock_filter','stock_ys');
- nb = size(stock_filter,3);
- y0(:,nbb+1:nbb+nb) = squeeze(stock_filter(jxj,:,:)) + ...
- kron(stock_ys(:,js)',ones(nobs+1,1));
- %y0(:,:,size(y0,3):size(y0,3)+size(stock,3))=stock;
- nbb=nbb+nb;
- clear stock_filter;
- end
-
-% y0 = squeeze(stock_filter(:,jxj,:)) + ...
-% kron(stock_ys(js,:),ones(size(stock_filter,1),1));
- end
- y0M=mean(y0,2);
- for j=1:nruns,
- rmse_MC(j,i) = sqrt(mean((vobs(istart:end)-y0(istart:end-1,j)).^2));
- end
- if exist('xparam1_mean','var')
- %eval(['rmse_pmean(i) = sqrt(mean((',vj,'(fobs-1+istart:fobs-1+nobs)-y0M(istart:end-1)).^2));'])
- [alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK] = DsgeSmoother(xparam1_mean,stock_gend,stock_data);
- y0 = squeeze(aK(1,jxj,:)) + ...
- kron(ys_mean(js,:),ones(size(aK,3),1));
-% y0 = ahat(jxj,:)' + ...
-% kron(ys_mean(js,:),ones(size(ahat,2),1));
- rmse_pmean(i) = sqrt(mean((vobs(istart:end)-y0(istart:length(vobs))).^2));
- end
- end
- clear stock_filter;
- end
- for j=1:nruns,
- lnprior(j,1) = priordens(x(j,:),bayestopt_.pshape,bayestopt_.p1,bayestopt_.p2,bayestopt_.p3,bayestopt_.p4);
- end
- likelihood=logpo2(:)-lnprior(:);
- disp('... done!')
-
- if options_.opt_gsa.ppost
- save([OutDir,'\',fnamtmp], 'x', 'logpo2', 'likelihood', 'rmse_MC', 'rmse_mode','rmse_pmean')
- else
- if options_.opt_gsa.lik_only
- save([OutDir,'\',fnamtmp], 'likelihood', '-append')
- else
- save([OutDir,'\',fnamtmp], 'likelihood', 'rmse_MC','-append')
- if exist('xparam1_mean','var')
- save([OutDir,'\',fnamtmp], 'rmse_pmean','-append')
- end
- if exist('xparam1','var')
- save([OutDir,'\',fnamtmp], 'rmse_mode','-append')
- end
- end
- end
-else
- if options_.opt_gsa.lik_only & options_.opt_gsa.ppost==0
- load([OutDir,'\',fnamtmp],'x','logpo2','likelihood');
- else
- load([OutDir,'\',fnamtmp],'x','logpo2','likelihood','rmse_MC','rmse_mode','rmse_pmean');
- end
- lnprior=logpo2(:)-likelihood(:);
- nruns=size(x,1);
- nfilt=floor(pfilt*nruns);
-end
-% smirnov tests
-nfilt0=nfilt*ones(size(vvarvecm,1),1);
-logpo2=logpo2(:);
-if ~options_.opt_gsa.ppost
- [dum, ipost]=sort(-logpo2);
- [dum, ilik]=sort(-likelihood);
-end
-if ~options_.opt_gsa.ppost & options_.opt_gsa.lik_only
- if options_.opt_gsa.pprior
- anam='rmse_prior_post';
- else
- anam='rmse_mc_post';
- end
- stab_map_1(x, ipost(1:nfilt), ipost(nfilt+1:end), anam, 1,[],OutDir);
- stab_map_2(x(ipost(1:nfilt),:),alpha2,anam, OutDir);
- if options_.opt_gsa.pprior
- anam='rmse_prior_lik';
- else
- anam='rmse_mc_lik';
- end
- stab_map_1(x, ilik(1:nfilt), ilik(nfilt+1:end), anam, 1,[],OutDir);
- stab_map_2(x(ilik(1:nfilt),:),alpha2,anam, OutDir);
-else
- for i=1:size(vvarvecm,1),
- [dum, ixx(:,i)]=sort(rmse_MC(:,i));
- if options_.opt_gsa.ppost,
- %nfilt0(i)=length(find(rmse_MC(:,i)<rmse_pmean(i)));
- rmse_txt=rmse_pmean;
- else
- if options_.opt_gsa.pprior | ~exist('rmse_pmean'),
- if exist('rmse_mode'),
- rmse_txt=rmse_mode;
- else
- rmse_txt=NaN(1,size(rmse_MC,2));
- end
- else
- %nfilt0(i)=length(find(rmse_MC(:,i)<rmse_pmean(i)));
- rmse_txt=rmse_pmean;
- end
- end
- for j=1:npar+nshock,
- [H,P,KSSTAT] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j), alpha);
- [H1,P1,KSSTAT1] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j),alpha,1);
- [H2,P2,KSSTAT2] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j),alpha,-1);
- if H1 & H2==0,
- SS(j,i)=1;
- elseif H1==0,
- SS(j,i)=-1;
- else
- SS(j,i)=0;
- end
- PP(j,i)=P;
- end
-end
-ifig=0;
-for i=1:size(vvarvecm,1),
- if mod(i,9)==1,
- ifig=ifig+1;
- figure('name',['Prior ',int2str(ifig)])
- end
- subplot(3,3,i-9*(ifig-1))
- h=cumplot(lnprior(ixx(1:nfilt0(i),i)));
- set(h,'color','red')
- hold on, cumplot(lnprior)
- h=cumplot(lnprior(ixx(nfilt0(i)+1:end,i)));
- set(h,'color','green')
- title(vvarvecm(i,:))
- if mod(i,9)==0 | i==size(vvarvecm,1)
- if options_.opt_gsa.ppost
- saveas(gcf,[OutDir,'\',fname_,'_rmse_post_lnprior',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '\' fname_ '_rmse_post_lnprior',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '\' fname_ '_rmse_post_lnprior',int2str(ifig)]);
- else
- if options_.opt_gsa.pprior
- saveas(gcf,[OutDir,'\',fname_,'_rmse_prior_lnprior',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '\' fname_ '_rmse_prior_lnprior',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '\' fname_ '_rmse_prior_lnprior',int2str(ifig)]);
- else
- saveas(gcf,[OutDir,'\',fname_,'_rmse_mc_lnprior',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '\' fname_ '_rmse_mc_lnprior',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '\' fname_ '_rmse_mc_lnprior',int2str(ifig)]);
- end
- end
- close(gcf)
- end
-end
-ifig=0;
-for i=1:size(vvarvecm,1),
- if mod(i,9)==1,
- ifig=ifig+1;
- figure('name',['Likelihood ',int2str(ifig)])
- end
- subplot(3,3,i-9*(ifig-1))
- h=cumplot(likelihood(ixx(1:nfilt0(i),i)));
- set(h,'color','red')
- hold on, h=cumplot(likelihood);
- h=cumplot(likelihood(ixx(nfilt0(i)+1:end,i)));
- set(h,'color','green')
- title(vvarvecm(i,:))
- if options_.opt_gsa.ppost==0,
- set(gca,'xlim',[min( likelihood(ixx(1:nfilt0(i),i)) ) max( likelihood(ixx(1:nfilt0(i),i)) )])
- end
- if mod(i,9)==0 | i==size(vvarvecm,1)
- if options_.opt_gsa.ppost
- saveas(gcf,[OutDir,'\',fname_,'_rmse_post_lnlik',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '\' fname_ '_rmse_post_lnlik',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '\' fname_ '_rmse_post_lnlik',int2str(ifig)]);
- else
- if options_.opt_gsa.pprior
- saveas(gcf,[OutDir,'\',fname_,'_rmse_prior_lnlik',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '\' fname_ '_rmse_prior_lnlik',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '\' fname_ '_rmse_prior_lnlik',int2str(ifig)]);
- else
- saveas(gcf,[OutDir,'\',fname_,'_rmse_mc_lnlik',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '\' fname_ '_rmse_mc_lnlik',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '\' fname_ '_rmse_mc_lnlik',int2str(ifig)]);
- end
- end
- close(gcf)
- end
-end
-ifig=0;
-for i=1:size(vvarvecm,1),
- if mod(i,9)==1,
- ifig=ifig+1;
- figure('name',['Posterior ',int2str(ifig)])
- end
- subplot(3,3,i-9*(ifig-1))
- h=cumplot(logpo2(ixx(1:nfilt0(i),i)));
- set(h,'color','red')
- hold on, h=cumplot(logpo2);
- h=cumplot(logpo2(ixx(nfilt0(i)+1:end,i)));
- set(h,'color','green')
- title(vvarvecm(i,:))
- if options_.opt_gsa.ppost==0,
- set(gca,'xlim',[min( logpo2(ixx(1:nfilt0(i),i)) ) max( logpo2(ixx(1:nfilt0(i),i)) )])
- end
- if mod(i,9)==0 | i==size(vvarvecm,1)
- if options_.opt_gsa.ppost
- saveas(gcf,[OutDir,'\',fname_,'_rmse_post_lnpost',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '\' fname_ '_rmse_post_lnpost',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '\' fname_ '_rmse_post_lnpost',int2str(ifig)]);
- else
- if options_.opt_gsa.pprior
- saveas(gcf,[OutDir,'\',fname_,'_rmse_prior_lnpost',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '\' fname_ '_rmse_prior_lnpost',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '\' fname_ '_rmse_prior_lnpost',int2str(ifig)]);
- else
- saveas(gcf,[OutDir,'\',fname_,'_rmse_mc_lnpost',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '\' fname_ '_rmse_mc_lnpost',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '\' fname_ '_rmse_mc_lnpost',int2str(ifig)]);
- end
- end
- close(gcf)
- end
-end
-
-param_names='';
-for j=1:npar+nshock,
- param_names=str2mat(param_names, bayestopt_.name{j});
-end
-param_names=param_names(2:end,:);
-
-disp(' ')
-disp('RMSE over the MC sample:')
-disp(' min yr RMSE max yr RMSE')
-for j=1:size(vvarvecm,1),
- disp([vvarvecm(j,:), sprintf('%15.5g',[(min(rmse_MC(:,j))) [(max(rmse_MC(:,j)))]])])
-end
-invar = find( std(rmse_MC)./mean(rmse_MC)<=0.0001 );
-if ~isempty(invar)
- disp(' ')
- disp(' ')
- disp('RMSE is not varying significantly over the MC sample for the following variables:')
- disp(vvarvecm(invar,:))
- disp('These variables are excluded from SA')
- disp('[Unless you treat these series as exogenous, there is something wrong in your estimation !]')
-end
-ivar = find( std(rmse_MC)./mean(rmse_MC)>0.0001 );
-vvarvecm=vvarvecm(ivar,:);
-rmse_MC=rmse_MC(:,ivar);
-
-disp(' ')
-% if options_.opt_gsa.ppost==0 & options_.opt_gsa.pprior,
- disp(['Sample filtered the ',num2str(pfilt*100),'% best RMSE''s for each observed series ...' ])
-% else
-% disp(['Sample filtered the best RMSE''s smaller than RMSE at the posterior mean ...' ])
-% end
-% figure, boxplot(rmse_MC)
-% set(gca,'xticklabel',vvarvecm)
-% saveas(gcf,[fname_,'_SA_RMSE'])
-
-disp(' ')
-disp(' ')
-disp('RMSE ranges after filtering:')
-if options_.opt_gsa.ppost==0 & options_.opt_gsa.pprior,
- disp([' best ',num2str(pfilt*100),'% filtered remaining 90%'])
- disp([' min max min max posterior mode'])
-else
- disp([' best filtered remaining '])
- disp([' min max min max posterior mean'])
-end
-for j=1:size(vvarvecm,1),
- disp([vvarvecm(j,:), sprintf('%15.5g',[min(rmse_MC(ixx(1:nfilt0(j),j),j)) ...
- max(rmse_MC(ixx(1:nfilt0(j),j),j)) ...
- min(rmse_MC(ixx(nfilt0(j)+1:end,j),j)) ...
- max(rmse_MC(ixx(nfilt0(j)+1:end,j),j)) ...
- rmse_txt(j)])])
- % disp([vvarvecm(j,:), sprintf('%15.5g',[min(logpo2(ixx(1:nfilt,j))) ...
- % max(logpo2(ixx(1:nfilt,j))) ...
- % min(logpo2(ixx(nfilt+1:end,j))) ...
- % max(logpo2(ixx(nfilt+1:end,j)))])])
-end
-
-SP=zeros(npar+nshock,size(vvarvecm,1));
-for j=1:size(vvarvecm,1),
- ns=find(PP(:,j)<alpha);
- SP(ns,j)=ones(size(ns));
- SS(:,j)=SS(:,j).*SP(:,j);
-end
-
-for j=1:npar+nshock, %estim_params_.np,
- nsp(j)=length(find(SP(j,:)));
-end
-snam0=param_names(find(nsp==0),:);
-snam1=param_names(find(nsp==1),:);
-snam2=param_names(find(nsp>1),:);
-snam=param_names(find(nsp>0),:);
-% snam0=bayestopt_.name(find(nsp==0));
-% snam1=bayestopt_.name(find(nsp==1));
-% snam2=bayestopt_.name(find(nsp>1));
-% snam=bayestopt_.name(find(nsp>0));
-nsnam=(find(nsp>1));
-
-disp(' ')
-disp(' ')
-disp('These parameters do not affect significantly the fit of ANY observed series:')
-disp(snam0)
-disp(' ')
-disp('These parameters affect ONE single observed series:')
-disp(snam1)
-disp(' ')
-disp('These parameters affect MORE THAN ONE observed series: trade off exists!')
-disp(snam2)
-
-
-%pnam=bayestopt_.name(end-estim_params_.np+1:end);
-pnam=bayestopt_.name;
-
-% plot trade-offs
-a00=jet(size(vvarvecm,1));
-for ix=1:ceil(length(nsnam)/5),
- figure,
- for j=1+5*(ix-1):min(size(snam2,1),5*ix),
- subplot(2,3,j-5*(ix-1))
- %h0=cumplot(x(:,nsnam(j)+nshock));
- h0=cumplot(x(:,nsnam(j)));
- set(h0,'color',[0 0 0])
- hold on,
- np=find(SP(nsnam(j),:));
- %a0=jet(nsp(nsnam(j)));
- a0=a00(np,:);
- for i=1:nsp(nsnam(j)), %size(vvarvecm,1),
- %h0=cumplot(x(ixx(1:nfilt,np(i)),nsnam(j)+nshock));
- h0=cumplot(x(ixx(1:nfilt0(np(i)),np(i)),nsnam(j)));
- set(h0,'color',a0(i,:))
- end
- ydum=get(gca,'ylim');
- %xdum=xparam1(nshock+nsnam(j));
- if exist('xparam1')
- xdum=xparam1(nsnam(j));
- h1=plot([xdum xdum],ydum);
- set(h1,'color',[0.85 0.85 0.85],'linewidth',2)
- end
- xlabel('')
- title([pnam{nsnam(j)}],'interpreter','none')
- end
- %subplot(3,2,6)
- h0=legend(str2mat('base',vvarvecm(np,:)),0);
- set(h0,'fontsize',6,'position',[0.7 0.1 0.2 0.3],'interpreter','none')
- %h0=legend({'base',vnam{np}}',0);
- %set(findobj(get(h0,'children'),'type','text'),'interpreter','none')
- if options_.opt_gsa.ppost
- saveas(gcf,[OutDir,'\',fname_,'_rmse_post_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '\' fname_ '_rmse_post_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '\' fname_ '_rmse_post_' int2str(ix)]);
- else
- if options_.opt_gsa.pprior
- saveas(gcf,[OutDir,'\',fname_,'_rmse_prior_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '\' fname_ '_rmse_prior_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '\' fname_ '_rmse_prior_' int2str(ix)]);
- else
- saveas(gcf,[OutDir,'\',fname_,'_rmse_mc_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '\' fname_ '_rmse_mc_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '\' fname_ '_rmse_mc_' int2str(ix)]);
- end
- end
-end
-close all
-
-for j=1:size(SP,2),
- nsx(j)=length(find(SP(:,j)));
-end
-
-number_of_grid_points = 2^9; % 2^9 = 512 !... Must be a power of two.
-bandwidth = 0; % Rule of thumb optimal bandwidth parameter.
-kernel_function = 'gaussian'; % Gaussian kernel for Fast Fourrier Transform approximaton.
-%kernel_function = 'uniform'; % Gaussian kernel for Fast Fourrier Transform approximaton.
-
-for ix=1:ceil(length(nsnam)/5),
- figure,
- for j=1+5*(ix-1):min(size(snam2,1),5*ix),
- subplot(2,3,j-5*(ix-1))
- optimal_bandwidth = mh_optimal_bandwidth(x(:,nsnam(j)),size(x,1),bandwidth,kernel_function);
- [x1,f1] = kernel_density_estimate(x(:,nsnam(j)),number_of_grid_points,...
- size(x,1),optimal_bandwidth,kernel_function);
- h0 = plot(x1, f1,'k');
- hold on,
- np=find(SP(nsnam(j),:));
- %a0=jet(nsp(nsnam(j)));
- a0=a00(np,:);
- for i=1:nsp(nsnam(j)), %size(vvarvecm,1),
- optimal_bandwidth = mh_optimal_bandwidth(x(ixx(1:nfilt0(np(i)),np(i)),nsnam(j)),nfilt,bandwidth,kernel_function);
- [x1,f1] = kernel_density_estimate(x(ixx(1:nfilt0(np(i)),np(i)),nsnam(j)),number_of_grid_points,...
- nfilt,optimal_bandwidth,kernel_function);
- h0 = plot(x1, f1);
- set(h0,'color',a0(i,:))
- end
- ydum=get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)]);
- if exist('xparam1')
- %xdum=xparam1(nshock+nsnam(j));
- xdum=xparam1(nsnam(j));
- h1=plot([xdum xdum],[0 ydum(2)]);
- set(h1,'color',[0.85 0.85 0.85],'linewidth',2)
- end
- xlabel('')
- title([pnam{nsnam(j)}],'interpreter','none')
- end
- h0=legend(str2mat('base',vvarvecm(np,:)),0);
- set(h0,'fontsize',6,'position',[0.7 0.1 0.2 0.3],'interpreter','none')
- %h0=legend({'base',vnam{np}}',0);
- %set(findobj(get(h0,'children'),'type','text'),'interpreter','none')
- if options_.opt_gsa.ppost
- saveas(gcf,[OutDir,'\',fname_,'_rmse_post_dens_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '\' fname_ '_rmse_post_dens_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '\' fname_ '_rmse_post_dens_' int2str(ix)]);
- else
- if options_.opt_gsa.pprior
- saveas(gcf,[OutDir,'\',fname_,'_rmse_prior_dens_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '\' fname_ '_rmse_prior_dens_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '\' fname_ '_rmse_prior_dens_' int2str(ix)]);
- else
- saveas(gcf,[OutDir,'\',fname_,'_rmse_mc_dens_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '\' fname_ '_rmse_mc_dens_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '\' fname_ '_rmse_mc_dens_' int2str(ix)]);
- end
- end
-end
-close all
-
-% for j=1:size(SP,2),
-% nfig=0;
-% np=find(SP(:,j));
-% for i=1:nsx(j), %size(vvarvecm,1),
-% if mod(i,12)==1,
-% nfig=nfig+1;
-% %figure('name',['Sensitivity of fit of ',vnam{j}]),
-% figure('name',['Sensitivity of fit of ',deblank(vvarvecm(j,:)),' ',num2str(nfig)]),
-% end
-%
-% subplot(3,4,i-12*(nfig-1))
-% optimal_bandwidth = mh_optimal_bandwidth(x(ixx(1:nfilt,j),np(i)),nfilt,bandwidth,kernel_function);
-% [x1,f1] = kernel_density_estimate(x(ixx(1:nfilt,j),np(i)),number_of_grid_points,...
-% optimal_bandwidth,kernel_function);
-% plot(x1, f1,':k','linewidth',2)
-% optimal_bandwidth = mh_optimal_bandwidth(x(ixx(nfilt+1:end,j),np(i)),nruns-nfilt,bandwidth,kernel_function);
-% [x1,f1] = kernel_density_estimate(x(ixx(nfilt+1:end,j),np(i)),number_of_grid_points,...
-% optimal_bandwidth,kernel_function);
-% hold on, plot(x1, f1,'k','linewidth',2)
-% ydum=get(gca,'ylim');
-% %xdum=xparam1(nshock+np(i));
-% xdum=xparam1(np(i));
-% h1=plot([xdum xdum],ydum);
-% set(h1,'color',[0.85 0.85 0.85],'linewidth',2)
-% %xdum1=mean(x(ixx(1:nfilt,j),np(i)+nshock));
-% xdum1=mean(x(ixx(1:nfilt,j),np(i)));
-% h2=plot([xdum1 xdum1],ydum);
-% set(h2,'color',[0 1 0],'linewidth',2)
-% % h0=cumplot(x(nfilt+1:end,np(i)+nshock));
-% % set(h0,'color',[1 1 1])
-% % hold on,
-% % h0=cumplot(x(ixx(1:nfilt,j),np(i)+nshock));
-% % set(h0,'linestyle',':','color',[1 1 1])
-% %title([pnam{np(i)}])
-% title([pnam{np(i)},'. K-S prob ', num2str(PP(np(i),j))],'interpreter','none')
-% xlabel('')
-% if mod(i,12)==0 | i==nsx(j),
-% saveas(gcf,[fname_,'_rmse_',deblank(vvarvecm(j,:)),'_',int2str(nfig)])
-% close(gcf)
-% end
-% end
-% end
-
-
-disp(' ')
-disp(' ')
-disp('Sensitivity table (significance and direction):')
-vav=char(zeros(1, size(param_names,2)+3 ));
-ibl = 12-size(vvarvecm,2);
-for j=1:size(vvarvecm,1),
- vav = [vav, char(zeros(1,ibl)),vvarvecm(j,:)];
-end
-disp(vav)
-for j=1:npar+nshock, %estim_params_.np,
- %disp([param_names(j,:), sprintf('%8.5g',SP(j,:))])
- disp([param_names(j,:),' ', sprintf('%12.3g',PP(j,:))])
- disp([char(zeros(1, size(param_names,2)+3 )),sprintf(' (%6g)',SS(j,:))])
-end
-
-
-disp(' ')
-disp(' ')
-disp('Starting bivariate analysis:')
-
-for i=1:size(vvarvecm,1)
- if options_.opt_gsa.ppost
- fnam = ['rmse_post_',deblank(vvarvecm(i,:))];
- else
- if options_.opt_gsa.pprior
- fnam = ['rmse_prior_',deblank(vvarvecm(i,:))];
- else
- fnam = ['rmse_mc_',deblank(vvarvecm(i,:))];
- end
- end
- stab_map_2(x(ixx(1:nfilt0(i),i),:),alpha2,fnam, OutDir);
-
- % [pc,latent,explained] = pcacov(c0);
- % %figure, bar([explained cumsum(explained)])
- % ifig=0;
- % j2=0;
- % for j=1:npar+nshock,
- % i2=find(abs(pc(:,j))>alphaPC);
- % if ~isempty(i2),
- % j2=j2+1;
- % if mod(j2,12)==1,
- % ifig=ifig+1;
- % figure('name',['PCA of the filtered sample ',deblank(vvarvecm(i,:)),' ',num2str(ifig)]),
- % end
- % subplot(3,4,j2-(ifig-1)*12)
- % bar(pc(i2,j)),
- % set(gca,'xticklabel',bayestopt_.name(i2)),
- % set(gca,'xtick',[1:length(i2)])
- % title(['PC ',num2str(j),'. Explained ',num2str(explained(j)),'%'])
- % end
- % if (mod(j2,12)==0 | j==(npar+nshock)) & j2,
- % saveas(gcf,[fname_,'_SA_PCA_',deblank(vvarvecm(i,:)),'_',int2str(ifig)])
- % end
- % end
- % close all
-end
-
-end
\ No newline at end of file
diff --git a/GSA_distrib/4.0.3/gamm_cdf.m b/GSA_distrib/4.0.3/gamm_cdf.m
deleted file mode 100644
index a11d0962a4cd911ae962b4830afdb383572d532f..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/gamm_cdf.m
+++ /dev/null
@@ -1,27 +0,0 @@
-function cdf = gamm_cdf (x, a)
-% PURPOSE: returns the cdf at x of the gamma(a) distribution
-%---------------------------------------------------
-% USAGE: cdf = gamm_cdf(x,a)
-% where: x = a vector
-% a = a scalar gamma(a)
-%---------------------------------------------------
-% RETURNS:
-% a vector of cdf at each element of x of the gamma(a) distribution
-% --------------------------------------------------
-% SEE ALSO: gamm_d, gamm_pdf, gamm_rnd, gamm_inv
-%---------------------------------------------------
-
-% Anders Holtsberg, 18-11-93
-% Copyright (c) Anders Holtsberg
-
-if nargin ~= 2
-error('Wrong # of arguments to gamm_cdf');
-end;
-
-if any(any(a<=0))
- error('gamm_cdf: parameter a is wrong')
-end
-
-cdf = gammainc(x,a);
-I0 = find(x<0);
-cdf(I0) = zeros(size(I0));
diff --git a/GSA_distrib/4.0.3/gamm_inv.m b/GSA_distrib/4.0.3/gamm_inv.m
deleted file mode 100644
index 3bede95ba39a4309c86bc5e2c5e347c840dbb23f..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/gamm_inv.m
+++ /dev/null
@@ -1,50 +0,0 @@
-function x = gamm_inv(p,a,b)
-% PURPOSE: returns the inverse of the cdf at p of the gamma(a,b) distribution
-%---------------------------------------------------
-% USAGE: x = gamm_inv(p,a)
-% where: p = a vector of probabilities
-% a = a scalar parameter gamma(a)
-% b = scaling factor for gamma
-%---------------------------------------------------
-% RETURNS:
-% a vector x of the quantile at each element of p of the gamma(a) distribution
-% --------------------------------------------------
-% SEE ALSO: gamm_d, gamm_pdf, gamm_rnd, gamm_cdf
-%---------------------------------------------------
-
-% Anders Holtsberg, 18-11-93
-% Copyright (c) Anders Holtsberg
-% documentation modified by LeSage to fit the format
-% of the econometrics toolbox
-
- if (nargin < 2 | isempty(b))
- b=1;
- end
-
- if (nargin > 3)
- error('Wrong # of arguments to gamm_inv');
- end
-
-
-if any(any(abs(2*p-1)>1))
- error('gamm_inv: a probability should be 0<=p<=1')
-end
-if any(any(a<=0))
- error('gamma_inv: parameter a is wrong')
-end
-
-x = max(a-1,0.1);
-dx = 1;
-while any(any(abs(dx)>256*eps*max(x,1)))
- dx = (gamm_cdf(x,a) - p) ./ gamm_pdf(x,a);
- x = x - dx;
- x = x + (dx - x) / 2 .* (x<0);
-end
-
-I0 = find(p==0);
-x(I0) = zeros(size(I0));
-I1 = find(p==1);
-x(I1) = zeros(size(I0)) + Inf;
-
-
-x=x.*b;
diff --git a/GSA_distrib/4.0.3/gamm_pdf.m b/GSA_distrib/4.0.3/gamm_pdf.m
deleted file mode 100644
index 86f4ffb1deb909af6fd7a5fddc4825f9c996ffc2..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/gamm_pdf.m
+++ /dev/null
@@ -1,27 +0,0 @@
-function f = gamm_pdf (x, a)
-% PURPOSE: returns the pdf at x of the gamma(a) distribution
-%---------------------------------------------------
-% USAGE: pdf = gamm_pdf(x,a)
-% where: x = a vector
-% a = a scalar for gamma(a)
-%---------------------------------------------------
-% RETURNS:
-% a vector of pdf at each element of x of the gamma(a) distribution
-% --------------------------------------------------
-% SEE ALSO: gamm_cdf, gamm_rnd, gamm_inv
-%---------------------------------------------------
-
-% Anders Holtsberg, 18-11-93
-% Copyright (c) Anders Holtsberg
-
-if nargin ~= 2
-error('Wrong # of arguments to gamm_cdf');
-end;
-
-if any(any(a<=0))
- error('gamm_pdf: parameter a is wrong')
-end
-
-f = x .^ (a-1) .* exp(-x) ./ gamma(a);
-I0 = find(x<0);
-f(I0) = zeros(size(I0));
diff --git a/GSA_distrib/4.0.3/ghx2transition.m b/GSA_distrib/4.0.3/ghx2transition.m
deleted file mode 100644
index 2f10a5f3b7ba1b001da2b5faf6cb93069afffe42..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/ghx2transition.m
+++ /dev/null
@@ -1,41 +0,0 @@
-function [A,B] = ghx2transition(mm,iv,ic,aux)
-% [A,B] = ghx2transition(mm,iv,ic,aux)
-%
-% Adapted by M. Ratto from kalman_transition_matrix.m
-% (kalman_transition_matrix.m is part of DYNARE, copyright M. Juillard)
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global M_
-
- [nr1, nc1] = size(mm);
- ghx = mm(:, [1:(nc1-M_.exo_nbr)]);
- ghu = mm(:, [(nc1-M_.exo_nbr+1):end] );
- n_iv = length(iv);
- n_ir1 = size(aux,1);
- nr = n_iv + n_ir1;
-
- A = zeros(nr,nr);
- B = zeros(nr,M_.exo_nbr);
-
- i_n_iv = 1:n_iv;
- A(i_n_iv,ic) = ghx(iv,:);
- if n_ir1 > 0
- A(n_iv+1:end,:) = sparse(aux(:,1),aux(:,2),ones(n_ir1,1),n_ir1,nr);
- end
-
- B(i_n_iv,:) = ghu(iv,:);
diff --git a/GSA_distrib/4.0.3/log_trans_.m b/GSA_distrib/4.0.3/log_trans_.m
deleted file mode 100644
index b0ff26ddfa8afd10f51f6e8eab91dfa3ca88fcc2..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/log_trans_.m
+++ /dev/null
@@ -1,54 +0,0 @@
-function [yy, xdir, isig, lam]=log_trans_(y0,xdir0)
-
-if nargin==1,
- xdir0='';
-end
-f=inline('skewness(log(y+lam))','lam','y');
-isig=1;
-if ~(max(y0)<0 | min(y0)>0)
- if skewness(y0)<0,
- isig=-1;
- y0=-y0;
- end
- n=hist(y0,10);
- if n(1)>20*n(end),
- try lam=fzero(f,[-min(y0)+10*eps -min(y0)+abs(median(y0))],[],y0);
- catch
- yl(1)=f(-min(y0)+10*eps,y0);
- yl(2)=f(-min(y0)+abs(median(y0)),y0);
- if abs(yl(1))<abs(yl(2))
- lam=-min(y0)+eps;
- else
- lam = -min(y0)+abs(median(y0)); %abs(100*(1+min(y0)));
- end
- end
- yy = log(y0+lam);
- xdir=[xdir0,'_logskew'];
- else
- isig=0;
- lam=0;
- yy = log(y0.^2);
- xdir=[xdir0,'_logsquared'];
- end
-else
- if max(y0)<0
- isig=-1;
- y0=-y0;
- %yy=log(-y0);
- xdir=[xdir0,'_minuslog'];
- elseif min(y0)>0
- %yy=log(y0);
- xdir=[xdir0,'_log'];
- end
- try lam=fzero(f,[-min(y0)+10*eps -min(y0)+median(y0)],[],y0);
- catch
- yl(1)=f(-min(y0)+10*eps,y0);
- yl(2)=f(-min(y0)+abs(median(y0)),y0);
- if abs(yl(1))<abs(yl(2))
- lam=-min(y0)+eps;
- else
- lam = -min(y0)+abs(median(y0)); %abs(100*(1+min(y0)));
- end
- end
- yy = log(y0+lam);
-end
diff --git a/GSA_distrib/4.0.3/lptauSEQ.m b/GSA_distrib/4.0.3/lptauSEQ.m
deleted file mode 100644
index 3f34e9ef4a50c90d6d3d6674f84be7544c201f38..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/lptauSEQ.m
+++ /dev/null
@@ -1,25 +0,0 @@
-function [lpmat] = lptauSEQ(Nsam,Nvar)
-
-% [lpmat] = lptauSEQ(Nsam,Nvar)
-%
-% function call LPTAU and generates a sample of dimension Nsam for a
-% number of parameters Nvar
-%
-% Copyright (C) 2005 Marco Ratto
-% THIS PROGRAM WAS WRITTEN FOR MATLAB BY
-% Marco Ratto,
-% Unit of Econometrics and Statistics AF
-% (http://www.jrc.cec.eu.int/uasa/),
-% IPSC, Joint Research Centre
-% The European Commission,
-% TP 361, 21020 ISPRA(VA), ITALY
-% marco.ratto@jrc.it
-%
-
-
-clear lptau
-lpmat = zeros(Nsam, Nvar);
-for j=1:Nsam,
- lpmat(j,:)=LPTAU(j,Nvar);
-end
-return
diff --git a/GSA_distrib/4.0.3/map_ident_.m b/GSA_distrib/4.0.3/map_ident_.m
deleted file mode 100644
index 2a919e38ea9a6c13292c2b576252b18c081233f4..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/map_ident_.m
+++ /dev/null
@@ -1,1211 +0,0 @@
-function map_ident_(OutputDirectoryName)
-global bayestopt_ M_ options_ estim_params_ oo_
-
-opt_gsa = options_.opt_gsa;
-fname_ = M_.fname;
-nliv = opt_gsa.morris_nliv;
-ntra = opt_gsa.morris_ntra;
-itrans = opt_gsa.trans_ident;
-
-np = estim_params_.np;
-if opt_gsa.load_ident,
- gsa_flag=0;
-else
- gsa_flag=-2;
-end
-
-pnames = M_.param_names(estim_params_.param_vals(:,1),:);
-
-filetoload=[OutputDirectoryName '\' fname_ '_prior'];
-load(filetoload,'lpmat','lpmat0','istable','T','nspred','nboth','nfwrd')
-Nsam = size(lpmat,1);
-nshock = size(lpmat0,2);
-npT = np+nshock;
-
-fname_ = M_.fname;
-
-% th moments
-[vdec, cc, ac] = mc_moments(T, lpmat0(istable,:), oo_.dr);
-if opt_gsa.morris==0,
- ifig=0;
- for j=1:M_.exo_nbr,
- if mod(j,6)==1
- figure('name',['Variance decomposition shocks']);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(2,3,iplo)
- myboxplot(squeeze(vdec(:,j,:))',[],'.',[],10)
-% boxplot(squeeze(vdec(:,j,:))','whis',10,'symbol','.r')
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:size(options_.varobs,1)])
- set(gca,'xlim',[0.5 size(options_.varobs,1)+0.5])
- set(gca,'ylim',[-2 102])
- for ip=1:size(options_.varobs,1),
- text(ip,-4,deblank(options_.varobs(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- ylabel(' ')
- title(M_.exo_names(j,:),'interpreter','none')
- if mod(j,6)==0 | j==M_.exo_nbr,
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_vdec_exo_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_vdec_exo_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_vdec_exo_',int2str(ifig)]);
- end
- end
-end
-[vdec, j0, ir_vdec, ic_vdec] = teff(vdec,Nsam,istable);
-[cc, j0, ir_cc, ic_cc] = teff(cc,Nsam,istable);
-[ac, j0, ir_ac, ic_ac] = teff(ac,Nsam,istable);
-
-[Aa,Bb] = ghx2transition(squeeze(T(:,:,1)), ...
- bayestopt_.restrict_var_list, ...
- bayestopt_.restrict_columns, ...
- bayestopt_.restrict_aux);
-A = zeros(size(Aa,1),size(Aa,2)+size(Bb,2),length(istable));
-A(:,:,1)=[Aa, Bb];
-for j=2:length(istable),
- [Aa,Bb] = ghx2transition(squeeze(T(:,:,j)), ...
- bayestopt_.restrict_var_list, ...
- bayestopt_.restrict_columns, ...
- bayestopt_.restrict_aux);
- A(:,:,j)=[Aa, Bb];
-end
-clear T;
-
-[nr,nc,nn]=size(A);
-io=bayestopt_.mf1;
-T1=A(io,1:nr,:);
-ino=find(~ismember([1:nr],io));
-T2=A(ino,1:nr,:);
-R=A(:,nr+1:nc,:);
-[tadj, iff] = speed(A(1:nr,1:nr,:),R,io,0.5);
-[tadj, j0, ir_tadj, ic_tadj] = teff(tadj,Nsam,istable);
-[iff, j0, ir_if, ic_if] = teff(iff,Nsam,istable);
-
-
-[yt, j0]=teff(A,Nsam,istable);
-[yt1, j01]=teff(T1,Nsam,istable);
-[yt2, j02]=teff(T2,Nsam,istable);
-[ytr, j0r]=teff(R,Nsam,istable);
-
-yt=[yt1 yt2 ytr];
-
-% for j=1:nr,
-% for i=1:nc,
-% y0=squeeze(A(j,i,:));
-% if max(y0)-min(y0)>1.e-10,
-% j0=j0+1;
-% y1=ones(size(lpmat,1),1)*NaN;
-% y1(istable,1)=y0;
-% yt(:,j0)=y1;
-% end
-% end
-% end
-% yt = yt(:,j0);
-
-if opt_gsa.morris==1,
- %OutputDir = CheckPath('GSA\SCREEN');
- SAMorris = [];
- for i=1:size(vdec,2),
- [SAmeas, SAMorris(:,:,i)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], vdec(:,i),nliv);
- end
- SAvdec = squeeze(SAMorris(:,1,:))';
- save([OutputDirectoryName,'\',fname_,'_morris_IDE'],'SAvdec','vdec','ir_vdec','ic_vdec')
-
- figure,
-% boxplot(SAvdec,'whis',10,'symbol','r.')
- myboxplot(SAvdec,[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:npT,
- text(ip,-2,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('All variance decomposition')
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morris_vdec'])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morris_vdec']);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morris_vdec']);
-
- ifig = 0;
- for j=1:size(options_.varobs,1)
- if mod(j,6)==1
- figure('name',['EET variance decomposition observed variables']);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ir_vdec==j);
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAvdec(iv,:),'whis',3,'symbol','r.');
- myboxplot(SAvdec(iv,:),[],'.',[],3)
- else
- plot(SAvdec(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:npT,
- text(ip,-2,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- end
- title(options_.varobs(j,:),'interpreter','none')
- if mod(j,6)==0 | j==size(options_.varobs,1)
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morris_vdec_varobs_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morris_vdec_varobs_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morris_vdec_varobs_',int2str(ifig)]);
- end
- end
-
- ifig = 0;
- for j=1:M_.exo_nbr,
- if mod(j,6)==1
- figure('name',['EET variance decomposition shocks']);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ic_vdec==j);
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAvdec(iv,:),'whis',3,'symbol','r.');
- myboxplot(SAvdec(iv,:),[],'.',[],3)
- else
- plot(SAvdec(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:npT,
- text(ip,-2,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- end
- title(M_.exo_names(j,:),'interpreter','none')
- if mod(j,6)==0 | j==M_.exo_nbr,
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morris_vdec_exo_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morris_vdec_exo_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morris_vdec_exo_',int2str(ifig)]);
- end
- end
-
-
- SAMorris = [];
- for i=1:size(cc,2),
- [SAmeas, SAMorris(:,:,i)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], cc(:,i),nliv);
- end
- SAcc = squeeze(SAMorris(:,1,:))';
- save([OutputDirectoryName,'\',fname_,'_morris_IDE'],'SAcc','cc','ir_cc','ic_cc','-append')
-
- figure,
-% boxplot(SAcc,'whis',10,'symbol','r.')
- myboxplot(SAcc,[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('EET All cross-correlation matrix')
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morris_cc'])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morris_cc']);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morris_cc']);
-
- ifig = 0;
- for j=1:size(options_.varobs,1)
- if mod(j,6)==1
- figure('name',['EET cross-correlations']);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ir_cc==j);
- iv = [iv; find(ic_cc==j)];
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAcc(iv,:),'whis',3,'symbol','r.');
- myboxplot(SAcc(iv,:),[],'.',[],3)
- else
- plot(SAcc(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- end
- title(options_.varobs(j,:),'interpreter','none')
- if mod(j,6)==0 | j==size(options_.varobs,1)
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morris_cc_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morris_cc_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morris_cc_',int2str(ifig)]);
- end
- end
-
-
- SAMorris = [];
- for i=1:size(ac,2),
- [SAmeas, SAMorris(:,:,i)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], ac(:,i),nliv);
- end
- %end
- SAac = squeeze(SAMorris(:,1,:))';
- save([OutputDirectoryName,'\',fname_,'_morris_IDE'],'SAac','ac','ir_ac','ic_ac','-append')
-
- figure,
-% boxplot(SAac,'whis',10,'symbol','r.')
- myboxplot(SAac,[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('EET All auto-correlations')
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morris_ac'])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morris_ac']);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morris_ac']);
-
- ifig = 0;
- for j=1:size(options_.varobs,1)
- if mod(j,6)==1
- figure('name',['EET auto-correlations']);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ir_ac==j);
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAac(iv,:),'whis',3,'symbol','r.');
- myboxplot(SAac(iv,:),[],'.',[],3)
- else
- plot(SAac(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- end
- title(options_.varobs(j,:),'interpreter','none')
- if mod(j,6)==0 | j==size(options_.varobs,1)
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morris_ac_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morris_ac_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morris_ac_',int2str(ifig)]);
- end
- end
-
- js=0;
- %for j=1:size(tadj,1),
- SAMorris = [];
- for i=1:size(tadj,2),
- js=js+1;
- [SAmeas, SAMorris(:,:,js)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], tadj(:,i),nliv);
- end
- %end
- SAM = squeeze(SAMorris(nshock+1:end,1,:));
- for j=1:js,
- SAtadj(:,j)=SAM(:,j)./(max(SAM(:,j))+eps);
- end
- SAtadj = SAtadj';
- save([OutputDirectoryName,'\',fname_,'_morris_IDE'],'SAtadj','tadj','ir_tadj','ic_tadj','-append')
-
- js=0;
- SAMorris = [];
- for i=1:size(iff,2),
- js=js+1;
- [SAmeas, SAMorriss(:,:,js)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], iff(:,i),nliv);
- end
- SAM = squeeze(SAMorriss(nshock+1:end,1,:));
- for j=1:js,
- SAIF(:,j)=SAM(:,j)./(max(SAM(:,j))+eps);
- end
- SAIF = SAIF';
- save([OutputDirectoryName,'\',fname_,'_morris_IDE'],'SAIF','iff','ir_if','ic_if','-append')
-
- figure,
- %bar(SAtadj),
-% boxplot(SAtadj,'whis',10,'symbol','r.')
- myboxplot(SAtadj,[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 np+0.5])
- set(gca,'ylim',[0 1])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('All half-life')
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morris_tadj'])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morris_tadj']);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morris_tadj']);
-
- ifig = 0;
- for j=1:size(options_.varobs,1)
- if mod(j,6)==1
- figure('name',['EET speed of adjustment observed variables']);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ir_tadj==j);
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAtadj(iv,:),'whis',3,'symbol','r.');
- myboxplot(SAtadj(iv,:),[],'.',[],3)
- else
- plot(SAtadj(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 np+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- end
- title(options_.varobs(j,:),'interpreter','none')
- if mod(j,6)==0 | j==size(options_.varobs,1)
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morris_tadj_varobs_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morris_tadj_varobs_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morris_tadj_varobs_',int2str(ifig)]);
- end
- end
-
- ifig = 0;
- for j=1:M_.exo_nbr,
- if mod(j,6)==1
- figure('name',['EET speed of adjustment shocks']);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ic_tadj==j);
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAtadj(iv,:),'whis',3,'symbol','r.');
- myboxplot(SAtadj(iv,:),[],'.',[],3)
- else
- plot(SAtadj(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 np+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- end
- title(M_.exo_names(j,:),'interpreter','none')
- if mod(j,6)==0 | j==M_.exo_nbr,
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morris_tadj_exo_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morris_tadj_exo_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morris_tadj_exo_',int2str(ifig)]);
- end
- end
-
- figure,
- %bar(SAIF),
-% boxplot(SAIF,'whis',10,'symbol','r.')
- myboxplot(SAIF,[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 np+0.5])
- set(gca,'ylim',[0 1])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- ylabel('Elementary Effects')
- title('Steady state gains (impact factors)')
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morris_gain'])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morris_gain']);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morris_gain']);
- %figure, bar(SAIF'), title('All Gain Relationships')
- ifig = 0;
- for j=1:size(options_.varobs,1)
- if mod(j,6)==1
- figure('name',['EET steady state gain observed series']);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ir_if==j);
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAIF(iv,:),'whis',10,'symbol','r.');
- myboxplot(SAIF(iv,:),[],'.',[],10)
- else
- plot(SAIF(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 np+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- end
- title(options_.varobs(j,:),'interpreter','none')
- if mod(j,6)==0 | j==size(options_.varobs,1)
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morris_gain_varobs_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morris_gain_varobs_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morris_gain_varobs_',int2str(ifig)]);
- end
- end
-
- ifig = 0;
- for j=1:M_.exo_nbr,
- if mod(j,6)==1
- figure('name',['EET steady state gain shocks']);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ic_if==j);
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAIF(iv,:),'whis',3,'symbol','r.');
- myboxplot(SAIF(iv,:),[],'.',[],3)
- else
- plot(SAIF(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 np+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- end
- title(M_.exo_names(j,:),'interpreter','none')
- if mod(j,6)==0 | j==M_.exo_nbr,
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morris_gain_exo_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morris_gain_exo_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morris_gain_exo_',int2str(ifig)]);
- end
- end
-
-
- SAMorris = [];
- for j=1:j0,
- [SAmeas, SAMorris(:,:,j)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], yt(:,j),nliv);
- end
-
- SAM = squeeze(SAMorris(nshock+1:end,1,:));
- for j=1:j0
- SAnorm(:,j)=SAM(:,j)./max(SAM(:,j));
- irex(j)=length(find(SAnorm(:,j)>0.01));
- end
- [dum, irel]=sort(irex);
-
- SAMmu = squeeze(SAMorris(:,2,:));
- for j=1:j0
- SAmunorm(:,j)=SAMmu(:,j)./max(SAM(:,j)); % normalised w.r.t. mu*
- end
- SAMsig = squeeze(SAMorris(:,3,:));
- for j=1:j0
- SAsignorm(:,j)=SAMsig(:,j)./max(SAMsig(:,j));
- end
-
- figure, %bar(SAnorm(:,irel))
-% boxplot(SAnorm','whis',10,'symbol','r.')
- myboxplot(SAnorm',[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 np+0.5])
- set(gca,'ylim',[0 1])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- xlabel(' ')
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('Elementary effects parameters')
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morris_par'])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morris_par']);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morris_par']);
-
- figure, %bar(SAmunorm(:,irel))
-% boxplot(SAmunorm','whis',10,'symbol','r.')
- myboxplot(SAmunorm',[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 np+0.5])
- set(gca,'ylim',[-1 1])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- xlabel(' ')
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('\mu parameters')
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morrismu_par'])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morrismu_par']);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morrismu_par']);
- figure, %bar(SAsignorm(:,irel))
-% boxplot(SAsignorm','whis',10,'symbol','r.')
- myboxplot(SAsignorm',[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 np+0.5])
- set(gca,'ylim',[0 1])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- xlabel(' ')
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('\sigma parameters')
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_morrissig_par'])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morrissig_par']);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morrissig_par']);
-
- % figure, bar(SAnorm(:,irel)')
- % set(gca,'xtick',[1:j0])
- % set(gca,'xlim',[0.5 j0+0.5])
- % title('Elementary effects relationships')
- % saveas(gcf,[OutputDirectoryName,'\',fname_,'_morris_redform'])
- % eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_morris_redform']);
- % eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_morris_redform']);
-
-elseif opt_gsa.morris==2,
- np=estim_params_.np;
- na=(4*np+1)*opt_gsa.Nsam;
- for j=1:j0,
- [idex(j,:), yd(j,:)] = spop_ide(lpmat, yt(:,j), opt_gsa.Nsam, 5-1);
- end
- iok=find(~isnan(yt(1:opt_gsa.Nsam,1)));
- yr=NaN*ones(size(lpmat,1),j0);
- for j=1:j0,
- ys(j,:)=yd(j,:)./max(yd(j,:));
- [dum, is]=sort(yt(iok,j));
- yr(iok(is),j)=[1:length(iok)]'./length(iok);
- yr(istable(length(iok)+1:end),j) = interp1(yt(iok,j),yr(iok,j),yt(istable(length(iok)+1:end),j),'','extrap');
- ineg=find(yr(:,j)<0);
- if any(ineg),
- [dum, is]=sort(yr(ineg,j));
- yr(ineg(is),j)=-[length(ineg):-1:1]./length(iok);
-
- end
- [idex_r(j,:), yd_r(j,:)] = spop_ide(lpmat, yr(:,j), opt_gsa.Nsam, 5-1);
- ys_r(j,:)=yd_r(j,:)./max(yd_r(j,:));
-
- end,
- figure, bar((idex.*ys)./opt_gsa.Nsam), title('Relationships')
- figure, bar((idex.*ys)'./opt_gsa.Nsam), title('Parameters')
- figure, bar((idex_r.*ys_r)./opt_gsa.Nsam), title('Relationships rank')
- figure, bar((idex_r.*ys_r)'./opt_gsa.Nsam), title('Parameters rank')
- [v0,d0]=eig(corrcoef(yt(iok,:)));
- ee=diag(d0);
- ee=ee([end:-1:1])./j0;
- i0=length(find(ee>0.01));
- v0=v0(:,[end:-1:1]);
- for j=1:i0,
- [idex_pc(j,:), yd_pc(j,:)] = spop_ide(lpmat, yt*v0(:,j), opt_gsa.Nsam, 5-1);
- end
- for j=1:i0,
- ys_pc(j,:)=yd_pc(j,:)./max(yd_pc(j,:));
- end,
- figure, bar((idex_pc.*ys_pc)./opt_gsa.Nsam), title('Relationships PCA')
- figure, bar((idex_pc.*ys_pc)'./opt_gsa.Nsam), title('Parameters PCA')
-
- [vr,dr]=eig(corrcoef(yr(iok,:)));
- er=diag(dr);
- er=er([end:-1:1])./j0;
- ir0=length(find(er>0.01));
- vr=vr(:,[end:-1:1]);
- for j=1:ir0,
- [idex_pcr(j,:), yd_pcr(j,:)] = spop_ide(lpmat, yr*vr(:,j), opt_gsa.Nsam, 5-1);
- end
- for j=1:ir0,
- ys_pcr(j,:)=yd_pcr(j,:)./max(yd_pcr(j,:));
- end,
- figure, bar((idex_pcr.*ys_pcr)./opt_gsa.Nsam), title('Relationships rank PCA')
- figure, bar((idex_pcr.*ys_pcr)'./opt_gsa.Nsam), title('Parameters rank PCA')
-else,
-
- if itrans==0,
- fsuffix = '';
- elseif itrans==1,
- fsuffix = '_log';
- else
- fsuffix = '_rank';
- end
-
- imap=[1:npT];
-
- x0=[lpmat0(istable,:), lpmat(istable,:)];
- nrun=length(istable);
- nest=min(250,nrun);
- nfit=min(1000,nrun);
- try
- EET=load([OutputDirectoryName,'\SCREEN\',fname_,'_morris_IDE'],'SAvdec','vdec','ir_vdec','ic_vdec');
- catch
- EET=[];
- end
-
- SAvdec=zeros(size(vdec,2),npT);
-
- for j=1:size(vdec,2),
- if itrans==0,
- y0 = vdec(istable,j);
- elseif itrans==1,
- y0 = log_trans_(vdec(istable,j));
- else
- y0 = trank(vdec(istable,j));
- end
- if ~isempty(EET),
-% imap=find(EET.SAvdec(j,:));
-% [dum, isort]=sort(-EET.SAvdec(j,:));
- imap=find(EET.SAvdec(j,:) >= (0.1.*max(EET.SAvdec(j,:))) );
- end
- gsa_(j) = gsa_sdp(y0(1:nest), x0(1:nest,imap), ...
- 2, [],[],[],0,[OutputDirectoryName,'/map_vdec',fsuffix,int2str(j)], pnames);
- if nfit>nest,
- gsa_(j) = gsa_sdp(y0(1:nfit), x0(1:nfit,imap), ...
- -2, gsa_(j).nvr*nest^3/nfit^3,[],[],0,[OutputDirectoryName,'/map_vdec',fsuffix,int2str(j)], pnames);
- end
-
- SAvdec(j,imap)=gsa_(j).si;
- imap_vdec{j}=imap;
- end
- save([OutputDirectoryName,'\',fname_,'_main_eff'],'imap_vdec','SAvdec','vdec','ir_vdec','ic_vdec')
-
- figure,
-% boxplot(SAvdec,'whis',10,'symbol','r.')
- myboxplot(SAvdec,[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title(['Main effects variance decomposition ',fsuffix],'interpreter','none')
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_map_vdec',fsuffix])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_map_vdec',fsuffix]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_map_vdec',fsuffix]);
-
- ifig = 0;
- for j=1:size(options_.varobs,1)
- if mod(j,6)==1
- figure('name',['Main effects observed variance decomposition ',fsuffix]);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ir_vdec==j);
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAvdec(iv,:),'whis',10,'symbol','r.');
- myboxplot(SAvdec(iv,:),[],'.',[],10)
- else
- plot(SAvdec(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- end
- title(options_.varobs(j,:),'interpreter','none')
- if mod(j,6)==0 | j==size(options_.varobs,1)
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_map_vdec',fsuffix,'_varobs_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_map_vdec',fsuffix,'_varobs_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_map_vdec',fsuffix,'_varobs_',int2str(ifig)]);
- end
- end
-
- ifig = 0;
- for j=1:M_.exo_nbr,
- if mod(j,6)==1
- figure('name',['Main effects shocks variance decomposition ',fsuffix]);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ic_vdec==j);
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAvdec(iv,:),'whis',3,'symbol','r.');
- myboxplot(SAvdec(iv,:),[],'.',[],10)
- else
- plot(SAvdec(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',3,'xtick',[1:np])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- set(gca,'fontsize',10)
- end
- title(M_.exo_names(j,:),'interpreter','none','fontsize',10)
- if mod(j,6)==0 | j==M_.exo_nbr
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_map_vdec',fsuffix,'_exo_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_map_vdec',fsuffix,'_exo_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_map_vdec',fsuffix,'_exo_',int2str(ifig)]);
- end
- end
-
- try
- EET=load([OutputDirectoryName,'\SCREEN\',fname_,'_morris_IDE'],'SAcc','ir_cc','ic_cc');
- catch
- EET=[];
- end
- SAcc=zeros(size(cc,2),npT);
- for j=1:size(cc,2),
- if itrans==0,
- y0 = cc(istable,j);
- elseif itrans==1,
- y0 = log_trans_(cc(istable,j));
- else
- y0 = trank(cc(istable,j));
- end
- if ~isempty(EET),
-% imap=find(EET.SAvdec(j,:));
-% [dum, isort]=sort(-EET.SAvdec(j,:));
- imap=find(EET.SAcc(j,:) >= (0.1.*max(EET.SAcc(j,:))) );
- end
- gsa_(j) = gsa_sdp(y0(1:nest), x0(1:nest,imap), ...
- 2, [],[],[],0,[OutputDirectoryName,'/map_cc',fsuffix,int2str(j)], pnames);
- if nfit>nest,
- gsa_(j) = gsa_sdp(y0(1:nfit), x0(1:nfit,imap), ...
- -2, gsa_(j).nvr*nest^3/nfit^3,[],[],0,[OutputDirectoryName,'/map_cc',fsuffix,int2str(j)], pnames);
- end
- SAcc(j,imap)=gsa_(j).si;
- imap_cc{j}=imap;
-
- end
- save([OutputDirectoryName,'\',fname_,'_main_eff'],'imap_cc','SAcc','cc','ir_cc','ic_cc')
-
- figure,
-% boxplot(SAcc,'whis',10,'symbol','r.')
- myboxplot(SAcc,[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- ylabel(' ')
- title(['Main effects cross-covariances ',fsuffix],'interpreter','none')
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_map_cc',fsuffix])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_map_cc',fsuffix]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_map_cc',fsuffix]);
-
- ifig = 0;
- for j=1:size(options_.varobs,1)
- if mod(j,6)==1
- figure('name',['Main effects cross-covariances ',fsuffix]);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ir_cc==j);
- iv = [iv; find(ic_cc==j)];
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAcc(iv,:),'whis',10,'symbol','r.');
- myboxplot(SAcc(iv,:),[],'.',[],10)
- else
- plot(SAcc(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- set(gca,'fontsize',10)
- end
- title(options_.varobs(j,:),'interpreter','none','fontsize',10)
- if mod(j,6)==0 | j==size(options_.varobs,1)
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_map_cc',fsuffix,'_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_map_cc',fsuffix,'_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_map_cc',fsuffix,'_',int2str(ifig)]);
- end
- end
-
- try
- EET=load([OutputDirectoryName,'\SCREEN\',fname_,'_morris_IDE'],'SAac','ir_ac','ic_ac');
- catch
- EET=[];
- end
- SAac=zeros(size(ac,2),npT);
- for j=1:size(ac,2),
- if itrans==0,
- y0 = ac(istable,j);
- elseif itrans==1,
- y0 = log_trans_(ac(istable,j));
- else
- y0 = trank(ac(istable,j));
- end
- if ~isempty(EET),
- imap=find(EET.SAac(j,:) >= (0.1.*max(EET.SAac(j,:))) );
- end
-% gsa_(j) = gsa_sdp_dyn( y0, lpmat(istable,:), ...
-% gsa_flag, [],[],[],0,[OutputDirectoryName,'/map_ac',fsuffix,int2str(j)], pnames);
- gsa_(j) = gsa_sdp(y0(1:nest), x0(1:nest,imap), ...
- 2, [],[],[],0,[OutputDirectoryName,'/map_ac',fsuffix,int2str(j)], pnames);
- if nfit>nest,
- gsa_(j) = gsa_sdp(y0(1:nfit), x0(1:nfit,imap), ...
- -2, gsa_(j).nvr*nest^3/nfit^3,[],[],0,[OutputDirectoryName,'/map_ac',fsuffix,int2str(j)], pnames);
- end
- SAac(j,imap)=gsa_(j).si;
- imap_ac{j}=imap;
-
- end
- save([OutputDirectoryName,'\',fname_,'_main_eff'],'imap_ac','SAac','ac','ir_ac','ic_ac')
-
- figure,
-% boxplot(SAac,'whis',10,'symbol','r.')
- myboxplot(SAac,[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title(['Main effects 1 lag auto-covariances ',fsuffix],'interpreter','none')
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_map_ac',fsuffix])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_map_ac',fsuffix]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_map_ac',fsuffix]);
-
- ifig = 0;
- for j=1:size(options_.varobs,1)
- if mod(j,6)==1
- figure('name',['Main effects auto-covariances ',fsuffix]);
- ifig=ifig+1;
- iplo = 0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ir_ac==j);
- %iv = [iv; find(ic_ac==j)];
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAac(iv,:),'whis',10,'symbol','r.');
- myboxplot(SAac(iv,:),[],'.',[],10)
- else
- plot(SAac(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- set(gca,'fontsize',10)
- end
- title(options_.varobs(j,:),'interpreter','none','fontsize',10)
- if mod(j,6)==0 | j==size(options_.varobs,1)
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_map_ac',fsuffix,'_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_map_ac',fsuffix,'_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_map_ac',fsuffix,'_',int2str(ifig)]);
- end
- end
-
- x0=x0(:,nshock+1:end);
- imap=[1:np];
-
- try
- EET=load([OutputDirectoryName,'\SCREEN\',fname_,'_morris_IDE'],'SAtadj','ir_tadj','ic_tadj');
- ny=size(EET.SAtadj,1);
- catch
- EET=[];
- end
- SAtadj=zeros(size(tadj,2),np);
- for j=1:size(tadj,2),
- if itrans==0,
- y0 = tadj(istable,j);
- elseif itrans==1,
- y0 = log_trans_(tadj(istable,j));
- else
- y0 = trank(tadj(istable,j));
- end
- if ~isempty(EET),
- if size(tadj,2)~=ny,
- jj=find(EET.ir_tadj==ir_tadj(j));
- jj=jj(find(EET.ic_tadj(jj)==ic_tadj(j)));
- if ~isempty(jj),
- imap=find(EET.SAtadj(jj,:) >= (0.1.*max(EET.SAtadj(jj,:))) );
- else
- imap=[1:np];
- end
- else
- imap=find(EET.SAtadj(j,:) >= (0.1.*max(EET.SAtadj(j,:))) );
- end
- end
-% gsa_(j) = gsa_sdp_dyn( y0, lpmat(istable,:), ...
-% gsa_flag, [],[],[],0,[OutputDirectoryName,'/map_tadj',fsuffix,int2str(j)], pnames);
- gsa_(j) = gsa_sdp(y0(1:nest), x0(1:nest,imap), ...
- 2, [],[],[],0,[OutputDirectoryName,'/map_tadj',fsuffix,int2str(j)], pnames);
- if nfit>nest,
- gsa_(j) = gsa_sdp(y0(1:nfit), x0(1:nfit,imap), ...
- -2, gsa_(j).nvr*nest^3/nfit^3,[],[],0,[OutputDirectoryName,'/map_tadj',fsuffix,int2str(j)], pnames);
- end
- SAtadj(j,imap)=gsa_(j).si;
- imap_tadj{j}=imap;
-
- end
- save([OutputDirectoryName,'\',fname_,'_main_eff'],'imap_tadj','SAtadj','tadj','ir_tadj','ic_tadj')
-
- figure,
-% boxplot(SAtadj,'whis',10,'symbol','r.')
- myboxplot(SAtadj,[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 np+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title(['Main effects speed of adjustment ',fsuffix],'interpreter','none')
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_map_tadj',fsuffix])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_map_tadj',fsuffix]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_map_tadj',fsuffix]);
-
- ifig = 0;
- for j=1:size(options_.varobs,1)
- if mod(j,6)==1
- figure('name',['Main effects observed speed adjustment ',fsuffix]);
- ifig=ifig+1;
- iplo = 0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ir_tadj==j);
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAtadj(iv,:),'whis',3,'symbol','r.');
- myboxplot(SAtadj(iv,:),[],'.',[],10)
- else
- plot(SAtadj(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 np+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- end
- title(options_.varobs(j,:),'interpreter','none')
- if mod(j,6)==0 | j==size(options_.varobs,1)
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_map_tadj',fsuffix,'_varobs_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_map_tadj',fsuffix,'_varobs_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_map_tadj',fsuffix,'_varobs_',int2str(ifig)]);
- end
- end
-
- ifig = 0;
- for j=1:M_.exo_nbr,
- if mod(j,6)==1
- figure('name',['Main effects shocks speed of adjustment ',fsuffix]);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ic_tadj==j);
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAtadj(iv,:),'whis',3,'symbol','r.');
- myboxplot(SAtadj(iv,:),[],'.',[],10)
- else
- plot(SAtadj(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 np+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- end
- title(M_.exo_names(j,:),'interpreter','none')
- if mod(j,6)==0 | j==M_.exo_nbr,
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_map_tadj',fsuffix,'_exo_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_map_tadj',fsuffix,'_exo_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_map_tadj',fsuffix,'_exo_',int2str(ifig)]);
- end
- end
-
-
- try
- EET=load([OutputDirectoryName,'\SCREEN\',fname_,'_morris_IDE'],'SAIF','ir_if','ic_if');
- catch
- EET=[];
- end
- SAif=zeros(size(iff,2),np);
- for j=1:size(iff,2),
- if itrans==0,
- y0 = iff(istable,j);
- elseif itrans==1,
- y0 = log_trans_(iff(istable,j));
- else
- y0 = trank(iff(istable,j));
- end
- if ~isempty(EET),
- imap=find(EET.SAIF(j,:) >= (0.1.*max(EET.SAIF(j,:))) );
- end
-% gsa_(j) = gsa_sdp_dyn( y0, lpmat(istable,:), ...
-% gsa_flag, [],[],[],0,[OutputDirectoryName,'/map_if',fsuffix,int2str(j)], pnames);
- gsa_(j) = gsa_sdp(y0(1:nest), x0(1:nest,imap), ...
- 2, [],[],[],0,[OutputDirectoryName,'/map_if',fsuffix,int2str(j)], pnames);
- if nfit>nest,
- gsa_(j) = gsa_sdp(y0(1:nfit), x0(1:nfit,imap), ...
- -2, gsa_(j).nvr*nest^3/nfit^3,[],[],0,[OutputDirectoryName,'/map_if',fsuffix,int2str(j)], pnames);
- end
- SAif(j,imap)=gsa_(j).si;
- imap_if{j}=imap;
-
- end
- save([OutputDirectoryName,'\',fname_,'_main_eff'],'imap_if','SAif','iff','ir_if','ic_if')
-
- figure,
-% boxplot(SAif,'whis',10,'symbol','r.')
- myboxplot(SAif,[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 np+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title(['Main effects impact factors ',fsuffix],'interpreter','none')
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_map_if',fsuffix])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_map_if',fsuffix]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_map_if',fsuffix]);
-
- ifig = 0;
- for j=1:size(options_.varobs,1)
- if mod(j,6)==1
- figure('name',['Main effects observed impact factors ',fsuffix]);
- ifig=ifig+1;
- iplo = 0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ir_if==j);
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAif(iv,:),'whis',3,'symbol','r.');
- myboxplot(SAif(iv,:),[],'.',[],10)
- else
- plot(SAif(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 np+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- end
- title(options_.varobs(j,:),'interpreter','none')
- if mod(j,6)==0 | j==size(options_.varobs,1)
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_map_if',fsuffix,'_varobs_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_map_if',fsuffix,'_varobs_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_map_if',fsuffix,'_varobs_',int2str(ifig)]);
- end
- end
-
- ifig = 0;
- for j=1:M_.exo_nbr,
- if mod(j,6)==1
- figure('name',['Main effects shocks impact factors ',fsuffix]);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(3,2,iplo)
- iv = find(ic_if==j);
- if ~isempty(iv)
- if length(iv)>1
-% boxplot(SAif(iv,:),'whis',3,'symbol','r.');
- myboxplot(SAif(iv,:),[],'.',[],10)
- else
- plot(SAif(iv,:),'r.');
- end
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
- set(gca,'xlim',[0.5 np+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- end
- title(M_.exo_names(j,:),'interpreter','none')
- if mod(j,6)==0 | j==M_.exo_nbr
- saveas(gcf,[OutputDirectoryName,'\',fname_,'_map_if',fsuffix,'_exo_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '\' fname_ '_map_if',fsuffix,'_exo_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '\' fname_ '_map_if',fsuffix,'_exo_',int2str(ifig)]);
- end
- end
-
-end
diff --git a/GSA_distrib/4.0.3/mc_moments.m b/GSA_distrib/4.0.3/mc_moments.m
deleted file mode 100644
index 5431a14b5f1dcf05fb3671a3295c969aa0d9c4d3..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/mc_moments.m
+++ /dev/null
@@ -1,21 +0,0 @@
-function [vdec, cc, ac] = mc_moments(mm, ss, dr)
-global options_ M_
-
- [nr1, nc1, nsam] = size(mm);
- disp('Computing theoretical moments ...')
- h = waitbar(0,'Theoretical moments ...');
-
- for j=1:nsam,
- dr.ghx = mm(:, [1:(nc1-M_.exo_nbr)],j);
- dr.ghu = mm(:, [(nc1-M_.exo_nbr+1):end], j);
- if ~isempty(ss),
- set_shocks_param(ss(j,:));
- end
- [vdec(:,:,j), corr, autocorr, z, zz] = th_moments(dr,options_.varobs);
- cc(:,:,j)=tril(corr,-1);
- ac(:,:,j)=autocorr{1};
- waitbar(j/nsam,h)
- end
- close(h)
- disp(' ')
- disp('... done !')
diff --git a/GSA_distrib/4.0.3/myboxplot.m b/GSA_distrib/4.0.3/myboxplot.m
deleted file mode 100644
index 17f752ff84d830bfe672d577d53f3cc17ba5f1c2..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/myboxplot.m
+++ /dev/null
@@ -1,158 +0,0 @@
-
-function sout = myboxplot (data,notched,symbol,vertical,maxwhisker)
-
-% sout = myboxplot (data,notched,symbol,vertical,maxwhisker)
-
-% % % % endif
-if nargin < 5 | isempty(maxwhisker), maxwhisker = 1.5; end
-if nargin < 4 | isempty(vertical), vertical = 1; end
-if nargin < 3 | isempty(symbol), symbol = ['+','o']; end
-if nargin < 2 | isempty(notched), notched = 0; end
-
-if length(symbol)==1, symbol(2)=symbol(1); end
-
-if notched==1, notched=0.25; end
-a=1-notched;
-
-% ## figure out how many data sets we have
-if iscell(data),
- nc = length(data);
-else
-% if isvector(data), data = data(:); end
- nc = size(data,2);
-end
-
-% ## compute statistics
-% ## s will contain
-% ## 1,5 min and max
-% ## 2,3,4 1st, 2nd and 3rd quartile
-% ## 6,7 lower and upper confidence intervals for median
-s = zeros(7,nc);
-box = zeros(1,nc);
-whisker_x = ones(2,1)*[1:nc,1:nc];
-whisker_y = zeros(2,2*nc);
-outliers_x = [];
-outliers_y = [];
-outliers2_x = [];
-outliers2_y = [];
-
-for i=1:nc
- % ## Get the next data set from the array or cell array
- if iscell(data)
- col = data{i}(:);
- else
- col = data(:,i);
- end
-% ## Skip missing data
-% % % % % % % col(isnan(col) | isna (col)) = [];
- col(isnan(col)) = [];
-
- % ## Remember the data length
- nd = length(col);
- box(i) = nd;
- if (nd > 1)
-% ## min,max and quartiles
-% s(1:5,i) = statistics(col)(1:5);
-s(1,i)=min(col);
-s(5,i)=max(col);
-s(2,i)=myprctilecol(col,25);
-s(3,i)=myprctilecol(col,50);
-s(4,i)=myprctilecol(col,75);
-
-
-
-
-
-
-
-
-% ## confidence interval for the median
- est = 1.57*(s(4,i)-s(2,i))/sqrt(nd);
- s(6,i) = max([s(3,i)-est, s(2,i)]);
- s(7,i) = min([s(3,i)+est, s(4,i)]);
-% ## whiskers out to the last point within the desired inter-quartile range
- IQR = maxwhisker*(s(4,i)-s(2,i));
- whisker_y(:,i) = [min(col(col >= s(2,i)-IQR)); s(2,i)];
- whisker_y(:,nc+i) = [max(col(col <= s(4,i)+IQR)); s(4,i)];
-% ## outliers beyond 1 and 2 inter-quartile ranges
- outliers = col((col < s(2,i)-IQR & col >= s(2,i)-2*IQR) | (col > s(4,i)+IQR & col <= s(4,i)+2*IQR));
- outliers2 = col(col < s(2,i)-2*IQR | col > s(4,i)+2*IQR);
- outliers_x = [outliers_x; i*ones(size(outliers))];
- outliers_y = [outliers_y; outliers];
- outliers2_x = [outliers2_x; i*ones(size(outliers2))];
- outliers2_y = [outliers2_y; outliers2];
- elseif (nd == 1)
-% ## all statistics collapse to the value of the point
- s(:,i) = col;
-% ## single point data sets are plotted as outliers.
- outliers_x = [outliers_x; i];
- outliers_y = [outliers_y; col];
- else
-% ## no statistics if no points
- s(:,i) = NaN;
- end
-end
-% % % % if isempty(outliers2_y)
-% % % % outliers2_y=
-% ## Note which boxes don't have enough stats
-chop = find(box <= 1);
-
-% ## Draw a box around the quartiles, with width proportional to the number of
-% ## items in the box. Draw notches if desired.
-box = box*0.23/max(box);
-quartile_x = ones(11,1)*[1:nc] + [-a;-1;-1;1;1;a;1;1;-1;-1;-a]*box;
-quartile_y = s([3,7,4,4,7,3,6,2,2,6,3],:);
-
-% ## Draw a line through the median
-median_x = ones(2,1)*[1:nc] + [-a;+a]*box;
-% median_x=median(col);
-median_y = s([3,3],:);
-
-% ## Chop all boxes which don't have enough stats
-quartile_x(:,chop) = [];
-quartile_y(:,chop) = [];
-whisker_x(:,[chop,chop+nc]) = [];
-whisker_y(:,[chop,chop+nc]) = [];
-median_x(:,chop) = [];
-median_y(:,chop) = [];
-% % % %
-% ## Add caps to the remaining whiskers
-cap_x = whisker_x;
-cap_x(1,:) =cap_x(1,:)- 0.05;
-cap_x(2,:) =cap_x(2,:)+ 0.05;
-cap_y = whisker_y([1,1],:);
-
-% #quartile_x,quartile_y
-% #whisker_x,whisker_y
-% #median_x,median_y
-% #cap_x,cap_y
-%
-% ## Do the plot
-
-mm=min(min(data));
-MM=max(max(data));
-
-if vertical
- plot (quartile_x, quartile_y, 'b', ...
- whisker_x, whisker_y, 'b--', ...
- cap_x, cap_y, 'k', ...
- median_x, median_y, 'r', ...
- outliers_x, outliers_y, [symbol(1),'r'], ...
- outliers2_x, outliers2_y, [symbol(2),'r']);
- set(gca,'XTick',1:nc);
- set(gca, 'XLim', [0.5, nc+0.5]);
- set(gca, 'YLim', [mm-(MM-mm)*0.05, MM+(MM-mm)*0.05]);
-
-else
-% % % % % plot (quartile_y, quartile_x, "b;;",
-% % % % % whisker_y, whisker_x, "b;;",
-% % % % % cap_y, cap_x, "b;;",
-% % % % % median_y, median_x, "r;;",
-% % % % % outliers_y, outliers_x, [symbol(1),"r;;"],
-% % % % % outliers2_y, outliers2_x, [symbol(2),"r;;"]);
-end
-
-if nargout,
- sout=s;
-end
-% % % endfunction
\ No newline at end of file
diff --git a/GSA_distrib/4.0.3/myprctilecol.m b/GSA_distrib/4.0.3/myprctilecol.m
deleted file mode 100644
index d99d5ad5009d0081ba192acfc1595b2e054f8536..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/myprctilecol.m
+++ /dev/null
@@ -1,20 +0,0 @@
-function y = myprctilecol(x,p);
-xx = sort(x);
-[m,n] = size(x);
-
-if m==1 | n==1
- m = max(m,n);
- if m == 1,
- y = x*ones(length(p),1);
- return;
- end
- n = 1;
- q = 100*(0.5:m - 0.5)./m;
- xx = [min(x); xx(:); max(x)];
-else
- q = 100*(0.5:m - 0.5)./m;
- xx = [min(x); xx; max(x)];
-end
-
-q = [0 q 100];
-y = interp1(q,xx,p);
\ No newline at end of file
diff --git a/GSA_distrib/4.0.3/norm_inv.m b/GSA_distrib/4.0.3/norm_inv.m
deleted file mode 100644
index fc0f7356d6829149c2c17313bb99618b7c68d6c0..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/norm_inv.m
+++ /dev/null
@@ -1,44 +0,0 @@
-function invp = norm_inv(x, m, sd)
-% PURPOSE: computes the quantile (inverse of the CDF)
-% for each component of x with mean m, standard deviation sd
-%---------------------------------------------------
-% USAGE: invp = norm_inv(x,m,v)
-% where: x = variable vector (nx1)
-% m = mean vector (default=0)
-% sd = standard deviation vector (default=1)
-%---------------------------------------------------
-% RETURNS: invp (nx1) vector
-%---------------------------------------------------
-% SEE ALSO: norm_d, norm_rnd, norm_inv, norm_cdf
-%---------------------------------------------------
-
-% Written by KH (Kurt.Hornik@ci.tuwien.ac.at) on Oct 26, 1994
-% Copyright Dept of Probability Theory and Statistics TU Wien
-% Converted to MATLAB by JP LeSage, jpl@jpl.econ.utoledo.edu
-
- if nargin > 3
- error ('Wrong # of arguments to norm_inv');
- end
-
- [r, c] = size (x);
- s = r * c;
-
- if (nargin == 1)
- m = zeros(1,s);
- sd = ones(1,s);
- end
-
-
-
- x = reshape(x,1,s);
- m = reshape(m,1,s);
- sd = reshape(sd,1,s);
-
- invp = zeros (1,s);
-
- invp = m + sd .* (sqrt(2) * erfinv(2 * x - 1));
-
-
-
- invp = reshape (invp, r, c);
-
diff --git a/GSA_distrib/4.0.3/prior_draw_gsa.m b/GSA_distrib/4.0.3/prior_draw_gsa.m
deleted file mode 100644
index 7000a6dc0daf668fee46194c9dda414426cd6959..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/prior_draw_gsa.m
+++ /dev/null
@@ -1,125 +0,0 @@
-function pdraw = prior_draw_gsa(init,rdraw,cc)
-% Draws from the prior distributions
-% Adapted by M. Ratto from prior_draw (of DYNARE, copyright M. Juillard),
-% for use with Sensitivity Toolbox for DYNARE
-%
-%
-% INPUTS
-% o init [integer] scalar equal to 1 (first call) or 0.
-% o rdraw
-% o cc [double] two columns matrix (same as in
-% metropolis.m), constraints over the
-% parameter space (upper and lower bounds).
-%
-% OUTPUTS
-% o pdraw [double] draw from the joint prior density.
-%
-% ALGORITHM
-% ...
-%
-% SPECIAL REQUIREMENTS
-% MATLAB Statistics Toolbox
-%
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global M_ options_ estim_params_ bayestopt_
-persistent fname npar bounds pshape pmean pstd a b p1 p2 p3 p4 condition
-
-if init
- nvx = estim_params_.nvx;
- nvn = estim_params_.nvn;
- ncx = estim_params_.ncx;
- ncn = estim_params_.ncn;
- np = estim_params_.np ;
- npar = nvx+nvn+ncx+ncn+np;
- MhDirectoryName = CheckPath('metropolis');
- fname = [ MhDirectoryName '/' M_.fname];
- pshape = bayestopt_.pshape;
- pmean = bayestopt_.pmean;
- pstd = bayestopt_.pstdev;
- p1 = bayestopt_.p1;
- p2 = bayestopt_.p2;
- p3 = bayestopt_.p3;
- p4 = bayestopt_.p4;
- a = zeros(npar,1);
- b = zeros(npar,1);
- if nargin == 2
- bounds = cc;
- else
- bounds = kron(ones(npar,1),[-Inf Inf]);
- end
- for i = 1:npar
- switch pshape(i)
- case 3% Gaussian prior
- b(i) = pstd(i)^2/(pmean(i)-p3(i));
- a(i) = (pmean(i)-p3(i))/b(i);
- case 1% Beta prior
- mu = (p1(i)-p3(i))/(p4(i)-p3(i));
- stdd = p2(i)/(p4(i)-p3(i));
- a(i) = (1-mu)*mu^2/stdd^2 - mu;
- b(i) = a(i)*(1/mu - 1);
- case 2;%Gamma prior
- mu = p1(i)-p3(i);
- b(i) = p2(i)^2/mu;
- a(i) = mu/b(i);
- case {5,4,6}
- % Nothing to do here
- %
- % 4: Inverse gamma, type 1, prior
- % p2(i) = nu
- % p1(i) = s
- % 6: Inverse gamma, type 2, prior
- % p2(i) = nu
- % p1(i) = s
- % 5: Uniform prior
- % p3(i) and p4(i) are used.
- otherwise
- disp('prior_draw :: Error!')
- disp('Unknown prior shape.')
- return
- end
- pdraw = zeros(npar,1);
- end
- condition = 1;
- pdraw = zeros(npar,1);
- return
-end
-
-
-for i = 1:npar
- switch pshape(i)
- case 5% Uniform prior.
- pdraw(:,i) = rdraw(:,i)*(p4(i)-p3(i)) + p3(i);
- case 3% Gaussian prior.
- pdraw(:,i) = norm_inv(rdraw(:,i),pmean(i),pstd(i));
- case 2% Gamma prior.
- pdraw(:,i) = gamm_inv(rdraw(:,i),a(i),b(i))+p3(i);
- case 1% Beta distribution (TODO: generalized beta distribution)
- pdraw(:,i) = beta_inv(rdraw(:,i),a(i),b(i))*(p4(i)-p3(i))+p3(i);
- case 4% INV-GAMMA1 distribution
- % TO BE CHECKED
- pdraw(:,i) = sqrt(1./gamm_inv(rdraw(:,i),p2(i)/2,2/p1(i)));
- case 6% INV-GAMMA2 distribution
- % TO BE CHECKED
- pdraw(:,i) = 1./gamm_inv(rdraw(:,i),p2(i)/2,2/p1(i));
- otherwise
- % Nothing to do here.
- end
-end
-
-
diff --git a/GSA_distrib/4.0.3/priorcdf.m b/GSA_distrib/4.0.3/priorcdf.m
deleted file mode 100644
index 06151ccfef47a0678f4c293638024db13c062e5b..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/priorcdf.m
+++ /dev/null
@@ -1,45 +0,0 @@
-function [xcum] = priorcdf(para, pshape, p1, p2, p3, p4)
-% This procedure transforms x vectors into cumulative values
-% pshape: 0 is point mass, both para and p2 are ignored
-% 1 is BETA(mean,stdd)
-% 2 is GAMMA(mean,stdd)
-% 3 is NORMAL(mean,stdd)
-% 4 is INVGAMMA(s^2,nu)
-% 5 is UNIFORM [p1,p2]
-% Adapted by M. Ratto from MJ priordens.m
-
-nprio = length(pshape);
-
-i = 1;
-while i <= nprio;
- a = 0;
- b = 0;
- if pshape(i) == 1; % (generalized) BETA Prior
- mu = (p1(i)-p3(i))/(p4(i)-p3(i));
- stdd = p2(i)/(p4(i)-p3(i));
- a = (1-mu)*mu^2/stdd^2 - mu;
- b = a*(1/mu - 1);
- %lnprior = lnprior + lpdfgbeta(para(i),a,b,p3(i),p4(i)) ;
- para(:,i) = (para(:,i)-p3(i))./(p4(i)-p3(i));
- xcum(:,i) = betacdf(para(:,i),a,b) ;
- elseif pshape(i) == 2; % GAMMA PRIOR
- b = p2(i)^2/(p1(i)-p3(i));
- a = (p1(i)-p3(i))/b;
- %lnprior = lnprior + lpdfgam(para(i)-p3(i),a,b);
- xcum(:,i) = gamcdf(para(:,i)-p3(i),a,b);
- elseif pshape(i) == 3; % GAUSSIAN PRIOR
- %lnprior = lnprior + lpdfnorm(para(i),p1(i),p2(i));
- xcum(:,i) = normcdf(para(:,i),p1(i),p2(i));
- elseif pshape(i) == 4; % INVGAMMA1 PRIOR
- %lnprior = lnprior + lpdfig1(para(i),p1(i),p2(i));
- xcum(:,i) = gamcdf(1/para(:,i).^2,p2(i)/2,2/p1(i));
- elseif pshape(i) == 5; % UNIFORM PRIOR
- %lnprior = lnprior + log(1/(p2(i)-p1(i)));
- xcum(:,i) = (para(:,i)-p1(i))./(p2(i)-p1(i));
- elseif pshape(i) == 6; % INVGAMMA2 PRIOR
-% lnprior = lnprior + lpdfig2(para(i),p1(i),p2(i));
- xcum(:,i) = gamcdf(1/para(:,i),p2(i)/2,2/p1(i));
- end;
- i = i+1;
-end;
-
diff --git a/GSA_distrib/4.0.3/read_data.m b/GSA_distrib/4.0.3/read_data.m
deleted file mode 100644
index f54f66cb67269238108c8d93383d5e0cdf66a458..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/read_data.m
+++ /dev/null
@@ -1,39 +0,0 @@
-function [gend, data] = read_data
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global options_ bayestopt_
-
-rawdata = read_variables(options_.datafile,options_.varobs,[],options_.xls_sheet,options_.xls_range);
-
-options_ = set_default_option(options_,'nobs',size(rawdata,1)-options_.first_obs+1);
-gend = options_.nobs;
-
-rawdata = rawdata(options_.first_obs:options_.first_obs+gend-1,:);
-if options_.loglinear == 1 & ~options_.logdata
- rawdata = log(rawdata);
-end
-if options_.prefilter == 1
- bayestopt_.mean_varobs = mean(rawdata,1);
- data = transpose(rawdata-ones(gend,1)*bayestopt_.mean_varobs);
-else
- data = transpose(rawdata);
-end
-
-if ~isreal(rawdata)
- error(['There are complex values in the data. Probably a wrong' ...
- ' transformation'])
-end
diff --git a/GSA_distrib/4.0.3/redform_map.m b/GSA_distrib/4.0.3/redform_map.m
deleted file mode 100644
index c5022a19c347e74541e5abc6c8d5cd7f854572ab..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/redform_map.m
+++ /dev/null
@@ -1,342 +0,0 @@
-function redform_map(dirname)
-%function redform_map(dirname)
-% inputs (from opt_gsa structure
-% anamendo = options_gsa_.namendo;
-% anamlagendo = options_gsa_.namlagendo;
-% anamexo = options_gsa_.namexo;
-% iload = options_gsa_.load_redform;
-% pprior = options_gsa_.pprior;
-% ilog = options_gsa_.logtrans_redform;
-% threshold = options_gsa_.threshold_redform;
-% ksstat = options_gsa_.ksstat_redform;
-% alpha2 = options_gsa_.alpha2_redform;
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global M_ oo_ estim_params_ options_ bayestopt_
-
-options_gsa_ = options_.opt_gsa;
-
-anamendo = options_gsa_.namendo;
-anamlagendo = options_gsa_.namlagendo;
-anamexo = options_gsa_.namexo;
-iload = options_gsa_.load_redform;
-pprior = options_gsa_.pprior;
-ilog = options_gsa_.logtrans_redform;
-threshold = options_gsa_.threshold_redform;
-ksstat = options_gsa_.ksstat_redform;
-alpha2 = options_gsa_.alpha2_redform;
-
-pnames = M_.param_names(estim_params_.param_vals(:,1),:);
-if nargin==0,
- dirname='';
-end
-
-if pprior
- load([dirname,'\',M_.fname,'_prior']);
- adir=[dirname '\redform_stab'];
-else
- load([dirname,'\',M_.fname,'_mc']);
- adir=[dirname '\redform_mc'];
-end
-if ~exist('T')
- stab_map_(dirname);
-if pprior
- load([dirname,'\',M_.fname,'_prior'],'T');
-else
- load([dirname,'\',M_.fname,'_mc'],'T');
-end
-end
-if isempty(dir(adir))
- mkdir(adir)
-end
-adir0=pwd;
-%cd(adir)
-
-nspred=size(T,2)-M_.exo_nbr;
-x0=lpmat(istable,:);
-[kn, np]=size(x0);
-offset = length(bayestopt_.pshape)-np;
-if options_gsa_.prior_range,
- pshape=5*(ones(np,1));
- pd = [NaN(np,1) NaN(np,1) bayestopt_.lb(offset+1:end) bayestopt_.ub(offset+1:end)];
-else
- pshape = bayestopt_.pshape(offset+1:end);
- pd = [bayestopt_.p1(offset+1:end) bayestopt_.p2(offset+1:end) bayestopt_.p3(offset+1:end) bayestopt_.p4(offset+1:end)];
-end
-
-nsok = length(find(M_.lead_lag_incidence(M_.maximum_lag,:)));
-clear lpmat lpmat0 egg iunstable yys
-js=0;
-for j=1:size(anamendo,1)
- namendo=deblank(anamendo(j,:));
- iendo=strmatch(namendo,M_.endo_names(oo_.dr.order_var,:),'exact');
- ifig=0;
- iplo=0;
- for jx=1:size(anamexo,1)
- namexo=deblank(anamexo(jx,:));
- iexo=strmatch(namexo,M_.exo_names,'exact');
-
- if ~isempty(iexo),
- %y0=squeeze(T(iendo,iexo+nspred,istable));
- y0=squeeze(T(iendo,iexo+nspred,:));
- if (max(y0)-min(y0))>1.e-10,
- if mod(iplo,9)==0,
- ifig=ifig+1;
- figure('name',[namendo,' vs. shocks ',int2str(ifig)]),
- iplo=0;
- end
- iplo=iplo+1;
- js=js+1;
- xdir0 = [adir,'\',namendo,'_vs_', namexo];
- if ilog==0,
- if isempty(threshold)
- si(:,js) = redform_private(x0, y0, pshape, pd, iload, pnames, namendo, namexo, xdir0);
- else
- iy=find( (y0>threshold(1)) & (y0<threshold(2)));
- iyc=find( (y0<=threshold(1)) | (y0>=threshold(2)));
- xdir = [xdir0,'_cut'];
- if ~isempty(iy),
- si(:,js) = redform_private(x0(iy,:), y0(iy), pshape, pd, iload, pnames, namendo, namexo, xdir);
- end
- if ~isempty(iy) & ~isempty(iyc)
- delete([xdir, '\*cut*.*'])
- [proba, dproba] = stab_map_1(x0, iy, iyc, 'cut',0);
- indsmirnov = find(dproba>ksstat);
- stab_map_1(x0, iy, iyc, 'cut',1,indsmirnov,xdir);
- stab_map_2(x0(iy,:),alpha2,'cut',xdir)
- stab_map_2(x0(iyc,:),alpha2,'trim',xdir)
- end
- end
- else
- [yy, xdir] = log_trans_(y0,xdir0);
- silog(:,js) = redform_private(x0, yy, pshape, pd, iload, pnames, namendo, namexo, xdir);
- end
-
- subplot(3,3,iplo),
- if ilog,
- [saso, iso] = sort(-silog(:,js));
- bar([silog(iso(1:min(np,10)),js)])
- logflag='log';
- else
- [saso, iso] = sort(-si(:,js));
- bar(si(iso(1:min(np,10)),js))
- logflag='';
- end
- %set(gca,'xticklabel',pnames(iso(1:min(np,10)),:),'fontsize',8)
- set(gca,'xticklabel',' ','fontsize',10)
- set(gca,'xlim',[0.5 10.5])
- for ip=1:min(np,10),
- text(ip,-0.02,deblank(pnames(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- title([logflag,' ',namendo,' vs. ',namexo],'interpreter','none')
- if iplo==9,
- saveas(gcf,[dirname,'\',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)])
- eval(['print -depsc2 ' dirname,'\',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)]);
- eval(['print -dpdf ' dirname,'\',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)]);
- close(gcf)
- end
-
- end
- end
- end
- if iplo<9 & iplo>0 & ifig,
- saveas(gcf,[dirname,'\',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)])
- eval(['print -depsc2 ' dirname,'\',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)]);
- eval(['print -dpdf ' dirname,'\',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)]);
- close(gcf)
- end
- ifig=0;
- iplo=0;
- for je=1:size(anamlagendo,1)
- namlagendo=deblank(anamlagendo(je,:));
- ilagendo=strmatch(namlagendo,M_.endo_names(oo_.dr.order_var(oo_.dr.nstatic+1:oo_.dr.nstatic+nsok),:),'exact');
-
- if ~isempty(ilagendo),
- %y0=squeeze(T(iendo,ilagendo,istable));
- y0=squeeze(T(iendo,ilagendo,:));
- if (max(y0)-min(y0))>1.e-10,
- if mod(iplo,9)==0,
- ifig=ifig+1;
- figure('name',[namendo,' vs. lags ',int2str(ifig)]),
- iplo=0;
- end
- iplo=iplo+1;
- js=js+1;
- xdir0 = [adir,'\',namendo,'_vs_', namlagendo];
- if ilog==0,
- if isempty(threshold)
- si(:,js) = redform_private(x0, y0, pshape, pd, iload, pnames, namendo, namlagendo, xdir0);
- else
- iy=find( (y0>threshold(1)) & (y0<threshold(2)));
- iyc=find( (y0<=threshold(1)) | (y0>=threshold(2)));
- xdir = [xdir0,'_cut'];
- if ~isempty(iy)
- si(:,js) = redform_private(x0(iy,:), y0(iy), pshape, pd, iload, pnames, namendo, namlagendo, xdir);
- end
- if ~isempty(iy) & ~isempty(iyc),
- delete([xdir, '\*cut*.*'])
- [proba, dproba] = stab_map_1(x0, iy, iyc, 'cut',0);
- indsmirnov = find(dproba>ksstat);
- stab_map_1(x0, iy, iyc, 'cut',1,indsmirnov,xdir);
- stab_map_2(x0(iy,:),alpha2,'cut',xdir)
- stab_map_2(x0(iyc,:),alpha2,'trim',xdir)
- end
- end
- else
- [yy, xdir] = log_trans_(y0,xdir0);
- silog(:,js) = redform_private(x0, yy, pshape, pd, iload, pnames, namendo, namlagendo, xdir);
- end
-
- subplot(3,3,iplo),
- if ilog,
- [saso, iso] = sort(-silog(:,js));
- bar([silog(iso(1:min(np,10)),js)])
- logflag='log';
- else
- [saso, iso] = sort(-si(:,js));
- bar(si(iso(1:min(np,10)),js))
- logflag='';
- end
- %set(gca,'xticklabel',pnames(iso(1:min(np,10)),:),'fontsize',8)
- set(gca,'xticklabel',' ','fontsize',10)
- set(gca,'xlim',[0.5 10.5])
- for ip=1:min(np,10),
- text(ip,-0.02,deblank(pnames(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- title([logflag,' ',namendo,' vs. ',namlagendo,'(-1)'],'interpreter','none')
- if iplo==9,
- saveas(gcf,[dirname,'\',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)])
- eval(['print -depsc2 ' dirname,'\',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)]);
- eval(['print -dpdf ' dirname,'\',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)]);
- close(gcf)
- end
-
- end
- end
- end
- if iplo<9 & iplo>0 & ifig,
- saveas(gcf,[dirname,'\',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)])
- eval(['print -depsc2 ' dirname,'\',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)]);
- eval(['print -dpdf ' dirname,'\',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)]);
- close(gcf)
- end
-end
-
-if ilog==0,
-figure, %bar(si)
-% boxplot(si','whis',10,'symbol','r.')
-myboxplot(si',[],'.',[],10)
-xlabel(' ')
-set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-set(gca,'xlim',[0.5 np+0.5])
-set(gca,'ylim',[0 1])
-set(gca,'position',[0.13 0.2 0.775 0.7])
-for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-end
-title('Reduced form GSA')
-
-saveas(gcf,[dirname,'\',M_.fname,'_redform_gsa'])
-eval(['print -depsc2 ' dirname,'\',M_.fname,'_redform_gsa']);
-eval(['print -dpdf ' dirname,'\',M_.fname,'_redform_gsa']);
-
-else
-figure, %bar(silog)
-% boxplot(silog','whis',10,'symbol','r.')
-myboxplot(silog',[],'.',[],10)
-set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-xlabel(' ')
-set(gca,'xlim',[0.5 np+0.5])
-set(gca,'ylim',[0 1])
-set(gca,'position',[0.13 0.2 0.775 0.7])
-for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-end
-title('Reduced form GSA - Log-transformed elements')
-
-saveas(gcf,[dirname,'\',M_.fname,'_redform_gsa_log'])
-eval(['print -depsc2 ' dirname,'\',M_.fname,'_redform_gsa_log']);
-eval(['print -dpdf ' dirname,'\',M_.fname,'_redform_gsa_log']);
-
-end
-function si = redform_private(x0, y0, pshape, pd, iload, pnames, namy, namx, xdir)
-global bayestopt_ options_
-
-opt_gsa=options_.opt_gsa;
-np=size(x0,2);
- if opt_gsa.prior_range,
- for j=1:np,
- x0(:,j)=(x0(:,j)-pd(j,3))./(pd(j,4)-pd(j,3));
- end
- else
- x0=priorcdf(x0,pshape, pd(:,1), pd(:,2), pd(:,3), pd(:,4));
- end
-
-fname=[xdir,'\map'];
-if iload==0,
- figure, hist(y0,30), title([namy,' vs. ', namx])
- if isempty(dir(xdir))
- mkdir(xdir)
- end
- saveas(gcf,[xdir,'\', namy,'_vs_', namx])
- eval(['print -depsc2 ' xdir,'\', namy,'_vs_', namx]);
- eval(['print -dpdf ' xdir,'\', namy,'_vs_', namx]);
- close(gcf)
-% gsa_ = gsa_sdp_dyn(y0, x0, -2, [],[],[],1,fname, pnames);
- nrun=length(y0);
- nest=min(250,nrun);
- nfit=min(1000,nrun);
- gsa_ = gsa_sdp(y0(1:nest), x0(1:nest,:), 2, [],[],[],0,[fname,'_est'], pnames);
- if nfit>nest,
- gsa_ = gsa_sdp(y0(1:nfit), x0(1:nfit,:), -2, gsa_.nvr*nest^3/nfit^3,[],[],1,fname, pnames);
- else
- copyfile([fname,'_est.mat'],[fname,'.mat'])
- end
- figure,
- plot(y0(1:nfit),[gsa_.fit y0(1:nfit)],'.'),
- title([namy,' vs. ', namx,' fit'])
- saveas(gcf,[xdir,'\', namy,'_vs_', namx,'_fit'])
- eval(['print -depsc2 ' xdir,'\', namy,'_vs_', namx,'_fit']);
- eval(['print -dpdf ' xdir,'\', namy,'_vs_', namx,'_fit']);
- close(gcf)
- if nfit<nrun,
- npred=[nfit+1:nrun];
- yf = ss_anova_fcast(x0(npred,:), gsa_);
- figure,
- plot(y0(npred),[yf y0(npred)],'.'),
- title([namy,' vs. ', namx,' pred'])
- saveas(gcf,[xdir,'\', namy,'_vs_', namx,'_pred'])
- eval(['print -depsc2 ' xdir,'\', namy,'_vs_', namx,'_pred']);
- eval(['print -dpdf ' xdir,'\', namy,'_vs_', namx,'_pred']);
- close(gcf)
- end
-else
-% gsa_ = gsa_sdp_dyn(y0, x0, 0, [],[],[],0,fname, pnames);
- gsa_ = gsa_sdp(y0, x0, 0, [],[],[],0,fname, pnames);
- yf = ss_anova_fcast(x0, gsa_);
- figure,
- plot(y0,[yf y0],'.'),
- title([namy,' vs. ', namx,' pred'])
- saveas(gcf,[xdir,'\', namy,'_vs_', namx,'_pred'])
- eval(['print -depsc2 ' xdir,'\', namy,'_vs_', namx,'_pred']);
- eval(['print -dpdf ' xdir,'\', namy,'_vs_', namx,'_pred']);
- close(gcf)
-end
-% si = gsa_.multivariate.si;
-si = gsa_.si;
-
diff --git a/GSA_distrib/4.0.3/redform_screen.m b/GSA_distrib/4.0.3/redform_screen.m
deleted file mode 100644
index c8f7e1865ac11629a6f103d2f5329de184770890..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/redform_screen.m
+++ /dev/null
@@ -1,165 +0,0 @@
-function redform_screen(dirname)
-%function redform_map(dirname)
-% inputs (from opt_gsa structure
-% anamendo = options_gsa_.namendo;
-% anamlagendo = options_gsa_.namlagendo;
-% anamexo = options_gsa_.namexo;
-% iload = options_gsa_.load_redform;
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global M_ oo_ estim_params_ options_ bayestopt_
-
-options_gsa_ = options_.opt_gsa;
-
-anamendo = options_gsa_.namendo;
-anamlagendo = options_gsa_.namlagendo;
-anamexo = options_gsa_.namexo;
-iload = options_gsa_.load_redform;
-nliv = options_gsa_.morris_nliv;
-
-pnames = M_.param_names(estim_params_.param_vals(:,1),:);
-if nargin==0,
- dirname='';
-end
-
-load([dirname,'\',M_.fname,'_prior'],'lpmat','lpmat0','istable','T');
-
-nspred=oo_.dr.nspred;
-
-[kn, np]=size(lpmat);
-nshock = length(bayestopt_.pshape)-np;
-
-nsok = length(find(M_.lead_lag_incidence(M_.maximum_lag,:)));
-
-js=0;
-for j=1:size(anamendo,1),
- namendo=deblank(anamendo(j,:));
- iendo=strmatch(namendo,M_.endo_names(oo_.dr.order_var,:),'exact');
-
- iplo=0;
- ifig=0;
- for jx=1:size(anamexo,1)
- namexo=deblank(anamexo(jx,:));
- iexo=strmatch(namexo,M_.exo_names,'exact');
-
- if ~isempty(iexo),
- y0=teff(T(iendo,iexo+nspred,:),kn,istable);
- if ~isempty(y0),
- if mod(iplo,9)==0,
- ifig=ifig+1;
- figure('name',[namendo,' vs. shocks ',int2str(ifig)]),
- iplo=0;
- end
- iplo=iplo+1;
- js=js+1;
- subplot(3,3,iplo),
- [SAmeas, SAMorris] = Morris_Measure_Groups(np+nshock, [lpmat0 lpmat], y0,nliv);
- SAM = squeeze(SAMorris(nshock+1:end,1));
- SA(:,js)=SAM./(max(SAM)+eps);
- [saso, iso] = sort(-SA(:,js));
- bar(SA(iso(1:min(np,10)),js))
- %set(gca,'xticklabel',pnames(iso(1:min(np,10)),:),'fontsize',8)
- set(gca,'xticklabel',' ','fontsize',10)
- set(gca,'xlim',[0.5 10.5])
- for ip=1:min(np,10),
- text(ip,-0.02,deblank(pnames(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- title([namendo,' vs. ',namexo],'interpreter','none')
- if iplo==9,
- saveas(gcf,[dirname,'\',M_.fname,'_', namendo,'_vs_shock_',num2str(ifig)])
- eval(['print -depsc2 ' dirname,'\',M_.fname,'_', namendo,'_vs_shock_',num2str(ifig)]);
- eval(['print -dpdf ' dirname,'\',M_.fname,'_', namendo,'_vs_shock_',num2str(ifig)]);
- close(gcf)
- end
-
- end
- end
- end
- if iplo<9 & iplo>0 & ifig,
- saveas(gcf,[dirname,'\',M_.fname,'_', namendo,'_vs_shocks_',num2str(ifig)])
- eval(['print -depsc2 ' dirname,'\',M_.fname,'_', namendo,'_vs_shocks_',num2str(ifig)]);
- eval(['print -dpdf ' dirname,'\',M_.fname,'_', namendo,'_vs_shocks_',num2str(ifig)]);
- close(gcf)
- end
-
- iplo=0;
- ifig=0;
- for je=1:size(anamlagendo,1)
- namlagendo=deblank(anamlagendo(je,:));
- ilagendo=strmatch(namlagendo,M_.endo_names(oo_.dr.order_var(oo_.dr.nstatic+1:oo_.dr.nstatic+nsok),:),'exact');
-
- if ~isempty(ilagendo),
- y0=teff(T(iendo,ilagendo,:),kn,istable);
- if ~isempty(y0),
- if mod(iplo,9)==0,
- ifig=ifig+1;
- figure('name',[namendo,' vs. lagged endogenous ',int2str(ifig)]),
- iplo=0;
- end
- iplo=iplo+1;
- js=js+1;
- subplot(3,3,iplo),
- [SAmeas, SAMorris] = Morris_Measure_Groups(np+nshock, [lpmat0 lpmat], y0,nliv);
- SAM = squeeze(SAMorris(nshock+1:end,1));
- SA(:,js)=SAM./(max(SAM)+eps);
- [saso, iso] = sort(-SA(:,js));
- bar(SA(iso(1:min(np,10)),js))
- %set(gca,'xticklabel',pnames(iso(1:min(np,10)),:),'fontsize',8)
- set(gca,'xticklabel',' ','fontsize',10)
- set(gca,'xlim',[0.5 10.5])
- for ip=1:min(np,10),
- text(ip,-0.02,deblank(pnames(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
-
- title([namendo,' vs. ',namlagendo,'(-1)'],'interpreter','none')
- if iplo==9,
- saveas(gcf,[dirname,'\',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)])
- eval(['print -depsc2 ' dirname,'\',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)]);
- eval(['print -dpdf ' dirname,'\',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)]);
- close(gcf)
- end
- end
- end
- end
- if iplo<9 & iplo>0 & ifig,
- saveas(gcf,[dirname,'\',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)])
- eval(['print -depsc2 ' dirname,'\',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)]);
- eval(['print -dpdf ' dirname,'\',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)]);
- close(gcf)
- end
-end
-
-figure,
-%bar(SA)
-% boxplot(SA','whis',10,'symbol','r.')
-myboxplot(SA',[],'.',[],10)
-set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-set(gca,'xlim',[0.5 np+0.5])
-set(gca,'ylim',[0 1])
-set(gca,'position',[0.13 0.2 0.775 0.7])
-for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-end
-xlabel(' ')
-ylabel('Elementary Effects')
-title('Reduced form screening')
-
-saveas(gcf,[dirname,'\',M_.fname,'_redform_screen'])
-eval(['print -depsc2 ' dirname,'\',M_.fname,'_redform_screen']);
-eval(['print -dpdf ' dirname,'\',M_.fname,'_redform_screen']);
-
diff --git a/GSA_distrib/4.0.3/set_shocks_param.m b/GSA_distrib/4.0.3/set_shocks_param.m
deleted file mode 100644
index f84247d299917645863b894899ee43c7b53e9391..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/set_shocks_param.m
+++ /dev/null
@@ -1,30 +0,0 @@
-function set_shocks_param(xparam1)
- global estim_params_ M_
-
- nvx = estim_params_.nvx;
- ncx = estim_params_.ncx;
- np = estim_params_.np;
- Sigma_e = M_.Sigma_e;
- offset = 0;
- if nvx
- offset = offset + nvx;
- var_exo = estim_params_.var_exo;
- for i=1:nvx
- k = var_exo(i,1);
- Sigma_e(k,k) = xparam1(i)^2;
- end
- end
-
- if ncx
- offset = offset + estim_params_.nvn;
- corrx = estim_params_.corrx;
- for i=1:ncx
- k1 = corrx(i,1);
- k2 = corrx(i,2);
- Sigma_e(k1,k2) = xparam1(i+offset)*sqrt(Sigma_e_(k1,k1)*Sigma_e_(k2,k2));
- Sigma_e(k2,k1) = Sigma_e_(k1,k2);
- end
- end
-
-
- M_.Sigma_e = Sigma_e;
\ No newline at end of file
diff --git a/GSA_distrib/4.0.3/skewness.m b/GSA_distrib/4.0.3/skewness.m
deleted file mode 100644
index 19ce487ab85deb85797680f06fc12f8db20c9d4b..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/skewness.m
+++ /dev/null
@@ -1,7 +0,0 @@
-function s=skewness(y),
-
-% y=stand_(y);
-% s=mean(y.^3);
- m2=mean((y-mean(y)).^2);
- m3=mean((y-mean(y)).^3);
- s=m3/m2^1.5;
\ No newline at end of file
diff --git a/GSA_distrib/4.0.3/smirnov.m b/GSA_distrib/4.0.3/smirnov.m
deleted file mode 100644
index bc068aeb1046e90ee8f739deff1c256a5bc0fcba..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/smirnov.m
+++ /dev/null
@@ -1,73 +0,0 @@
-function [H,prob,d] = smirnov(x1 , x2 , alpha, iflag )
-% Smirnov test for 2 distributions
-% [H,prob,d] = smirnov(x1 , x2 , alpha, iflag )
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-
-
-if nargin<3
- alpha = 0.05;
-end
-if nargin<4,
- iflag=0;
-end
-
-% empirical cdfs.
-xmix= [x1;x2];
-bin = [-inf ; sort(xmix) ; inf];
-
-ncount1 = histc (x1 , bin);
-ncount1 = ncount1(:);
-ncount2 = histc (x2 , bin);
-ncount2 = ncount2(:);
-
-cum1 = cumsum(ncount1)./sum(ncount1);
-cum1 = cum1(1:end-1);
-
-cum2 = cumsum(ncount2)./sum(ncount2);
-cum2 = cum2(1:end-1);
-
-n1= length(x1);
-n2= length(x2);
-n = n1*n2 /(n1+n2);
-
-% Compute the d(n1,n2) statistics.
-
-if iflag==0,
- d = max(abs(cum1 - cum2));
-elseif iflag==-1
- d = max(cum2 - cum1);
-elseif iflag==1
- d = max(cum1 - cum2);
-end
-%
-% Compute P-value check H0 hypothesis
-%
-
-lam = max((sqrt(n) + 0.12 + 0.11/sqrt(n)) * d , 0);
-if iflag == 0
- j = [1:101]';
- prob = 2 * sum((-1).^(j-1).*exp(-2*lam*lam*j.^2));
-
- prob=max(prob,0);
- prob=min(1,prob);
-else
- prob = exp(-2*lam*lam);
-end
-
-H = (alpha >= prob);
diff --git a/GSA_distrib/4.0.3/speed.m b/GSA_distrib/4.0.3/speed.m
deleted file mode 100644
index faaa1de86ead1e91c71bcbf0f81f09cdc2c3e587..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/speed.m
+++ /dev/null
@@ -1,52 +0,0 @@
-function [tadj, iff] = speed(A,B,mf,p),
-% [tadj, iff] = speed(A,B,mf,p),
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-nvar=length(mf);
-nstate= size(A,1);
-nshock = size(B,2);
-nrun=size(B,3);
-
-iff=zeros(nvar,nshock,nrun);
-tadj=iff;
-disp('Computing speed of adjustement ...')
-h = waitbar(0,'Speed of adjustement...');
-
-for i=1:nrun,
- irf=zeros(nvar,nshock);
- a=squeeze(A(:,:,i));
- b=squeeze(B(:,:,i));
- IFF=inv(eye(nstate)-a)*b;
- iff(:,:,i)=IFF(mf,:);
- IF=IFF-b;
-
- t=0;
- while any(any(irf<0.5))
- t=t+1;
- IFT=((eye(nstate)-a^(t+1))*inv(eye(nstate)-a))*b-b;
- irf=IFT(mf,:)./(IF(mf,:)+eps);
- irf = irf.*(abs(IF(mf,:))>1.e-7)+(abs(IF(mf,:))<=1.e-7);
- %irf=ft(mf,:);
- tt=(irf>0.5).*t;
- tadj(:,:,i)=((tt-tadj(:,:,i))==tt).*tt+tadj(:,:,i);
- end
- waitbar(i/nrun,h)
-end
-disp(' ')
-disp('.. done !')
-close(h)
diff --git a/GSA_distrib/4.0.3/stab_map_.m b/GSA_distrib/4.0.3/stab_map_.m
deleted file mode 100644
index 7bfa4cb15052617c1a1b15feb68e959969a64d89..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/stab_map_.m
+++ /dev/null
@@ -1,511 +0,0 @@
-function x0 = stab_map_(OutputDirectoryName)
-%
-% function x0 = stab_map_(OutputDirectoryName)
-%
-% Mapping of stability regions in the prior ranges applying
-% Monte Carlo filtering techniques.
-%
-% INPUTS (from opt_gsa structure)
-% Nsam = MC sample size
-% fload = 0 to run new MC; 1 to load prevoiusly generated analysis
-% alpha2 = significance level for bivariate sensitivity analysis
-% [abs(corrcoef) > alpha2]
-% prepSA = 1: save transition matrices for mapping reduced form
-% = 0: no transition matrix saved (default)
-% pprior = 1: sample from prior ranges (default): sample saved in
-% _prior.mat file
-% = 0: sample from posterior ranges: sample saved in
-% _mc.mat file
-% OUTPUT:
-% x0: one parameter vector for which the model is stable.
-%
-% GRAPHS
-% 1) Pdf's of marginal distributions under the stability (dotted
-% lines) and unstability (solid lines) regions
-% 2) Cumulative distributions of:
-% - stable subset (dotted lines)
-% - unacceptable subset (solid lines)
-% 3) Bivariate plots of significant correlation patterns
-% ( abs(corrcoef) > alpha2) under the stable and unacceptable subsets
-%
-% USES lptauSEQ,
-% stab_map_1, stab_map_2
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-%global bayestopt_ estim_params_ dr_ options_ ys_ fname_
-global bayestopt_ estim_params_ options_ oo_ M_
-
-opt_gsa=options_.opt_gsa;
-
-Nsam = opt_gsa.Nsam;
-fload = opt_gsa.load_stab;
-ksstat = opt_gsa.ksstat;
-alpha2 = opt_gsa.alpha2_stab;
-prepSA = (opt_gsa.redform | opt_gsa.identification);
-pprior = opt_gsa.pprior;
-ilptau = opt_gsa.ilptau;
-nliv = opt_gsa.morris_nliv;
-ntra = opt_gsa.morris_ntra;
-
-dr_ = oo_.dr;
-%if isfield(dr_,'ghx'),
- ys_ = oo_.dr.ys;
- nspred = dr_.nspred; %size(dr_.ghx,2);
- nboth = dr_.nboth;
- nfwrd = dr_.nfwrd;
-%end
-fname_ = M_.fname;
-
-np = estim_params_.np;
-nshock = estim_params_.nvx;
-nshock = nshock + estim_params_.nvn;
-nshock = nshock + estim_params_.ncx;
-nshock = nshock + estim_params_.ncn;
-lpmat0=[];
-
-pshape = bayestopt_.pshape(nshock+1:end);
-p1 = bayestopt_.p1(nshock+1:end);
-p2 = bayestopt_.p2(nshock+1:end);
-p3 = bayestopt_.p3(nshock+1:end);
-p4 = bayestopt_.p4(nshock+1:end);
-
-if nargin==0,
- OutputDirectoryName='';
-end
-
-opt=options_;
- options_.periods=0;
- options_.nomoments=1;
- options_.irf=0;
- options_.noprint=1;
- options_.simul=0;
-if fload==0,
-% if prepSA
-% T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),Nsam/2);
-% end
-
- if isfield(dr_,'ghx'),
- egg=zeros(length(dr_.eigval),Nsam);
- end
- yys=zeros(length(dr_.ys),Nsam);
-
- if opt_gsa.morris
- if opt_gsa.morris == 1
- [lpmat, OutFact] = Sampling_Function_2(nliv, np+nshock, ntra, ones(np+nshock, 1), zeros(np+nshock,1), []);
- lpmat = lpmat.*(nliv-1)/nliv+1/nliv/2;
- Nsam=size(lpmat,1);
- lpmat0 = lpmat(:,1:nshock);
- lpmat = lpmat(:,nshock+1:end);
- elseif opt_gsa.morris==2
- lpmat = prep_ide(Nsam,np,5);
- Nsam=size(lpmat,1);
- end
- else
- if np<52 & ilptau>0,
- [lpmat] = lptauSEQ(Nsam,np); % lptau
- if np>30 | ilptau==2, % scrambled lptau
- for j=1:np,
- lpmat(:,j)=lpmat(randperm(Nsam),j);
- end
- end
- else ilptau==0
- %[lpmat] = rand(Nsam,np);
- for j=1:np,
- lpmat(:,j) = randperm(Nsam)'./(Nsam+1); %latin hypercube
- end
-
- end
- end
- try
- dummy=prior_draw_gsa(1);
- catch
- if pprior,
- if opt_gsa.prior_range==0;
- error('Some unknown prior is specified or ML estimation,: use prior_range=1 option!!');
- end
- end
-
- end
- if pprior,
- for j=1:nshock,
- if opt_gsa.morris~=1,
- lpmat0(:,j) = randperm(Nsam)'./(Nsam+1); %latin hypercube
- end
- if opt_gsa.prior_range
- lpmat0(:,j)=lpmat0(:,j).*(bayestopt_.ub(j)-bayestopt_.lb(j))+bayestopt_.lb(j);
- end
- end
- if opt_gsa.prior_range
- for j=1:np,
- lpmat(:,j)=lpmat(:,j).*(bayestopt_.ub(j+nshock)-bayestopt_.lb(j+nshock))+bayestopt_.lb(j+nshock);
- end
- else
- xx=prior_draw_gsa(0,[lpmat0 lpmat]);
- lpmat0=xx(:,1:nshock);
- lpmat=xx(:,nshock+1:end);
- clear xx;
- end
- else
- % for j=1:nshock,
- % xparam1(j) = oo_.posterior_mode.shocks_std.(bayestopt_.name{j});
- % sd(j) = oo_.posterior_std.shocks_std.(bayestopt_.name{j});
- % lpmat0(:,j) = randperm(Nsam)'./(Nsam+1); %latin hypercube
- % lb = max(bayestopt_.lb(j), xparam1(j)-2*sd(j));
- % ub1=xparam1(j)+(xparam1(j) - lb); % define symmetric range around the mode!
- % ub = min(bayestopt_.ub(j),ub1);
- % if ub<ub1,
- % lb=xparam1(j)-(ub-xparam1(j)); % define symmetric range around the mode!
- % end
- % lpmat0(:,j) = lpmat0(:,j).*(ub-lb)+lb;
- % end
- % %
- % for j=1:np,
- % xparam1(j+nshock) = oo_.posterior_mode.parameters.(bayestopt_.name{j+nshock});
- % sd(j+nshock) = oo_.posterior_std.parameters.(bayestopt_.name{j+nshock});
- % lb = max(bayestopt_.lb(j+nshock),xparam1(j+nshock)-2*sd(j+nshock));
- % ub1=xparam1(j+nshock)+(xparam1(j+nshock) - lb); % define symmetric range around the mode!
- % ub = min(bayestopt_.ub(j+nshock),ub1);
- % if ub<ub1,
- % lb=xparam1(j+nshock)-(ub-xparam1(j+nshock)); % define symmetric range around the mode!
- % end
- % %ub = min(bayestopt_.ub(j+nshock),xparam1(j+nshock)+2*sd(j+nshock));
- % if np>30 & np<52
- % lpmat(:,j) = lpmat(randperm(Nsam),j).*(ub-lb)+lb;
- % else
- % lpmat(:,j) = lpmat(:,j).*(ub-lb)+lb;
- % end
- % end
- %load([fname_,'_mode'])
- eval(['load ' options_.mode_file ';']');
- d = chol(inv(hh));
- lp=randn(Nsam*2,nshock+np)*d+kron(ones(Nsam*2,1),xparam1');
- for j=1:Nsam*2,
- lnprior(j) = any(lp(j,:)'<=bayestopt_.lb | lp(j,:)'>=bayestopt_.ub);
- end
- ireal=[1:2*Nsam];
- ireal=ireal(find(lnprior==0));
- lp=lp(ireal,:);
- Nsam=min(Nsam, length(ireal));
- lpmat0=lp(1:Nsam,1:nshock);
- lpmat=lp(1:Nsam,nshock+1:end);
- clear lp lnprior ireal;
- end
- %
- h = waitbar(0,'Please wait...');
- istable=[1:Nsam];
- jstab=0;
- iunstable=[1:Nsam];
- iindeterm=zeros(1,Nsam);
- iwrong=zeros(1,Nsam);
- for j=1:Nsam,
- M_.params(estim_params_.param_vals(:,1)) = lpmat(j,:)';
- %try stoch_simul([]);
- try
- [Tt,Rr,SteadyState,info] = dynare_resolve(bayestopt_.restrict_var_list,...
- bayestopt_.restrict_columns,...
- bayestopt_.restrict_aux);
-
- if ~exist('T')
- T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),Nsam);
- end
- catch
- if isfield(oo_.dr,'eigval'),
- oo_.dr=rmfield(oo_.dr,'eigval');
- end
- if isfield(oo_.dr,'ghx'),
- oo_.dr=rmfield(oo_.dr,'ghx');
- end
- disp('No solution could be found'),
- end
- dr_ = oo_.dr;
- if isfield(dr_,'ghx'),
- egg(:,j) = sort(dr_.eigval);
- iunstable(j)=0;
- if prepSA
- jstab=jstab+1;
- T(:,:,jstab) = [dr_.ghx dr_.ghu];
- [A,B] = ghx2transition(squeeze(T(:,:,jstab)), ...
- bayestopt_.restrict_var_list, ...
- bayestopt_.restrict_columns, ...
- bayestopt_.restrict_aux);
- end
- if ~exist('nspred'),
- nspred = dr_.nspred; %size(dr_.ghx,2);
- nboth = dr_.nboth;
- nfwrd = dr_.nfwrd;
- end
- else
- istable(j)=0;
- if isfield(dr_,'eigval')
- egg(:,j) = sort(dr_.eigval);
- if exist('nspred')
- if any(isnan(egg(1:nspred,j)))
- iwrong(j)=j;
- else
- if (nboth | nfwrd) & abs(egg(nspred+1,j))<=options_.qz_criterium,
- iindeterm(j)=j;
- end
- end
- end
- else
- if exist('egg'),
- egg(:,j)=ones(size(egg,1),1).*NaN;
- end
- iwrong(j)=j;
- end
- end
- ys_=real(dr_.ys);
- yys(:,j) = ys_;
- ys_=yys(:,1);
- waitbar(j/Nsam,h,['MC iteration ',int2str(j),'/',int2str(Nsam)])
- end
- close(h)
- if prepSA,
- T=T(:,:,1:jstab);
- end
- istable=istable(find(istable)); % stable params
- iunstable=iunstable(find(iunstable)); % unstable params
- iindeterm=iindeterm(find(iindeterm)); % indeterminacy
- iwrong=iwrong(find(iwrong)); % dynare could not find solution
-
- % % map stable samples
- % istable=[1:Nsam];
- % for j=1:Nsam,
- % if any(isnan(egg(1:nspred,j)))
- % istable(j)=0;
- % else
- % if abs(egg(nspred,j))>=options_.qz_criterium; %(1-(options_.qz_criterium-1)); %1-1.e-5;
- % istable(j)=0;
- % %elseif (dr_.nboth | dr_.nfwrd) & abs(egg(nspred+1,j))<=options_.qz_criterium; %1+1.e-5;
- % elseif (nboth | nfwrd) & abs(egg(nspred+1,j))<=options_.qz_criterium; %1+1.e-5;
- % istable(j)=0;
- % end
- % end
- % end
- % istable=istable(find(istable)); % stable params
- %
- % % map unstable samples
- % iunstable=[1:Nsam];
- % for j=1:Nsam,
- % %if abs(egg(dr_.npred+1,j))>1+1.e-5 & abs(egg(dr_.npred,j))<1-1.e-5;
- % %if (dr_.nboth | dr_.nfwrd),
- % if ~any(isnan(egg(1:5,j)))
- % if (nboth | nfwrd),
- % if abs(egg(nspred+1,j))>options_.qz_criterium & abs(egg(nspred,j))<options_.qz_criterium; %(1-(options_.qz_criterium-1));
- % iunstable(j)=0;
- % end
- % else
- % if abs(egg(nspred,j))<options_.qz_criterium; %(1-(options_.qz_criterium-1));
- % iunstable(j)=0;
- % end
- % end
- % end
- % end
- % iunstable=iunstable(find(iunstable)); % unstable params
- bkpprior.pshape=bayestopt_.pshape;
- bkpprior.p1=bayestopt_.p1;
- bkpprior.p2=bayestopt_.p2;
- bkpprior.p3=bayestopt_.p3;
- bkpprior.p4=bayestopt_.p4;
- if pprior,
- if ~prepSA
- save([OutputDirectoryName '\' fname_ '_prior'], ...
- 'bkpprior','lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
- 'egg','yys','nspred','nboth','nfwrd')
- else
- save([OutputDirectoryName '\' fname_ '_prior'], ...
- 'bkpprior','lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
- 'egg','yys','T','nspred','nboth','nfwrd')
- end
-
- else
- if ~prepSA
- save([OutputDirectoryName '\' fname_ '_mc'], ...
- 'lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
- 'egg','yys','nspred','nboth','nfwrd')
- else
- save([OutputDirectoryName '\' fname_ '_mc'], ...
- 'lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
- 'egg','yys','T','nspred','nboth','nfwrd')
- end
- end
-else
- if pprior,
- filetoload=[OutputDirectoryName '\' fname_ '_prior'];
- else
- filetoload=[OutputDirectoryName '\' fname_ '_mc'];
- end
- load(filetoload,'lpmat','lpmat0','iunstable','istable','iindeterm','iwrong','egg','yys','nspred','nboth','nfwrd')
- Nsam = size(lpmat,1);
-
-
- if prepSA & isempty(strmatch('T',who('-file', filetoload),'exact')),
- h = waitbar(0,'Please wait...');
- options_.periods=0;
- options_.nomoments=1;
- options_.irf=0;
- options_.noprint=1;
- stoch_simul([]);
- %T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),length(istable));
- ntrans=length(istable);
- for j=1:ntrans,
- M_.params(estim_params_.param_vals(:,1)) = lpmat(istable(j),:)';
- %stoch_simul([]);
- [Tt,Rr,SteadyState,info] = dynare_resolve(bayestopt_.restrict_var_list,...
- bayestopt_.restrict_columns,...
- bayestopt_.restrict_aux);
- if ~exist('T')
- T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),ntrans);
- end
- dr_ = oo_.dr;
- T(:,:,j) = [dr_.ghx dr_.ghu];
- if ~exist('nspred')
- nspred = dr_.nspred; %size(dr_.ghx,2);
- nboth = dr_.nboth;
- nfwrd = dr_.nfwrd;
- end
- ys_=real(dr_.ys);
- yys(:,j) = ys_;
- ys_=yys(:,1);
- waitbar(j/ntrans,h,['MC iteration ',int2str(j),'/',int2str(ntrans)])
- end
- close(h)
- save(filetoload,'T','-append')
- elseif prepSA
- load(filetoload,'T')
- end
-end
-
-if pprior
- aname='prior_stab';
- auname='prior_unacceptable';
- aunstname='prior_unstable';
- aindname='prior_indeterm';
- asname='prior_stable';
-else
- aname='mc_stab';
- auname='mc_unacceptable';
- aunstname='mc_unstable';
- aindname='mc_indeterm';
- asname='mc_stable';
-end
-delete([OutputDirectoryName,'\',fname_,'_',aname,'_*.*']);
-%delete([OutputDirectoryName,'\',fname_,'_',aname,'_SA_*.*']);
-delete([OutputDirectoryName,'\',fname_,'_',asname,'_corr_*.*']);
-delete([OutputDirectoryName,'\',fname_,'_',auname,'_corr_*.*']);
-delete([OutputDirectoryName,'\',fname_,'_',aunstname,'_corr_*.*']);
-delete([OutputDirectoryName,'\',fname_,'_',aindname,'_corr_*.*']);
-
-if length(iunstable)>0 & length(iunstable)<Nsam,
- disp([num2str(length(istable)/Nsam*100,3),'\% of the prior support is stable.'])
- disp([num2str( (length(iunstable)-length(iwrong)-length(iindeterm) )/Nsam*100),'\% of the prior support is unstable.'])
- if ~isempty(iindeterm),
- disp([num2str(length(iindeterm)/Nsam*100,3),'\% of the prior support gives indeterminacy.'])
- end
- if ~isempty(iwrong),
- disp(' ');
- disp(['For ',num2str(length(iwrong)/Nsam*100,3),'\% of the prior support dynare could not find a solution.'])
- end
- disp(' ');
- % Blanchard Kahn
- [proba, dproba] = stab_map_1(lpmat, istable, iunstable, aname,0);
- indstab=find(dproba>ksstat);
- disp('Smirnov statistics in driving acceptable behaviour')
- for j=1:np,
- disp([M_.param_names(estim_params_.param_vals(j,1),:),' d-stat = ', num2str(dproba(j),3)])
- end
- disp(' ');
- if ~isempty(indstab)
- stab_map_1(lpmat, istable, iunstable, aname, 1, indstab, OutputDirectoryName);
- end
- ixun=iunstable(find(~ismember(iunstable,[iindeterm,iwrong])));
- if ~isempty(iindeterm),
- [proba, dproba] = stab_map_1(lpmat, [1:Nsam], iindeterm, [aname, '_indet'],0);
- indindet=find(dproba>ksstat);
- disp('Smirnov statistics in driving indeterminacy')
- for j=1:np,
- disp([M_.param_names(estim_params_.param_vals(j,1),:),' d-stat = ', num2str(dproba(j),3)])
- end
- disp(' ');
- if ~isempty(indindet)
- stab_map_1(lpmat, istable, iindeterm, [aname, '_indet'], 1, indindet, OutputDirectoryName);
- end
- end
-
- if ~isempty(ixun),
- [proba, dproba] = stab_map_1(lpmat, [1:Nsam], ixun, [aname, '_unst'],0);
- indunst=find(dproba>ksstat);
- disp('Smirnov statistics in driving instability')
- for j=1:np,
- disp([M_.param_names(estim_params_.param_vals(j,1),:),' d-stat = ', num2str(dproba(j),3)])
- end
- disp(' ');
- if ~isempty(indunst)
- stab_map_1(lpmat, istable, ixun, [aname, '_unst'], 1, indunst, OutputDirectoryName);
- end
- end
-
- disp(' ')
- disp('Starting bivariate analysis:')
-
- c0=corrcoef(lpmat(istable,:));
- c00=tril(c0,-1);
-
- stab_map_2(lpmat(istable,:),alpha2, asname, OutputDirectoryName);
- if length(iunstable)>3,
- stab_map_2(lpmat(iunstable,:),alpha2, auname, OutputDirectoryName);
- end
- if length(iindeterm)>3,
- stab_map_2(lpmat(iindeterm,:),alpha2, aindname, OutputDirectoryName);
- end
- if length(ixun)>3,
- stab_map_2(lpmat(ixun,:),alpha2, aunstname, OutputDirectoryName);
- end
-
- x0=0.5.*(bayestopt_.ub(1:nshock)-bayestopt_.lb(1:nshock))+bayestopt_.lb(1:nshock);
- x0 = [x0; lpmat(istable(1),:)'];
- if istable(end)~=Nsam
- M_.params(estim_params_.param_vals(:,1)) = lpmat(istable(1),:)';
- [oo_.dr, info] = resol(oo_.steady_state,0);
-% stoch_simul([]);
- end
-else
- if length(iunstable)==0,
- disp('All parameter values in the specified ranges are stable!')
- x0=0.5.*(bayestopt_.ub(1:nshock)-bayestopt_.lb(1:nshock))+bayestopt_.lb(1:nshock);
- x0 = [x0; lpmat(istable(1),:)'];
- else
- disp('All parameter values in the specified ranges are not acceptable!')
- x0=[];
- end
-
-end
-
-
-options_.periods=opt.periods;
-if isfield(opt,'nomoments'),
- options_.nomoments=opt.nomoments;
-end
-options_.irf=opt.irf;
-options_.noprint=opt.noprint;
-if isfield(opt,'simul'),
- options_.simul=opt.simul;
-end
-
-
-
diff --git a/GSA_distrib/4.0.3/stab_map_1.m b/GSA_distrib/4.0.3/stab_map_1.m
deleted file mode 100644
index 17aeaa794ac7b23df07092ecce5e3587640296bd..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/stab_map_1.m
+++ /dev/null
@@ -1,87 +0,0 @@
-function [proba, dproba] = stab_map_1(lpmat, ibehaviour, inonbehaviour, aname, iplot, ipar, dirname)
-%function [proba, dproba] = stab_map_1(lpmat, ibehaviour, inonbehaviour, aname, iplot, ipar, dirname)
-%
-% lpmat = Monte Carlo matrix
-% ibehaviour = index of behavioural runs
-% inonbehaviour = index of non-behavioural runs
-% aname = label of the analysis
-% iplot = 1 plot cumulative distributions (default)
-% iplot = 0 no plots
-% ipar = index array of parameters to plot
-% dirname = (OPTIONAL) path of the directory where to save
-% (default: current directory)
-%
-% Plots: dotted lines for BEHAVIOURAL
-% solid lines for NON BEHAVIOURAL
-% USES smirnov
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global estim_params_ bayestopt_ M_ options_
-
-if nargin<5,
- iplot=1;
-end
-fname_ = M_.fname;
-if nargin<7,
- dirname='';;
-end
-
-nshock = estim_params_.nvx;
-nshock = nshock + estim_params_.nvn;
-nshock = nshock + estim_params_.ncx;
-nshock = nshock + estim_params_.ncn;
-
-npar=size(lpmat,2);
-ishock= npar>estim_params_.np;
-
-if nargin<6 | isempty(ipar),
- ipar=[1:npar];
-end
-nparplot=length(ipar);
-
-% Smirnov test for Blanchard;
-for j=1:npar,
- [H,P,KSSTAT] = smirnov(lpmat(ibehaviour,j),lpmat(inonbehaviour,j));
- proba(j)=P;
- dproba(j)=KSSTAT;
-end
-if iplot
- lpmat=lpmat(:,ipar);
- ftit=bayestopt_.name(ipar+nshock*(1-ishock));
-
-for i=1:ceil(nparplot/12),
- figure('name',aname),
- for j=1+12*(i-1):min(nparplot,12*i),
- subplot(3,4,j-12*(i-1))
- if ~isempty(ibehaviour),
- h=cumplot(lpmat(ibehaviour,j));
- set(h,'color',[0 0 0], 'linestyle',':')
- end
- hold on,
- if ~isempty(inonbehaviour),
- h=cumplot(lpmat(inonbehaviour,j));
- set(h,'color',[0 0 0])
- end
- title([ftit{j},'. D-stat ', num2str(dproba(ipar(j)),2)],'interpreter','none')
- end
- saveas(gcf,[dirname,'\',fname_,'_',aname,'_SA_',int2str(i)])
- eval(['print -depsc2 ' dirname '\' fname_ '_' aname '_SA_' int2str(i)]);
- eval(['print -dpdf ' dirname '\' fname_ '_' aname '_SA_' int2str(i)]);
- if options_.nograph, close(gcf), end
-end
-end
diff --git a/GSA_distrib/4.0.3/stab_map_2.m b/GSA_distrib/4.0.3/stab_map_2.m
deleted file mode 100644
index 3941132a20d4c7169129eef225893c7871573831..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/stab_map_2.m
+++ /dev/null
@@ -1,97 +0,0 @@
-%function stab_map_2(x,alpha2,istab,fnam)
-function stab_map_2(x,alpha2,fnam, dirname)
-% function stab_map_2(x,alpha2,fnam, dirname)
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-%global bayestopt_ estim_params_ dr_ options_ ys_ fname_
-global bayestopt_ estim_params_ options_ oo_ M_
-
-npar=size(x,2);
-ishock= npar>estim_params_.np;
-if nargin<3,
- fnam='';
-end
-if nargin<4,
- dirname='';
-end
-
-ys_ = oo_.dr.ys;
-dr_ = oo_.dr;
-fname_ = M_.fname;
-nshock = estim_params_.nvx;
-nshock = nshock + estim_params_.nvn;
-nshock = nshock + estim_params_.ncx;
-nshock = nshock + estim_params_.ncn;
-
-c0=corrcoef(x);
-c00=tril(c0,-1);
-fig_nam_=[fname_,'_',fnam,'_corr_'];
-
-ifig=0;
-j2=0;
-if ishock==0
- npar=estim_params_.np;
-else
- npar=estim_params_.np+nshock;
-end
-for j=1:npar,
- i2=find(abs(c00(:,j))>alpha2);
- if length(i2)>0,
- for jx=1:length(i2),
- j2=j2+1;
- if mod(j2,12)==1,
- ifig=ifig+1;
- figure('name',['Correlations in the ',fnam,' sample ', num2str(ifig)]),
- end
- subplot(3,4,j2-(ifig-1)*12)
- % bar(c0(i2,j)),
- % set(gca,'xticklabel',bayestopt_.name(i2)),
- % set(gca,'xtick',[1:length(i2)])
- %plot(stock_par(ixx(nfilt+1:end,i),j),stock_par(ixx(nfilt+1:end,i),i2(jx)),'.k')
- %hold on,
- plot(x(:,j),x(:,i2(jx)),'.')
- % xlabel(deblank(estim_params_.param_names(j,:)),'interpreter','none'),
- % ylabel(deblank(estim_params_.param_names(i2(jx),:)),'interpreter','none'),
- if ishock,
- xlabel(bayestopt_.name{j},'interpreter','none'),
- ylabel(bayestopt_.name{i2(jx)},'interpreter','none'),
- else
- xlabel(bayestopt_.name{j+nshock},'interpreter','none'),
- ylabel(bayestopt_.name{i2(jx)+nshock},'interpreter','none'),
- end
- title(['cc = ',num2str(c0(i2(jx),j))])
- if (mod(j2,12)==0) & j2>0,
- saveas(gcf,[dirname,'\',fig_nam_,int2str(ifig)])
- eval(['print -depsc2 ' dirname '\' fig_nam_ int2str(ifig)]);
- eval(['print -dpdf ' dirname '\' fig_nam_ int2str(ifig)]);
- if options_.nograph, close(gcf), end
- end
- end
- end
- if (j==(npar)) & j2>0,
- saveas(gcf,[dirname,'\',fig_nam_,int2str(ifig)])
- eval(['print -depsc2 ' dirname '\' fig_nam_ int2str(ifig)]);
- eval(['print -dpdf ' dirname '\' fig_nam_ int2str(ifig)]);
- if options_.nograph, close(gcf), end
- end
-
-end
-if ifig==0,
- disp(['No correlation term >', num2str(alpha2),' found for ',fnam])
-end
-%close all
diff --git a/GSA_distrib/4.0.3/stand_.m b/GSA_distrib/4.0.3/stand_.m
deleted file mode 100644
index 2b19a740543e740776f1a962c5562bcb6b35c0d0..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/stand_.m
+++ /dev/null
@@ -1,25 +0,0 @@
-function [y, meany, stdy] = stand_(x)
-% STAND_ Standardise a matrix by columns
-%
-% [x,my,sy]=stand(y)
-%
-% y: Time series (column matrix)
-%
-% x: standardised equivalent of y
-% my: Vector of mean values for each column of y
-% sy: Vector of standard deviations for each column of y
-%
-% Copyright (c) 2006 by JRC, European Commission, United Kingdom
-% Author : Marco Ratto
-
-
-if nargin==0,
- return;
-end
-
-meany=mean(x);
-stdy=std(x);
-for j=1:size(x,2);
- y(:,j)=(x(:,j)-meany(j))./stdy(j);
-end
-% end of m-file
\ No newline at end of file
diff --git a/GSA_distrib/4.0.3/teff.m b/GSA_distrib/4.0.3/teff.m
deleted file mode 100644
index 57b1beb3e6e33507bbaaa17e523e14195f9d18fe..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/teff.m
+++ /dev/null
@@ -1,38 +0,0 @@
-function [yt, j0, ir, ic]=teff(T,Nsam,istable)
-%
-% [yt, j0, ir, ic]=teff(T,Nsam,istable)
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-if nargin==1,
- Nsam=size(T,3);
- istable = [1:Nsam]';
-end
-tmax=max(T,[],3);
-tmin=min(T,[],3);
-[ir, ic]=(find( (tmax-tmin)>1.e-8));
-j0 = length(ir);
-yt=zeros(Nsam, j0);
-
-for j=1:j0,
- y0=squeeze(T(ir(j),ic(j),:));
- %y1=ones(size(lpmat,1),1)*NaN;
- y1=ones(Nsam,1)*NaN;
- y1(istable,1)=y0;
- yt(:,j)=y1;
-end
-%clear y0 y1;
diff --git a/GSA_distrib/4.0.3/th_moments.m b/GSA_distrib/4.0.3/th_moments.m
deleted file mode 100644
index 1e7f3405ad90111efd6e9bf111d0946fad9abde0..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/th_moments.m
+++ /dev/null
@@ -1,56 +0,0 @@
-% Copyright (C) 2001 Michel Juillard
-%
-function [vdec, corr, autocorr, z, zz] = th_moments(dr,var_list)
- global M_ oo_ options_
-
- nvar = size(var_list,1);
- if nvar == 0
- nvar = length(dr.order_var);
- ivar = [1:nvar]';
- else
- ivar=zeros(nvar,1);
- for i=1:nvar
- i_tmp = strmatch(var_list(i,:),M_.endo_names,'exact');
- if isempty(i_tmp)
- error (['One of the variable specified does not exist']) ;
- else
- ivar(i) = i_tmp;
- end
- end
- end
-
- [gamma_y,ivar] = th_autocovariances(dr,ivar);
- m = dr.ys(ivar);
-
-
- i1 = find(abs(diag(gamma_y{1})) > 1e-12);
- s2 = diag(gamma_y{1});
- sd = sqrt(s2);
-
-
- z = [ m sd s2 ];
- mean = m;
- var = gamma_y{1};
-
-
-%'THEORETICAL MOMENTS';
-%'MEAN','STD. DEV.','VARIANCE');
-z;
-
-%'VARIANCE DECOMPOSITION (in percent)';
-
-vdec = 100*gamma_y{options_.ar+2}(i1,:);
-
-%'MATRIX OF CORRELATIONS';
- corr = gamma_y{1}(i1,i1)./(sd(i1)*sd(i1)');
-
- if options_.ar > 0
-%'COEFFICIENTS OF AUTOCORRELATION';
- for i=1:options_.ar
- autocorr{i} = gamma_y{i+1};
- zz(:,i) = diag(gamma_y{i+1}(i1,i1));
- end
- end
-
-
-
\ No newline at end of file
diff --git a/GSA_distrib/4.0.3/trank.m b/GSA_distrib/4.0.3/trank.m
deleted file mode 100644
index a0c5bda999a6eebdf4d1b1977f1c47240d4c111d..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.0.3/trank.m
+++ /dev/null
@@ -1,25 +0,0 @@
-function yr = trank(y);
-% yr = trank(y);
-% yr is the rank transformation of y
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-[nr, nc] = size(y);
-for j=1:nc,
- [dum, is]=sort(y(:,j));
- yr(is,j)=[1:nr]'./nr;
-end
diff --git a/GSA_distrib/4.1/GSA_manual.pdf b/GSA_distrib/4.1/GSA_manual.pdf
deleted file mode 100644
index 49c70a59207f99634f0d889f0bd9b91399fa2625..0000000000000000000000000000000000000000
Binary files a/GSA_distrib/4.1/GSA_manual.pdf and /dev/null differ
diff --git a/GSA_distrib/4.1/LPTAU.m b/GSA_distrib/4.1/LPTAU.m
deleted file mode 100644
index 7427de885c114d4e0cbed949322d62072bb92f34..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/LPTAU.m
+++ /dev/null
@@ -1,512 +0,0 @@
-function VECTOR = LPTAU(I, N)
-%
-% I.M. SOBOL', V.I. TURCHANINOV, Yu.L. LEVITAN, B.V. SHUKHMAN
-% KELDYSH INSTITUTE OF APPLIED MATHEMATICS
-% RUSSIAN ACADEMY OF SCIENCES
-%
-% QUASIRANDOM SEQUENCE GENERATORS
-% -------------------------------
-%
-% 28.11.1991
-%
-% NOTE TO THE USER BY the NEA Data Bank:
-% This quasi random number generator has been made available to
-% you on condition that its identity is preserved when used
-% in computer programs. If its use leads to scientific publication
-% of results you should cite it in the references, in addition
-% no commercial use should be made unless agreed upon with the
-% main author (Prof. I.M. Sobol')
-%
-% ABSTRACT
-% ........
-%
-% POINTS BELONGING TO LP-TAU SEQUENCES UNIFORMLY DISTRIBUTED IN THE
-% N-DIMENSIONAL UNIT CUBE ARE OFTEN USED IN NUMERICAL MATHEMATICS:
-%
-% - AS NODES FOR MULTIDIMENSIONAL INTEGRATION;
-% - AS SEARCHING POINTS IN GLOBAL OPTIMIZATION;
-% - AS TRIAL POINTS IN MULTI-CRITERIA DECISION MAKING;
-% - AS QUASIRANDOM POINTS FOR QUASI-MONTECARLO ALGORITHMS;
-% - ETC.
-%
-% THIS SUBROUTINE CONTAINS THE ALGORITHM FOR FAST GENERATION OF
-% LP-TAU SEQUENCES THAT ARE SUITABLE FOR MULTI-PROCESSOR COMPUTATIONS.
-% THE DIMENSIONS N.LE.51, THE NUMBER OF POINTS N.LT.2**30.
-% THE PROGRAMMING LANGUAGE IS FORTRAN-77. THIS SUBROUTINE IS AVAILABLE
-% ALSO IN %-LANGUAGE.
-% THE REPORT DESCRIBING THE ALGORITHM CONTAINS THE DESCRIPTION OF THE
-% ALGORITHM AND CERTAIN IMPORTANT PROPERTIES OF LP-TAU SEQUENCES AND
-% THEIR GENERALIZATIONS ARE DISCUSSED.
-%
-% REFERENCE:
-% I.M. SOBOL', V.I. TURCHANINOV, Yu.L. LEVITAN, B.V. SHUKHMAN
-% KELDYSH INSTITUTE OF APPLIED MATHEMATICS
-% RUSSIAN ACADEMY OF SCIENCES
-%
-% QUASIRANDOM SEQUENCE GENERATORS
-% MOSCOW 1992, IPM ZAK. NO.30 (100 COPIES)
-%
-% ------------------------------------------------------------------------
-%
-% INPUT PARAMETERS:
-%
-% I - NUMBER OF THE POINT (I=(0,2**30-1)),
-% N - DIMENSION OF THE POINT (0<N<52);
-%
-% OUTPUT PARAMETER:
-%
-% VECTOR(N) - N-VECTOR CONTAINING THE CARTESIAN CO-ORDINATES OF
-% THE I-TH POINT.
-%
-%
-% TO CALL THE SUBROUTINE WRITE:
-%
-% CALL LPTAU(I,N,VECTOR)
-% WHERE I, N: INTEGER CAPABLE OF STORING 2**30 (INTEGER*4 ON IBM
-% OR OTHER 32 BIT/WORD MACHINES)
-% VECTOR: DOUBLE PRECISION ARRAY WHOSE LENGTH < 52.
-%
-% INTEGER QP
-% QP = QUANTITY POWER
-%
-% PARAMETER (MAXDIM=51, QP=30, MAXNUM=2**30-1)
-MAXDIM=51; QP=30; MAXNUM=2^30-1;
-%
-% THE DIMENSION OF THE POINT CANNOT EXCEED MAXDIM
-% THE TOTAL NUMBER OF GENERATED POINTS CANNOT EXCEED 2**QP
-% MAXNUM=2**30-1 // 1073741823
-%
-% DOUBLE PRECISION VECTOR(N)
-% INTEGER I,N
-%
-% INTEGER PRVNUM,PRVDIM
-% INTEGER DIRECT(MAXDIM,QP), MASKV(MAXDIM)
-% DOUBLE PRECISION SCALE
-%
-% Translated into MATLAB by M. Ratto
-VECTOR=zeros(1,N);
-SCALE =9.31322574615478516E-10;
-
-persistent PRVNUM PRVDIM MASKV DIRECT
-if isempty(PRVNUM), PRVNUM=-2; end,
-if isempty(PRVDIM), PRVDIM=0; end,
-
-if isempty(DIRECT), ...
- DIRECT(1:MAXDIM,1)=[
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912]';
- DIRECT(1:MAXDIM,2)=[
- 805306368, 268435456, 805306368, 268435456, 805306368, ...
- 268435456, 805306368, 268435456, 268435456, 805306368, ...
- 268435456, 805306368, 268435456, 805306368, 268435456, ...
- 805306368, 805306368, 268435456, 805306368, 268435456, ...
- 805306368, 268435456, 805306368, 268435456, 268435456, ...
- 805306368, 268435456, 805306368, 268435456, 805306368, ...
- 268435456, 805306368, 805306368, 268435456, 805306368, ...
- 268435456, 805306368, 268435456, 805306368, 268435456, ...
- 268435456, 805306368, 268435456, 805306368, 268435456, ...
- 805306368, 268435456, 805306368, 805306368, 268435456, ...
- 805306368]';
- DIRECT(1:MAXDIM,3)=[
- 939524096, 939524096, 134217728, 671088640, 402653184, ...
- 402653184, 671088640, 134217728, 671088640, 402653184, ...
- 939524096, 134217728, 671088640, 939524096, 134217728, ...
- 671088640, 134217728, 939524096, 939524096, 402653184, ...
- 402653184, 134217728, 671088640, 402653184, 671088640, ...
- 402653184, 402653184, 671088640, 134217728, 134217728, ...
- 939524096, 939524096, 939524096, 939524096, 134217728, ...
- 671088640, 402653184, 402653184, 671088640, 134217728, ...
- 671088640, 402653184, 939524096, 134217728, 671088640, ...
- 939524096, 134217728, 671088640, 134217728, 939524096, ...
- 939524096]';
- DIRECT(1:MAXDIM,4)=[
- 1006632960, 67108864, 603979776, 1006632960, 335544320, ...
- 469762048, 872415232, 738197504, 469762048, 872415232, ...
- 1006632960, 67108864, 872415232, 469762048, 469762048, ...
- 469762048, 1006632960, 335544320, 872415232, 603979776, ...
- 201326592, 67108864, 335544320, 67108864, 201326592, ...
- 738197504, 1006632960, 738197504, 603979776, 335544320, ...
- 738197504, 67108864, 1006632960, 67108864, 603979776, ...
- 1006632960, 335544320, 469762048, 872415232, 738197504, ...
- 469762048, 872415232, 1006632960, 67108864, 872415232, ...
- 469762048, 469762048, 469762048, 1006632960, 335544320, ...
- 872415232]';
- DIRECT(1:MAXDIM,5)=[
- 1040187392, 637534208, 1040187392, 838860800, 167772160, ...
- 234881024, 167772160, 1040187392, 436207616, 33554432, ...
- 570425344, 1040187392, 503316480, 838860800, 973078528, ...
- 167772160, 234881024, 436207616, 771751936, 100663296, ...
- 234881024, 905969664, 771751936, 33554432, 838860800, ...
- 973078528, 905969664, 33554432, 301989888, 838860800, ...
- 100663296, 234881024, 1040187392, 637534208, 1040187392, ...
- 838860800, 167772160, 234881024, 167772160, 1040187392, ...
- 436207616, 33554432, 570425344, 1040187392, 503316480, ...
- 838860800, 973078528, 167772160, 234881024, 436207616, ...
- 771751936]';
- DIRECT(1:MAXDIM,6)=[
- 1056964608, 352321536, 50331648, 419430400, 956301312, ...
- 889192448, 620756992, 117440512, 956301312, 922746880, ...
- 822083584, 218103808, 587202560, 385875968, 452984832, ...
- 218103808, 184549376, 285212672, 150994944, 956301312, ...
- 352321536, 654311424, 553648128, 352321536, 788529152, ...
- 956301312, 587202560, 251658240, 218103808, 721420288, ...
- 251658240, 1056964608, 520093696, 889192448, 587202560, ...
- 956301312, 419430400, 352321536, 83886080, 654311424, ...
- 419430400, 385875968, 285212672, 754974720, 50331648, ...
- 922746880, 989855744, 754974720, 721420288, 822083584, ...
- 687865856]';
- DIRECT(1:MAXDIM,7)=[
- 1065353216, 1065353216, 578813952, 25165824, 125829120, ...
- 964689920, 327155712, 310378496, 360710144, 360710144, ...
- 159383552, 444596224, 947912704, 662700032, 444596224, ...
- 528482304, 578813952, 578813952, 75497472, 1065353216, ...
- 92274688, 511705088, 897581056, 847249408, 662700032, ...
- 931135488, 411041792, 713031680, 696254464, 528482304, ...
- 209715200, 578813952, 1065353216, 1065353216, 578813952, ...
- 25165824, 125829120, 964689920, 327155712, 310378496, ...
- 360710144, 360710144, 159383552, 444596224, 947912704, ...
- 662700032, 444596224, 528482304, 578813952, 578813952, ...
- 75497472]';
- DIRECT(1:MAXDIM,8)=[
- 1069547520, 4194304, 826277888, 624951296, 616562688, ...
- 801112064, 952107008, 406847488, 398458880, 331350016, ...
- 356515840, 46137344, 1010827264, 1069547520, 734003200, ...
- 113246208, 490733568, 633339904, 910163968, 801112064, ...
- 893386752, 851443712, 801112064, 918552576, 742391808, ...
- 499122176, 62914560, 264241152, 708837376, 717225984, ...
- 759169024, 499122176, 272629760, 423624704, 155189248, ...
- 239075328, 205520896, 943718400, 373293056, 457179136, ...
- 406847488, 71303168, 473956352, 54525952, 624951296, ...
- 104857600, 1019215872, 901775360, 213909504, 281018368, ...
- 851443712]';
- DIRECT(1:MAXDIM,9)=[
- 1071644672, 543162368, 190840832, 329252864, 853540864, ...
- 132120576, 778043392, 73400320, 178257920, 522190848, ...
- 639631360, 534773760, 991952896, 333447168, 48234496, ...
- 1059061760, 761266176, 673185792, 220200960, 396361728, ...
- 362807296, 815792128, 819986432, 346030080, 39845888, ...
- 752877568, 387973120, 643825664, 291504128, 274726912, ...
- 568328192, 526385152, 673185792, 98566144, 396361728, ...
- 727711744, 1042284544, 106954752, 299892736, 912261120, ...
- 44040192, 895483904, 333447168, 551550976, 467664896, ...
- 618659840, 606076928, 274726912, 245366784, 446693376, ...
- 421527552]';
- DIRECT(1:MAXDIM,10)=[
- 1072693248, 273678336, 644874240, 753926144, 495976448, ...
- 869269504, 355467264, 57671680, 816840704, 961544192, ...
- 804257792, 495976448, 347078656, 426770432, 1066401792, ...
- 372244480, 84934656, 208666624, 313524224, 598736896, ...
- 487587840, 965738496, 1011875840, 296747008, 393216000, ...
- 523239424, 720371712, 823132160, 128974848, 407896064, ...
- 747634688, 850395136, 873463808, 504365056, 481296384, ...
- 686817280, 592445440, 995098624, 498073600, 969932800, ...
- 586153984, 1039138816, 814743552, 523239424, 294649856, ...
- 305135616, 506462208, 11534336, 449839104, 619708416, ...
- 479199232]';
- DIRECT(1:MAXDIM,11)=[
- 1073217536, 947388416, 1070071808, 977797120, 365428736, ...
- 702021632, 461897728, 829947904, 425197568, 634912768, ...
- 437780480, 582483968, 792199168, 315097088, 611844096, ...
- 667418624, 166199296, 513277952, 187170816, 1036517376, ...
- 25690112, 201850880, 443023360, 990380032, 63438848, ...
- 211288064, 983040000, 1069023232, 421003264, 742916096, ...
- 487063552, 363331584, 973602816, 286785536, 171442176, ...
- 669515776, 110624768, 383254528, 289931264, 352845824, ...
- 878182400, 655884288, 836239360, 765984768, 549978112, ...
- 655884288, 85458944, 591921152, 563609600, 277348352, ...
- 919076864]';
- DIRECT(1:MAXDIM,12)=[
- 1073479680, 71565312, 2359296, 891551744, 158597120, ...
- 383516672, 1019478016, 947126272, 621019136, 714866688, ...
- 738459648, 265027584, 468975616, 131858432, 504627200, ...
- 581173248, 266600448, 865861632, 658243584, 546045952, ...
- 521404416, 304873472, 1060896768, 163840000, 305922048, ...
- 257163264, 50069504, 773062656, 59506688, 779354112, ...
- 165937152, 587988992, 486801408, 160694272, 90439680, ...
- 423362560, 536608768, 614203392, 56885248, 999030784, ...
- 10747904, 764674048, 25952256, 989069312, 352583680, ...
- 799801344, 261357568, 873201664, 40108032, 769392640, ...
- 254541824]';
- DIRECT(1:MAXDIM,13)=[
- 1073610752, 644218880, 538836992, 455475200, 1062600704, ...
- 139329536, 205651968, 905052160, 797048832, 452329472, ...
- 973471744, 627703808, 614072320, 803078144, 637403136, ...
- 835059712, 949878784, 662044672, 767950848, 426901504, ...
- 448659456, 23986176, 1016201216, 524943360, 525991936, ...
- 618790912, 781058048, 761659392, 458096640, 226361344, ...
- 950665216, 952500224, 516030464, 337510400, 496107520, ...
- 830865408, 944111616, 636354560, 978452480, 921567232, ...
- 533594112, 7471104, 678035456, 471203840, 1065746432, ...
- 575275008, 996540416, 909246464, 879362048, 637927424, ...
- 25821184]';
- DIRECT(1:MAXDIM,14)=[
- 1073676288, 357892096, 808648704, 2424832, 2555904, ...
- 624230400, 69271552, 456851456, 1052966912, 600637440, ...
- 487260160, 794624000, 386727936, 467599360, 798031872, ...
- 630652928, 340983808, 493944832, 37945344, 264175616, ...
- 263520256, 833421312, 235077632, 464846848, 534839296, ...
- 992411648, 10813440, 367067136, 116457472, 115015680, ...
- 928710656, 619773952, 813760512, 1043398656, 967770112, ...
- 912850944, 72155136, 1009057792, 668532736, 462356480, ...
- 267321344, 795803648, 635764736, 574160896, 1003421696, ...
- 181075968, 56688640, 388562944, 190906368, 657915904, ...
- 474939392]';
- DIRECT(1:MAXDIM,15)=[
- 1073709056, 1073709056, 137003008, 547782656, 545095680, ...
- 26836992, 34701312, 354385920, 925663232, 656965632, ...
- 327581696, 894795776, 110067712, 1038057472, 209354752, ...
- 596541440, 42631168, 471433216, 52527104, 666861568, ...
- 706707456, 674070528, 824410112, 305496064, 136282112, ...
- 847740928, 531464192, 222920704, 379289600, 507740160, ...
- 11894784, 1053392896, 129990656, 557547520, 666468352, ...
- 1061912576, 576684032, 1041334272, 380469248, 114196480, ...
- 133070848, 517046272, 129990656, 790396928, 563773440, ...
- 388333568, 661749760, 446791680, 737378304, 229998592, ...
- 348225536]';
- DIRECT(1:MAXDIM,16)=[
- 1073725440, 16384, 605372416, 275234816, 817971200, ...
- 603963392, 555335680, 721534976, 997801984, 1028767744, ...
- 407060480, 375275520, 256688128, 1021165568, 303349760, ...
- 1022476288, 234143744, 106708992, 732971008, 733954048, ...
- 789889024, 879575040, 764657664, 762658816, 1010843648, ...
- 941080576, 827932672, 98942976, 1051738112, 624934912, ...
- 993280000, 134070272, 201375744, 567558144, 882163712, ...
- 649084928, 356564992, 489439232, 637091840, 60637184, ...
- 199278592, 815677440, 927678464, 94519296, 419184640, ...
- 933838848, 426655744, 911130624, 171393024, 561332224, ...
- 471613440]';
- DIRECT(1:MAXDIM,17)=[
- 1073733632, 536895488, 1043685376, 679944192, 417505280, ...
- 301981696, 832561152, 210542592, 167501824, 1071341568, ...
- 229302272, 970661888, 732176384, 576659456, 402464768, ...
- 451584000, 368467968, 928260096, 933847040, 29319168, ...
- 582934528, 772612096, 330014720, 647323648, 174071808, ...
- 1008689152, 295919616, 353869824, 177774592, 580198400, ...
- 381837312, 638574592, 637558784, 679370752, 504012800, ...
- 747118592, 429973504, 1032609792, 932667392, 583360512, ...
- 969498624, 1056333824, 660955136, 247488512, 153509888, ...
- 242180096, 205840384, 797499392, 824565760, 234348544, ...
- 842326016]';
- DIRECT(1:MAXDIM,18)=[
- 1073737728, 268455936, 52785152, 1020628992, 345018368, ...
- 452972544, 704442368, 255987712, 750759936, 697692160, ...
- 196677632, 764604416, 485625856, 522022912, 680620032, ...
- 362270720, 838103040, 83972096, 629133312, 46108672, ...
- 867561472, 725422080, 184504320, 751112192, 191918080, ...
- 306425856, 507310080, 30453760, 281858048, 604000256, ...
- 208662528, 319557632, 318779392, 476139520, 863719424, ...
- 567062528, 521179136, 712790016, 610299904, 293687296, ...
- 1023086592, 549089280, 1065242624, 707751936, 363024384, ...
- 16674816, 197136384, 1037561856, 195112960, 372707328, ...
- 992751616]';
- DIRECT(1:MAXDIM,19)=[
- 1073739776, 939554816, 580732928, 854333440, 172619776, ...
- 511694848, 936142848, 518199296, 593348608, 225527808, ...
- 900982784, 180279296, 168904704, 62814208, 754485248, ...
- 730691584, 1005996032, 411174912, 249866240, 641669120, ...
- 1008719872, 749066240, 860993536, 94177280, 432564224, ...
- 226355200, 925784064, 995657728, 967731200, 436226048, ...
- 913799168, 549894144, 964696064, 843315200, 445863936, ...
- 1047422976, 548947968, 492066816, 953870336, 1002653696, ...
- 861440000, 385636352, 325253120, 187353088, 653584384, ...
- 1008269312, 748693504, 1013016576, 55814144, 255170560, ...
- 260708352]';
- DIRECT(1:MAXDIM,20)=[
- 1073740800, 67126272, 829514752, 423777280, 968297472, ...
- 205511680, 147076096, 926669824, 202300416, 118395904, ...
- 381332480, 1002738688, 743042048, 292551680, 584567808, ...
- 284339200, 183936000, 616762368, 435221504, 159376384, ...
- 907322368, 595696640, 247497728, 553735168, 826051584, ...
- 564454400, 446024704, 214236160, 33661952, 251685888, ...
- 660327424, 284244992, 859868160, 722502656, 622844928, ...
- 324342784, 682374144, 400579584, 405353472, 605187072, ...
- 840682496, 212956160, 157891584, 193201152, 437990400, ...
- 573578240, 368053248, 580197376, 937905152, 565527552, ...
- 89064448]';
- DIRECT(1:MAXDIM,21)=[
- 1073741312, 637560320, 189496832, 27474432, 129338880, ...
- 908054016, 641870336, 186375680, 302677504, 763663872, ...
- 103878144, 325187072, 858254848, 922041856, 261924352, ...
- 954978816, 292822528, 849512960, 210311680, 933232128, ...
- 691981824, 155417088, 627070464, 416795136, 182081024, ...
- 513433088, 848658944, 515770880, 627273216, 629169664, ...
- 414566912, 147450368, 698353152, 244844032, 226578944, ...
- 1020087808, 886978048, 389697024, 1007004160, 839646720, ...
- 621924864, 549962240, 609583616, 735976960, 87342592, ...
- 1058542080, 163066368, 307997184, 876471808, 794280448, ...
- 675386880]';
- DIRECT(1:MAXDIM,22)=[
- 1073741568, 352343296, 644236032, 636735232, 615860480, ...
- 959444224, 287380736, 1007410432, 890187008, 399480576, ...
- 520092928, 643311360, 816901376, 695310080, 1019229440, ...
- 77034240, 733295872, 1035127552, 986582784, 332381952, ...
- 334852352, 364956416, 596672256, 800381696, 480316672, ...
- 574863104, 647347968, 702910208, 499965184, 364968704, ...
- 120862976, 1023256320, 995114240, 13951232, 32520448, ...
- 702127360, 45176064, 444945664, 237860096, 152839936, ...
- 530633984, 429135616, 267272448, 884808960, 933712640, ...
- 61605632, 174335744, 564911360, 302327552, 650589440, ...
- 450649344]';
- DIRECT(1:MAXDIM,23)=[
- 1073741696, 1065385856, 1073734272, 331949184, 842310784, ...
- 799537536, 965852032, 369351808, 662886016, 86119808, ...
- 865109888, 299633792, 422735488, 181087360, 174252416, ...
- 1041212544, 840196224, 750314368, 391053440, 903306880, ...
- 742365312, 236995200, 42492800, 946000512, 771692416, ...
- 897405824, 613803136, 924258688, 808338304, 1038125440, ...
- 683814272, 177186176, 766008960, 704549248, 194555008, ...
- 306383744, 496592512, 416020864, 655186816, 1032204928, ...
- 694773632, 577910144, 45797760, 910332544, 536014976, ...
- 675946368, 987635840, 788223872, 353993856, 96313472, ...
- 85248640]';
- DIRECT(1:MAXDIM,24)=[
- 1073741760, 4210752, 12608, 744788544, 494377792, ...
- 115601344, 769248448, 990895808, 851706304, 979326784, ...
- 692061120, 429015104, 217132864, 736067008, 55694400, ...
- 456152640, 631601984, 787264192, 898599104, 478383808, ...
- 507774272, 458270272, 392995136, 872482496, 124824768, ...
- 1034161344, 362141632, 1053833280, 943810496, 428920128, ...
- 795835200, 835462848, 961843520, 606198080, 785652672, ...
- 154954432, 491617344, 297351232, 580735552, 634587968, ...
- 185277760, 141505600, 417673280, 106907456, 395575616, ...
- 566958656, 352651200, 415242688, 26635200, 1030317504, ...
- 247212992]';
- DIRECT(1:MAXDIM,25)=[
- 1073741792, 543187040, 536882016, 981766752, 357858144, ...
- 810665952, 369083488, 613015520, 86115232, 845149216, ...
- 606076960, 1018241504, 35245536, 635403744, 236633696, ...
- 407451232, 427671904, 460141792, 116344544, 990246688, ...
- 1024892576, 883429408, 150655392, 173476896, 197666464, ...
- 1016740448, 605376608, 970487008, 1006881248, 598265632, ...
- 1022861728, 489055392, 216680608, 371439072, 53140576, ...
- 965114400, 98534112, 209692256, 264598496, 321437280, ...
- 545303840, 324119904, 876587488, 778239712, 802033120, ...
- 44406496, 665829024, 803213920, 309742112, 735181344, ...
- 1036125600]';
- DIRECT(1:MAXDIM,26)=[
- 1073741808, 273698896, 805312112, 903123536, 153504624, ...
- 689632208, 432848944, 859888752, 510853776, 240805744, ...
- 250610192, 852489168, 139460144, 283082224, 222702928, ...
- 342181488, 922872432, 187528656, 360637424, 814514736, ...
- 301037840, 800872624, 272595184, 158627600, 238839088, ...
- 927181136, 710248688, 788854608, 1048376560, 484709072, ...
- 85709008, 1065469744, 429237328, 490778384, 848024144, ...
- 443114288, 687907504, 474573648, 45706416, 681465296, ...
- 805303216, 14567920, 369839504, 440402480, 797652624, ...
- 115959088, 929784560, 91226544, 205943056, 288358704, ...
- 950217296]';
- DIRECT(1:MAXDIM,27)=[
- 1073741816, 947419256, 134232008, 460100200, 1073685336, ...
- 398354904, 1069834248, 686054696, 108299224, 273898840, ...
- 731382552, 938170664, 86812552, 677346808, 602208712, ...
- 652635752, 209797064, 323968376, 384078968, 561178056, ...
- 923399256, 996597176, 942777416, 885167400, 89791048, ...
- 956122504, 87393464, 987661336, 993412952, 827749496, ...
- 903211272, 33649816, 594875176, 65052056, 822835240, ...
- 625704888, 1065374584, 612232920, 536299720, 1046858504, ...
- 939518840, 160843032, 654656088, 744496936, 872197704, ...
- 219111576, 829112632, 455614152, 1064192952, 313010856, ...
- 820754920]';
- DIRECT(1:MAXDIM,28)=[
- 1073741820, 71582788, 603989028, 37500, 120660, ...
- 182195932, 213921796, 473570692, 41763004, 156352828, ...
- 88343188, 698012780, 666108868, 337608156, 1054329884, ...
- 799472220, 641885244, 392104980, 502284340, 1002405628, ...
- 249907140, 75586228, 206587660, 565275348, 1021426548, ...
- 425987996, 598058580, 401940420, 919427316, 822049324, ...
- 115655868, 759299588, 562394644, 990942164, 1003212268, ...
- 598750292, 675334852, 675293340, 445665316, 903023756, ...
- 872412692, 172640916, 1051615436, 91229620, 94586692, ...
- 344873452, 7029156, 683421900, 434258804, 955002092, ...
- 436424380]';
- DIRECT(1:MAXDIM,29)=[
- 1073741822, 644245094, 1040195102, 537039474, 537089354, ...
- 642656334, 73402402, 664239174, 1014620426, 500917234, ...
- 1042677826, 347788318, 1069154738, 373259762, 362587674, ...
- 239395914, 132283950, 903121466, 445210638, 968851198, ...
- 230153254, 935549622, 308815630, 861891286, 496995094, ...
- 670740382, 657311830, 573565382, 248331478, 1064650798, ...
- 338312798, 669059078, 1065190902, 379125622, 111897166, ...
- 520650422, 740300390, 1046483950, 66254898, 992513134, ...
- 234871606, 610553330, 450553866, 566758134, 787800806, ...
- 1071709866, 971732606, 528102354, 790919122, 917384366, ...
- 656244162]';
- DIRECT(1:MAXDIM,30)=[
- 1073741823, 357913941, 50344755, 268538457, 805540473, ...
- 3487029, 3146769, 592038967, 729591963, 781578389, ...
- 66781679, 113956361, 331153483, 967802327, 935343371, ...
- 324351309, 609305915, 818137857, 131059769, 918519549, ...
- 827341719, 922770101, 456972047, 363883221, 1057014661, ...
- 900956063, 580478293, 520383687, 315470533, 227601711, ...
- 169598765, 909227271, 796983815, 349496709, 393974911, ...
- 378320037, 777004343, 927999269, 616377385, 345930959, ...
- 989849787, 627400495, 892675125, 260314121, 1041964063, ...
- 531367163, 195776757, 237309785, 949187605, 719002587, ...
- 495745187]';
-end
-
-%
-% TRAP FOR A WRONG SUBROUTINE CALL
-%
-if ((I<0) | (N<1) | (I>MAXNUM) | (N>MAXDIM)),
- disp('LP-TAU CALL FAILED')
- disp(' PRESS <ENTER> TO EXIT LPTAU')
- pause
- return
-end
-if ((PRVNUM+1==I) & (N<=PRVDIM)),
- %
- % RECURRENT GENERATION OF THE POINT
- %
- %
- % SEARCH POSITION OF THE RIGHTMOST "1"
- % IN THE BINARY REPRESENTATION OF I
- %
- L=0;
- POS=0;
- while L<QP & POS==0,
- L=L+1;
- POS=bitand(bitshift(I,-(L-1)),1);
- end
- %
- % RIGHTMOST POSITION IS L
- %
- for J=1:N
- MASKV(J)=bitxor(MASKV(J),DIRECT(J,L));
- VECTOR(J)=MASKV(J)*SCALE;
- end
-else
- %
- % GENERATION OF THE POINT FROM "I" AND "N"
- %
- MASKV=zeros(1,N);
- IM=bitxor(I,bitshift(I,-1));
- M=0;
- while IM~=0 & M<QP,
- M=M+1;
- if (bitand(IM,1)==1),
- for J=1:N
- MASKV(J)=bitxor(MASKV(J),DIRECT(J,M));
- end
- end
- IM=bitshift(IM,-1);
- end
- for J=1:N
- VECTOR(J)=MASKV(J)*SCALE;
- end
-end
-%
-PRVNUM=I;
-PRVDIM=N;
-return
-
-
diff --git a/GSA_distrib/4.1/Morris_Measure_Groups.m b/GSA_distrib/4.1/Morris_Measure_Groups.m
deleted file mode 100644
index c5a71b057a3d8029f6abdf621f82816465b7f4be..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/Morris_Measure_Groups.m
+++ /dev/null
@@ -1,130 +0,0 @@
-
-function [SAmeas, OutMatrix] = Morris_Measure_Groups(NumFact, Sample, Output, p, Group)
-
-% [SAmeas, OutMatrix] = Morris_Measure_Groups(NumFact, Sample, Output, p, Group)
-%
-% Given the Morris sample matrix, the output values and the group matrix compute the Morris measures
-% -------------------------------------------------------------------------
-% INPUTS
-% -------------------------------------------------------------------------
-% Group [NumFactor, NumGroups] := Matrix describing the groups.
-% Each column represents one group.
-% The element of each column are zero if the factor is not in the
-% group. Otherwise it is 1.
-
-% Sample := Matrix of the Morris sampled trajectories
-
-% Output := Matrix of the output(s) values in correspondence of each point
-% of each trajectory
-
-% k = Number of factors
-% -------------------------------------------------------------------------
-% OUTPUTS
-% OutMatrix (NumFactor*NumOutputs, 3)= [Mu*, Mu, StDev]
-% for each output it gives the three measures of each factor
-% -------------------------------------------------------------------------
-
-if nargin==0,
- disp(' ')
- disp('[SAmeas, OutMatrix] = Morris_Measure_Groups(NumFact, Sample, Output, p, Group);')
- return
-end
-
-OutMatrix=[];
-if nargin < 5, Group=[]; end
-
-NumGroups = size(Group,2);
-if nargin < 4 | isempty(p),
- p = 4;
-end
-Delt = p/(2*p-2);
-
-if NumGroups ~ 0
- sizea = NumGroups; % Number of groups
- GroupMat=Group;
- GroupMat = GroupMat';
-else
- sizea = NumFact;
-end
-r=size(Sample,1)/(sizea+1); % Number of trajectories
-
-% For Each Output
-for k=1:size(Output,2)
-
- OutValues=Output(:,k);
-
- % For each r trajectory
- for i=1:r
-
- % For each step j in the trajectory
- % Read the orientation matrix fact for the r-th sampling
- % Read the corresponding output values
- Single_Sample = Sample(i+(i-1)*sizea:i+(i-1)*sizea+sizea,:);
- Single_OutValues = OutValues(i+(i-1)*sizea:i+(i-1)*sizea+sizea,:);
- A = (Single_Sample(2:sizea+1,:)-Single_Sample(1:sizea,:))';
- Delta = A(find(A));
-
- % For each point of the fixed trajectory compute the values of the Morris function. The function
- % is partitioned in four parts, from order zero to order 4th.
- for j=1:sizea % For each point in the trajectory i.e for each factor
- % matrix of factor which changes
- if NumGroups ~ 0;
- AuxFind (:,1) = A(:,j);
-% AuxFind(find(A(:,j)),1)=1;
-% Pippo = sum((Group - repmat(AuxFind,1,NumGroups)),1);
-% Change_factor(j,i) = find(Pippo==0);
- Change_factor = find(abs(AuxFind)>1e-010);
- % If we deal with groups we can only estimate the new mu*
- % measure since factors in the same groups can move in
- % opposite direction and the definition of the standard
- % Morris mu cannopt be applied.
- % In the new version the elementary effect is defined with
- % the absolute value.
- %SAmeas(find(GroupMat(Change_factor(j,i),:)),i) = abs((Single_OutValues(j) - Single_OutValues(j+1) )/Delt); %(2/3));
- SAmeas(i,Change_factor') = abs((Single_OutValues(j) - Single_OutValues(j+1) )/Delt);
- else
- Change_factor(j,i) = find(Single_Sample(j+1,:)-Single_Sample(j,:));
- % If no groups --> we compute both the original and
- % modified measure
- if Delta(j) > 0 %=> +Delta
- SAmeas(Change_factor(j,i),i) = (Single_OutValues(j+1) - Single_OutValues(j) )/Delt; %(2/3);
- else %=> -Delta
- SAmeas(Change_factor(j,i),i) = (Single_OutValues(j) - Single_OutValues(j+1) )/Delt; %(2/3);
- end
- end
- end %for j=1:sizea
-
- end %for i=1:r
-
- if NumGroups ~ 0
- SAmeas = SAmeas';
- end
-
- % Compute Mu AbsMu and StDev
- if any(any(isnan(SAmeas)))
- for j=1:NumFact,
- SAm = SAmeas(j,:);
- SAm = SAm(find(~isnan(SAm)));
- rr=length(SAm);
- AbsMu(j,1) = sum(abs(SAm),2)/rr;
- if NumGroups == 0
- Mu(j,1) = sum(SAm,2)/rr;
- StDev(j,1) = sum((SAm - repmat(Mu(j),1,rr)).^2/(rr*(rr-1)),2).^0.5;
- end
- end
- else
- AbsMu = sum(abs(SAmeas),2)/r;
- if NumGroups == 0
- Mu = sum(SAmeas,2)/r;
- StDev = sum((SAmeas - repmat(Mu,1,r)).^2/(r*(r-1)),2).^0.5;
- end
- end
-
- % Define the output Matrix - if we have groups we cannot define the old
- % measure mu, only mu* makes sense
- if NumGroups > 0
- OutMatrix = [OutMatrix; AbsMu];
- else
- OutMatrix = [OutMatrix; AbsMu, Mu, StDev];
- end
-end % For Each Output
diff --git a/GSA_distrib/4.1/Sampling_Function_2.m b/GSA_distrib/4.1/Sampling_Function_2.m
deleted file mode 100644
index ccd3a87f91051686bea0d3a406e751223b076ca6..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/Sampling_Function_2.m
+++ /dev/null
@@ -1,174 +0,0 @@
-function [Outmatrix, OutFact] = Sampling_Function_2(p, k, r, UB, LB, GroupMat)
-%[Outmatrix, OutFact] = Sampling_Function_2(p, k, r, UB, LB, GroupMat)
-% Inputs: k (1,1) := number of factors examined or number of groups examined.
-% In case the groups are chosen the number of factors is stores in NumFact and
-% sizea becomes the number of created groups.
-% NumFact (1,1) := number of factors examined in the case when groups are chosen
-% r (1,1) := sample size
-% p (1,1) := number of intervals considered in [0, 1]
-% UB(sizea,1) := Upper Bound for each factor
-% LB(sizea,1) := Lower Bound for each factor
-% GroupNumber(1,1) := Number of groups (eventually 0)
-% GroupMat(NumFact,GroupNumber):= Matrix which describes the chosen groups. Each column represents a group and its elements
-% are set to 1 in correspondence of the factors that belong to the fixed group. All
-% the other elements are zero.
-% Local Variables:
-% sizeb (1,1) := sizea+1
-% sizec (1,1) := 1
-% randmult (sizea,1) := vector of random +1 and -1
-% perm_e(1,sizea) := vector of sizea random permutated indeces
-% fact(sizea) := vector containing the factor varied within each traj
-% DDo(sizea,sizea) := D* in Morris, 1991
-% A(sizeb,sizea) := Jk+1,k in Morris, 1991
-% B(sizeb,sizea) := B in Morris, 1991
-% Po(sizea,sizea) := P* in Morris, 1991
-% Bo(sizeb,sizea) := B* in Morris, 1991
-% Ao(sizeb,sizec) := Jk+1,1 in Morris, 1991
-% xo(sizec,sizea) := x* in Morris, 1991 (starting point for the trajectory)
-% In(sizeb,sizea) := for each loop orientation matrix. It corresponds to a trajectory
-% of k step in the parameter space and it provides a single elementary
-% effect per factor
-% MyInt()
-% Fact(sizea,1) := for each loop vector indicating which factor or group of factors has been changed
-% in each step of the trajectory
-% AuxMat(sizeb,sizea) := Delta*0.5*((2*B - A) * DD0 + A) in Morris, 1991. The AuxMat is used as in Morris design
-% for single factor analysis, while it constitutes an intermediate step for the group analysis.
-%
-% Output: Outmatrix(sizeb*r, sizea) := for the entire sample size computed In(i,j) matrices
-% OutFact(sizea*r,1) := for the entire sample size computed Fact(i,1) vectors
-%
-% Note: B0 is constructed as in Morris design when groups are not considered. When groups are considered the routine
-% follows the following steps:
-% 1- Creation of P0 and DD0 matrices defined in Morris for the groups. This means that the dimensions of these
-% 2 matrices are (GroupNumber,GroupNumber).
-% 2- Creation of AuxMat matrix with (GroupNumber+1,GroupNumber) elements.
-% 3- Definition of GroupB0 starting from AuxMat, GroupMat and P0.
-% 4- The final B0 for groups is obtained as [ones(sizeb,1)*x0' + GroupB0]. The P0 permutation is present in GroupB0
-% and it's not necessary to permute the matrix (ones(sizeb,1)*x0') because it's already randomly created.
-% Reference:
-% A. Saltelli, K. Chan, E.M. Scott, "Sensitivity Analysis" on page 68 ss
-%
-% F. Campolongo, J. Cariboni, JRC - IPSC Ispra, Varese, IT
-% Last Update: 15 November 2005 by J.Cariboni
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-
-% Parameters and initialisation of the output matrix
-sizea = k;
-Delta = p/(2*p-2);
-%Delta = 1/3
-NumFact = sizea;
-GroupNumber = size(GroupMat,2);
-
-if GroupNumber ~ 0;
- sizea = size(GroupMat,2);
-end
-
-sizeb = sizea + 1;
-sizec = 1;
-Outmatrix = [];
-OutFact = [];
-
-% For each i generate a trajectory
-for i=1:r
-
- % Construct DD0 - OLD VERSION - it does not need communication toolbox
- % RAND(N,M) is an NXM matrix with random entries, chosen from a uniform distribution on the interval (0.0,1.0).
- % Note that DD0 tells if the factor have to be increased or ddecreased
- % by Delta.
- randmult = ones(k,1);
- v = rand(k,1);
- randmult (find(v < 0.5))=-1;
- randmult = repmat(randmult,1,k);
- DD0 = randmult .* eye(k);
-
- % Construct DD0 - NEW VERSION - it needs communication toolbox
- % randsrc(m) generates an m-by-m matrix, each of whose entries independently takes the value -1 with probability 1/2,
- % and 1 with probability 1/2.
- % DD0 = randsrc(NumFact) .* eye(NumFact);
-
- % Construct B (lower triangular)
- B = ones(sizeb,sizea);
- for j = 1:sizea
- B(1:j,j)=0;
- end
-
- % Construct A0, A
- A0 = ones(sizeb,1);
- A = ones(sizeb,NumFact);
-
- % Construct the permutation matrix P0. In each column of P0 one randomly chosen element equals 1
- % while all the others equal zero.
- % P0 tells the order in which order factors are changed in each
- % trajectory. P0 is created as it follows:
- % 1) All the elements of P0 are set equal to zero ==> P0 = zeros (sizea, sizea);
- % 2) The function randperm create a random permutation of integer 1:sizea, without repetitions ==> perm_e;
- % 3) In each column of P0 the element indicated in perm_e is set equal to one.
- % Note that P0 is then used reading it by rows.
- P0 = zeros (sizea, sizea);
- perm_e = randperm(sizea); % RANDPERM(n) is a random permutation of the integers from 1 to n.
- for j = 1:sizea
- P0(perm_e(j),j) = 1;
- end
-
- % When groups are present the random permutation is done only on B. The effect is the same since
- % the added part (A0*x0') is completely random.
- if GroupNumber ~ 0
- B = B * (GroupMat*P0')';
- end
-
- % Compute AuxMat both for single factors and groups analysis. For Single factors analysis
- % AuxMat is added to (A0*X0) and then permutated through P0. When groups are active AuxMat is
- % used to build GroupB0. AuxMat is created considering DD0. If the element on DD0 diagonal
- % is 1 then AuxMat will start with zero and add Delta. If the element on DD0 diagonal is -1
- % then DD0 will start Delta and goes to zero.
- AuxMat = Delta*0.5*((2*B - A) * DD0 + A);
-
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
- % a --> Define the random vector x0 for the factors. Note that x0 takes value in the hypercube
- % [0,...,1-Delta]*[0,...,1-Delta]*[0,...,1-Delta]*[0,...,1-Delta]
- MyInt = repmat([0:(1/(p-1)):(1-Delta)],NumFact,1); % Construct all possible values of the factors
-
- % OLD VERSION - it needs communication toolbox
- % w = randint(NumFact,1,[1,size(MyInt,2)]);
-
- % NEW VERSION - construct a version of random integers
- % 1) create a vector of random integers
- % 2) divide [0,1] into the needed steps
- % 3) check in which interval the random numbers fall
- % 4) generate the corresponding integer
- v = repmat(rand(NumFact,1),1,size(MyInt,2)+1); % 1)
- IntUsed = repmat([0:1/size(MyInt,2):1],NumFact,1); % 2)
- DiffAuxVec = IntUsed - v; % 3)
-
- for ii = 1:size(DiffAuxVec,1)
- w(1,ii) = max(find(DiffAuxVec(ii,:)<0)); % 4)
- end
- x0 = MyInt(1,w)'; % Define x0
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
- % b --> Compute the matrix B*, here indicated as B0. Each row in B0 is a
- % trajectory for Morris Calculations. The dimension of B0 is (Numfactors+1,Numfactors)
- if GroupNumber ~ 0
- B0 = (A0*x0' + AuxMat);
- else
- B0 = (A0*x0' + AuxMat)*P0;
- end
-
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
- % c --> Compute values in the original intervals
- % B0 has values x(i,j) in [0, 1/(p -1), 2/(p -1), ... , 1].
- % To obtain values in the original intervals [LB, UB] we compute
- % LB(j) + x(i,j)*(UB(j)-LB(j))
- In = repmat(LB,1,sizeb)' + B0 .* repmat((UB-LB),1,sizeb)';
-
- % Create the Factor vector. Each component of this vector indicate which factor or group of factor
- % has been changed in each step of the trajectory.
- for j=1:sizea
- Fact(1,j) = find(P0(j,:));
- end
- Fact(1,sizea+1) = 0;
-
- Outmatrix = [Outmatrix; In];
- OutFact = [OutFact; Fact'];
-
-end
\ No newline at end of file
diff --git a/GSA_distrib/4.1/beta_inv.m b/GSA_distrib/4.1/beta_inv.m
deleted file mode 100644
index d3c95836dd060c5dbcdc1f300131576955360dfb..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/beta_inv.m
+++ /dev/null
@@ -1,38 +0,0 @@
-function x = beta_inv(p, a, b)
-% PURPOSE: inverse of the cdf (quantile) of the beta(a,b) distribution
-%--------------------------------------------------------------
-% USAGE: x = beta_inv(p,a,b)
-% where: p = vector of probabilities
-% a = beta distribution parameter, a = scalar
-% b = beta distribution parameter b = scalar
-% NOTE: mean [beta(a,b)] = a/(a+b), variance = ab/((a+b)*(a+b)*(a+b+1))
-%--------------------------------------------------------------
-% RETURNS: x at each element of p for the beta(a,b) distribution
-%--------------------------------------------------------------
-% SEE ALSO: beta_d, beta_pdf, beta_inv, beta_rnd
-%--------------------------------------------------------------
-
-% Anders Holtsberg, 18-11-93
-% Copyright (c) Anders Holtsberg
-% documentation modified by LeSage to
-% match the format of the econometrics toolbox
-
-if (nargin ~= 3)
- error('Wrong # of arguments to beta_inv');
-end
-
-if any(any((a<=0)|(b<=0)))
- error('beta_inv parameter a or b is nonpositive');
-end
-if any(any(abs(2*p-1)>1))
- error('beta_inv: A probability should be 0<=p<=1');
-end
-
-x = a ./ (a+b);
-dx = 1;
-while any(any(abs(dx)>256*eps*max(x,1)))
- dx = (betainc(x,a,b) - p) ./ beta_pdf(x,a,b);
- x = x - dx;
- x = x + (dx - x) / 2 .* (x<0);
-end
-
\ No newline at end of file
diff --git a/GSA_distrib/4.1/beta_pdf.m b/GSA_distrib/4.1/beta_pdf.m
deleted file mode 100644
index 8412fbdce51af35e893bcb501b60230e49e3e1b0..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/beta_pdf.m
+++ /dev/null
@@ -1,32 +0,0 @@
-function pdf = beta_pdf(x, a, b)
-% PURPOSE: pdf of the beta(a,b) distribution
-%--------------------------------------------------------------
-% USAGE: pdf = beta_pdf(x,a,b)
-% where: x = vector of components
-% a = beta distribution parameter, a = scalar
-% b = beta distribution parameter b = scalar
-% NOTE: mean[(beta(a,b)] = a/(a+b), variance = ab/((a+b)*(a+b)*(a+b+1))
-%--------------------------------------------------------------
-% RETURNS: pdf at each element of x of the beta(a,b) distribution
-%--------------------------------------------------------------
-% SEE ALSO: beta_d, beta_pdf, beta_inv, beta_rnd
-%--------------------------------------------------------------
-
-% Anders Holtsberg, 18-11-93
-% Copyright (c) Anders Holtsberg
-% documentation modified by LeSage to
-% match the format of the econometrics toolbox
-
-
-if (nargin ~=3)
- error('Wrong # of arguments to beta_pdf');
-end
-
-if any(any((a<=0)|(b<=0)))
- error('Parameter a or b is nonpositive');
-end
-
-I = find((x<0)|(x>1));
-
-pdf = x.^(a-1) .* (1-x).^(b-1) ./ beta(a,b);
-pdf(I) = 0*I;
diff --git a/GSA_distrib/4.1/cumplot.m b/GSA_distrib/4.1/cumplot.m
deleted file mode 100644
index a700d37842a1c4ddb3a9adb34a4780c90e5b5685..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/cumplot.m
+++ /dev/null
@@ -1,14 +0,0 @@
-function h = cumplot(x);
-%function h =cumplot(x)
-% Copyright (C) 2005 Marco Ratto
-
-
-n=length(x);
-x=[-inf; sort(x); Inf];
-y=[0:n n]./n;
-h0 = stairs(x,y);
-grid on,
-
-if nargout,
- h=h0;
-end
diff --git a/GSA_distrib/4.1/dat_fil_.m b/GSA_distrib/4.1/dat_fil_.m
deleted file mode 100644
index 0b3ac8f8e7499ca8f48b610df9a04c2fdcfe48c1..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/dat_fil_.m
+++ /dev/null
@@ -1,30 +0,0 @@
-function c = dat_fil_(data_file);
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-try
- eval(data_file);
-catch
- load(data_file);
-end
-clear data_file;
-
-a=who;
-
-for j=1:length(a)
- eval(['c.',a{j},'=',a{j},';']);
-end
\ No newline at end of file
diff --git a/GSA_distrib/4.1/dynare_MC.m b/GSA_distrib/4.1/dynare_MC.m
deleted file mode 100644
index 05c83da2ed43da201ac0f5c8860d45f549fa9459..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/dynare_MC.m
+++ /dev/null
@@ -1,149 +0,0 @@
-function dynare_MC(var_list_,OutDir)
-%
-% Adapted by M. Ratto from dynare_estimation.m and posteriorsmoother.m
-% (dynare_estimation.m and posteriorsmoother.m are part of DYNARE,
-% copyright M. Juillard)
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global M_ options_ oo_ estim_params_
-global bayestopt_
-
-% if options_.filtered_vars ~= 0 & options_.filter_step_ahead == 0
-% options_.filter_step_ahead = 1;
-% end
-% if options_.filter_step_ahead ~= 0
-% options_.nk = max(options_.filter_step_ahead);
-% else
-% options_.nk = 0;
-% end
-%
-options_.filter_step_ahead=1;
-options_.nk = 1;
-
-
-
-nvx = estim_params_.nvx;
-nvn = estim_params_.nvn;
-ncx = estim_params_.ncx;
-ncn = estim_params_.ncn;
-np = estim_params_.np ;
-npar = nvx+nvn+ncx+ncn+np;
-
-if isempty(options_.datafile)
- error('ESTIMATION: datafile option is missing')
-end
-
-if isempty(options_.varobs)
- error('ESTIMATION: VAROBS is missing')
-end
-
-%% Read and demean data
-rawdata = read_variables(options_.datafile,options_.varobs,[],options_.xls_sheet,options_.xls_range);
-
-options_ = set_default_option(options_,'nobs',size(rawdata,1)-options_.first_obs+1);
-gend = options_.nobs;
-n_varobs = size(options_.varobs,1);
-
-rawdata = rawdata(options_.first_obs:options_.first_obs+gend-1,:);
-if options_.loglinear == 1 & ~options_.logdata
- rawdata = log(rawdata);
-end
-if options_.prefilter == 1
- bayestopt_.mean_varobs = mean(rawdata,1);
- data = transpose(rawdata-ones(gend,1)*bayestopt_.mean_varobs);
-else
- data = transpose(rawdata);
-end
-[data_index,number_of_observations,no_more_missing_observations] = describe_missing_data(data,gend,n_varobs);
-
-if ~isreal(rawdata)
- error(['There are complex values in the data. Probably a wrong' ...
- ' transformation'])
-end
-
-offset = npar-np;
-fname_=M_.fname;
-
-options_ = set_default_option(options_,'opt_gsa',1);
-options_gsa_ = options_.opt_gsa;
-
-if options_gsa_.pprior,
- namfile=[fname_,'_prior'];
-else
- namfile=[fname_,'_mc'];
-end
-load([OutDir,'/',namfile],'lpmat', 'lpmat0', 'istable')
-% load(options_.mode_file)
-%%
-%%
-%%
-x=[lpmat0(istable,:) lpmat(istable,:)];
-clear lpmat lpmat0 istable %iunstable egg yys T
-B = size(x,1);
-[atT,innov,measurement_error,filtered_state_vector,ys,trend_coeff, aK] = DsgeSmoother(x(1,:)',gend,data,{},0);
-n1=size(atT,1);
-
-nfil=B/40;
-stock_smooth = zeros(M_.endo_nbr,gend,40);
-stock_filter = zeros(M_.endo_nbr,gend+1,40);
-stock_ys = zeros(40, M_.endo_nbr);
-logpo2=zeros(B,1);
-%%
-h = waitbar(0,'MC smoother ...');
-delete([OutDir,'/',namfile,'_*.mat'])
-ib=0;
-ifil=0;
-opt_gsa=options_.opt_gsa;
-
-for b=1:B
- ib=ib+1;
- deep = x(b,:)';
- set_all_parameters(deep);
- dr = resol(oo_.steady_state,0);
- %deep(1:offset) = xparam1(1:offset);
- logpo2(b,1) = DsgeLikelihood(deep,gend,data,data_index,number_of_observations,no_more_missing_observations);
- if opt_gsa.lik_only==0,
- [atT,innov,measurement_error,filtered_state_vector,ys,trend_coeff, aK] = DsgeSmoother(deep,gend,data,data_index,0);
- stock_smooth(:,:,ib)=atT(1:M_.endo_nbr,:);
-% stock_filter(:,:,ib)=filtered_state_vector(1:M_.endo_nbr,:);
- stock_filter(:,:,ib)=aK(1,1:M_.endo_nbr,:);
- stock_ys(ib,:)=ys';
- if ib==40,
- ib=0;
- ifil=ifil+1;
- save([OutDir,'/',namfile,'_',num2str(ifil)],'stock_smooth','stock_filter','stock_ys')
- stock_smooth = zeros(M_.endo_nbr,gend,40);
- stock_filter = zeros(M_.endo_nbr,gend+1,40);
- stock_ys = zeros(40, M_.endo_nbr);
- end
- end
- waitbar(b/B,h,['MC smoother ...',num2str(b),'/',num2str(B)]);
-end
-close(h)
-if opt_gsa.lik_only==0,
-if ib>0,
- ifil=ifil+1;
- stock_smooth = stock_smooth(:,:,1:ib);
- stock_filter = stock_filter(:,:,1:ib);
- stock_ys = stock_ys(1:ib,:);
- save([OutDir,'/',namfile,'_',num2str(ifil)],'stock_smooth','stock_filter','stock_ys')
-end
-end
-stock_gend=gend;
-stock_data=data;
-save([OutDir,'/',namfile],'x','logpo2','stock_gend','stock_data','-append')
diff --git a/GSA_distrib/4.1/fdjac.m b/GSA_distrib/4.1/fdjac.m
deleted file mode 100644
index 2ff746531b5393759295f07a94ea67a7a24230bf..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/fdjac.m
+++ /dev/null
@@ -1,37 +0,0 @@
-% FDJAC Computes two-sided finite difference Jacobian
-% USAGE
-% fjac = fdjac(f,x,P1,P2,...)
-% INPUTS
-% f : name of function of form fval = f(x)
-% x : evaluation point
-% P1,P2,... : additional arguments for f (optional)
-% OUTPUT
-% fjac : finite differnce Jacobian
-%
-% USER OPTIONS (SET WITH OPSET)
-% tol : a factor used in setting the step size
-% increase if f is inaccurately computed
-
-% Copyright (c) 1997-2002, Paul L. Fackler & Mario J. Miranda
-% paul_fackler@ncsu.edu, miranda.4@osu.edu
-
-function fjac = fdjac(f,x,varargin)
-
-tol = optget(mfilename,'tol',eps.^(1/3));
-
-h = tol.*max(abs(x),1);
-xh1=x+h; xh0=x-h;
-h=xh1-xh0;
-for j=1:length(x);
- xx = x;
- xx(j) = xh1(j); f1=feval(f,xx,varargin{:});
- xx(j) = xh0(j); f0=feval(f,xx,varargin{:});
- fjac(:,j) = (f1-f0)/h(j);
-% v = (f1-f0);
-% k = find(abs(v) < 1e-8);
-% v(k) = 0;
-%
-% fjac(:,j) = v/h(j);
-end
-
-feval(f,x,varargin{:});
\ No newline at end of file
diff --git a/GSA_distrib/4.1/filt_mc_.m b/GSA_distrib/4.1/filt_mc_.m
deleted file mode 100644
index 45c1caf605e453d2faa164494fe304ca23f4e15a..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/filt_mc_.m
+++ /dev/null
@@ -1,708 +0,0 @@
-function [rmse_MC, ixx] = filt_mc_(OutDir)
-% function [rmse_MC, ixx] = filt_mc_(OutDir)
-% copyright Marco Ratto 2006
-% inputs (from opt_gsa structure)
-% vvarvecm = options_gsa_.var_rmse;
-% loadSA = options_gsa_.load_rmse;
-% pfilt = options_gsa_.pfilt_rmse;
-% alpha = options_gsa_.alpha_rmse;
-% alpha2 = options_gsa_.alpha2_rmse;
-% istart = options_gsa_.istart_rmse;
-% alphaPC = 0.5;
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global bayestopt_ estim_params_ M_ options_ oo_
-
-options_gsa_=options_.opt_gsa;
-vvarvecm = options_gsa_.var_rmse;
-loadSA = options_gsa_.load_rmse;
-pfilt = options_gsa_.pfilt_rmse;
-alpha = options_gsa_.alpha_rmse;
-alpha2 = options_gsa_.alpha2_rmse;
-istart = options_gsa_.istart_rmse;
-alphaPC = 0.5;
-
-fname_ = M_.fname;
-lgy_ = M_.endo_names;
-dr_ = oo_.dr;
-
-disp(' ')
-disp(' ')
-disp('Starting sensitivity analysis')
-disp('for the fit of EACH observed series ...')
-disp(' ')
-disp('Deleting old SA figures...')
-a=dir([OutDir,'/*.*']);
-tmp1='0';
-if options_.opt_gsa.ppost,
- tmp=['_rmse_post'];
-else
- if options_.opt_gsa.pprior
- tmp=['_rmse_prior'];
- else
- tmp=['_rmse_mc'];
- end
- if options_gsa_.lik_only,
- tmp1 = [tmp,'_post_SA'];
- tmp = [tmp,'_lik_SA'];
- end
-end
-for j=1:length(a),
- if strmatch([fname_,tmp],a(j).name),
- disp(a(j).name)
- delete([OutDir,'/',a(j).name])
- end,
- if strmatch([fname_,tmp1],a(j).name),
- disp(a(j).name)
- delete([OutDir,'/',a(j).name])
- end,
-end
-disp('done !')
-
-
-nshock=estim_params_.nvx + estim_params_.nvn + estim_params_.ncx + estim_params_.ncn;
-npar=estim_params_.np;
-if ~isempty(options_.mode_file),
- load(options_.mode_file,'xparam1'),
-end
-if options_.opt_gsa.ppost,
- c=load([fname_,'_mean'],'xparam1');
- xparam1_mean=c.xparam1;
- clear c
-elseif ~isempty(options_.mode_file) & ~isempty(ls([fname_,'_mean.mat']))
- c=load([fname_,'_mean'],'xparam1');
- xparam1_mean=c.xparam1;
- clear c
-end
-
-if options_.opt_gsa.ppost,
- fnamtmp=[fname_,'_post'];
- DirectoryName = CheckPath('metropolis');
-else
- if options_.opt_gsa.pprior
- fnamtmp=[fname_,'_prior'];
- else
- fnamtmp=[fname_,'_mc'];
- end
-end
-if ~loadSA,
- if exist('xparam1','var')
- set_all_parameters(xparam1);
- steady_;
- ys_mode=oo_.steady_state;
- end
- if exist('xparam1_mean','var')
- set_all_parameters(xparam1_mean);
- steady_;
- ys_mean=oo_.steady_state;
- end
-% eval(options_.datafile)
- obs = dat_fil_(options_.datafile);
- if ~options_.opt_gsa.ppost
- load([OutDir,'/',fnamtmp],'x','logpo2','stock_gend','stock_data');
- logpo2=-logpo2;
- else
- %load([DirectoryName '/' M_.fname '_data.mat']);
- [stock_gend, stock_data] = read_data;
- filfilt = dir([DirectoryName '/' M_.fname '_filter_step_ahead*.mat']);
- filparam = dir([DirectoryName '/' M_.fname '_param*.mat']);
- x=[];
- logpo2=[];
- sto_ys=[];
- for j=1:length(filparam),
- %load([DirectoryName '/' M_.fname '_param',int2str(j),'.mat']);
- if isempty(strmatch([M_.fname '_param_irf'],filparam(j).name))
- load([DirectoryName '/' filparam(j).name]);
- x=[x; stock];
- logpo2=[logpo2; stock_logpo];
- sto_ys=[sto_ys; stock_ys];
- clear stock stock_logpo stock_ys;
- end
- end
- end
- nruns=size(x,1);
- nfilt=floor(pfilt*nruns);
- if options_.opt_gsa.ppost | (options_.opt_gsa.ppost==0 & options_.opt_gsa.lik_only==0)
- disp(' ')
- disp('Computing RMSE''s...')
- fobs = options_.first_obs;
- nobs=options_.nobs;
- for i=1:size(vvarvecm,1),
- vj=deblank(vvarvecm(i,:));
- eval(['vobs =obs.',vj,'(fobs:fobs-1+nobs);'])
- if options_.prefilter == 1
- %eval([vj,'=',vj,'-bayestopt_.mean_varobs(i);'])
- %eval([vj,'=',vj,'-mean(',vj,',1);'])
- vobs = vobs-mean(vobs,1);
- end
-
- jxj = strmatch(vj,lgy_(dr_.order_var,:),'exact');
- js = strmatch(vj,lgy_,'exact');
- if exist('xparam1','var')
-% if isfield(oo_,'FilteredVariables')
-% eval(['rmse_mode(i) = sqrt(mean((vobs(istart:end)-oo_.steady_state(js)-oo_.FilteredVariables.',vj,'(istart:end-1)).^2));'])
-% else
- [alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK] = DsgeSmoother(xparam1,stock_gend,stock_data,{},0);
- y0 = squeeze(aK(1,jxj,:)) + ...
- kron(ys_mode(js,:),ones(size(aK,3),1));
-% y0 = ahat(jxj,:)' + ...
-% kron(ys_mode(js,:),ones(size(ahat,2),1));
- rmse_mode(i) = sqrt(mean((vobs(istart:end)-y0(istart:end-1)).^2));
-% end
- end
- y0=zeros(nobs+1,nruns);
- if options_.opt_gsa.ppost
- %y0=zeros(nobs+max(options_.filter_step_ahead),nruns);
- nbb=0;
- for j=1:length(filfilt),
- load([DirectoryName '/' M_.fname '_filter_step_ahead',num2str(j),'.mat']);
- nb = size(stock,4);
-% y0(:,nbb+1:nbb+nb)=squeeze(stock(1,js,:,:)) + ...
-% kron(sto_ys(nbb+1:nbb+nb,js)',ones(size(stock,3),1));
- y0(:,nbb+1:nbb+nb)=squeeze(stock(1,js,1:nobs+1,:)) + ...
- kron(sto_ys(nbb+1:nbb+nb,js)',ones(nobs+1,1));
- %y0(:,:,size(y0,3):size(y0,3)+size(stock,3))=stock;
- nbb=nbb+nb;
- clear stock;
- end
- else
- filfilt=dir([OutDir,'/',fnamtmp,'_*.mat']);
- nbb=0;
- for j=1:size(filfilt,1),
- load([OutDir,'/',fnamtmp,'_',num2str(j),'.mat'],'stock_filter','stock_ys');
- nb = size(stock_filter,3);
- y0(:,nbb+1:nbb+nb) = squeeze(stock_filter(jxj,:,:)) + ...
- kron(stock_ys(:,js)',ones(nobs+1,1));
- %y0(:,:,size(y0,3):size(y0,3)+size(stock,3))=stock;
- nbb=nbb+nb;
- clear stock_filter;
- end
-
-% y0 = squeeze(stock_filter(:,jxj,:)) + ...
-% kron(stock_ys(js,:),ones(size(stock_filter,1),1));
- end
- y0M=mean(y0,2);
- for j=1:nruns,
- rmse_MC(j,i) = sqrt(mean((vobs(istart:end)-y0(istart:end-1,j)).^2));
- end
- if exist('xparam1_mean','var')
- %eval(['rmse_pmean(i) = sqrt(mean((',vj,'(fobs-1+istart:fobs-1+nobs)-y0M(istart:end-1)).^2));'])
- [alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK] = DsgeSmoother(xparam1_mean,stock_gend,stock_data,{},0);
- y0 = squeeze(aK(1,jxj,:)) + ...
- kron(ys_mean(js,:),ones(size(aK,3),1));
-% y0 = ahat(jxj,:)' + ...
-% kron(ys_mean(js,:),ones(size(ahat,2),1));
- rmse_pmean(i) = sqrt(mean((vobs(istart:end)-y0(istart:end-1)).^2));
- end
- end
- clear stock_filter;
- end
- for j=1:nruns,
- lnprior(j,1) = priordens(x(j,:)',bayestopt_.pshape,bayestopt_.p1,bayestopt_.p2,bayestopt_.p3,bayestopt_.p4);
- end
- likelihood=logpo2(:)-lnprior(:);
- disp('... done!')
-
- if options_.opt_gsa.ppost
- save([OutDir,'/',fnamtmp], 'x', 'logpo2', 'likelihood', 'rmse_MC', 'rmse_mode','rmse_pmean')
- else
- if options_.opt_gsa.lik_only
- save([OutDir,'/',fnamtmp], 'likelihood', '-append')
- else
- save([OutDir,'/',fnamtmp], 'likelihood', 'rmse_MC','-append')
- if exist('xparam1_mean','var')
- save([OutDir,'/',fnamtmp], 'rmse_pmean','-append')
- end
- if exist('xparam1','var')
- save([OutDir,'/',fnamtmp], 'rmse_mode','-append')
- end
- end
- end
-else
- if options_.opt_gsa.lik_only & options_.opt_gsa.ppost==0
- load([OutDir,'/',fnamtmp],'x','logpo2','likelihood');
- else
- load([OutDir,'/',fnamtmp],'x','logpo2','likelihood','rmse_MC','rmse_mode','rmse_pmean');
- end
- lnprior=logpo2(:)-likelihood(:);
- nruns=size(x,1);
- nfilt=floor(pfilt*nruns);
-end
-% smirnov tests
-nfilt0=nfilt*ones(size(vvarvecm,1),1);
-logpo2=logpo2(:);
-if ~options_.opt_gsa.ppost
- [dum, ipost]=sort(-logpo2);
- [dum, ilik]=sort(-likelihood);
-end
-if ~options_.opt_gsa.ppost & options_.opt_gsa.lik_only
- if options_.opt_gsa.pprior
- anam='rmse_prior_post';
- else
- anam='rmse_mc_post';
- end
- stab_map_1(x, ipost(1:nfilt), ipost(nfilt+1:end), anam, 1,[],OutDir);
- stab_map_2(x(ipost(1:nfilt),:),alpha2,anam, OutDir);
- if options_.opt_gsa.pprior
- anam='rmse_prior_lik';
- else
- anam='rmse_mc_lik';
- end
- stab_map_1(x, ilik(1:nfilt), ilik(nfilt+1:end), anam, 1,[],OutDir);
- stab_map_2(x(ilik(1:nfilt),:),alpha2,anam, OutDir);
-else
- for i=1:size(vvarvecm,1),
- [dum, ixx(:,i)]=sort(rmse_MC(:,i));
- if options_.opt_gsa.ppost,
- %nfilt0(i)=length(find(rmse_MC(:,i)<rmse_pmean(i)));
- rmse_txt=rmse_pmean;
- else
- if options_.opt_gsa.pprior | ~exist('rmse_pmean'),
- if exist('rmse_mode'),
- rmse_txt=rmse_mode;
- else
- rmse_txt=NaN(1,size(rmse_MC,2));
- end
- else
- %nfilt0(i)=length(find(rmse_MC(:,i)<rmse_pmean(i)));
- rmse_txt=rmse_pmean;
- end
- end
- for j=1:npar+nshock,
- [H,P,KSSTAT] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j), alpha);
- [H1,P1,KSSTAT1] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j),alpha,1);
- [H2,P2,KSSTAT2] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j),alpha,-1);
- if H1 & H2==0,
- SS(j,i)=1;
- elseif H1==0,
- SS(j,i)=-1;
- else
- SS(j,i)=0;
- end
- PP(j,i)=P;
- end
-end
-ifig=0;
-for i=1:size(vvarvecm,1),
- if mod(i,9)==1,
- ifig=ifig+1;
- figure('name',['Prior ',int2str(ifig)])
- end
- subplot(3,3,i-9*(ifig-1))
- h=cumplot(lnprior(ixx(1:nfilt0(i),i)));
- set(h,'color','red')
- hold on, cumplot(lnprior)
- h=cumplot(lnprior(ixx(nfilt0(i)+1:end,i)));
- set(h,'color','green')
- title(vvarvecm(i,:))
- if mod(i,9)==0 | i==size(vvarvecm,1)
- if options_.opt_gsa.ppost
- saveas(gcf,[OutDir,'/',fname_,'_rmse_post_lnprior',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_post_lnprior',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_post_lnprior',int2str(ifig)]);
- else
- if options_.opt_gsa.pprior
- saveas(gcf,[OutDir,'/',fname_,'_rmse_prior_lnprior',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_prior_lnprior',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_prior_lnprior',int2str(ifig)]);
- else
- saveas(gcf,[OutDir,'/',fname_,'_rmse_mc_lnprior',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_mc_lnprior',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_mc_lnprior',int2str(ifig)]);
- end
- end
- close(gcf)
- end
-end
-ifig=0;
-for i=1:size(vvarvecm,1),
- if mod(i,9)==1,
- ifig=ifig+1;
- figure('name',['Likelihood ',int2str(ifig)])
- end
- subplot(3,3,i-9*(ifig-1))
- h=cumplot(likelihood(ixx(1:nfilt0(i),i)));
- set(h,'color','red')
- hold on, h=cumplot(likelihood);
- h=cumplot(likelihood(ixx(nfilt0(i)+1:end,i)));
- set(h,'color','green')
- title(vvarvecm(i,:))
- if options_.opt_gsa.ppost==0,
- set(gca,'xlim',[min( likelihood(ixx(1:nfilt0(i),i)) ) max( likelihood(ixx(1:nfilt0(i),i)) )])
- end
- if mod(i,9)==0 | i==size(vvarvecm,1)
- if options_.opt_gsa.ppost
- saveas(gcf,[OutDir,'/',fname_,'_rmse_post_lnlik',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_post_lnlik',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_post_lnlik',int2str(ifig)]);
- else
- if options_.opt_gsa.pprior
- saveas(gcf,[OutDir,'/',fname_,'_rmse_prior_lnlik',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_prior_lnlik',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_prior_lnlik',int2str(ifig)]);
- else
- saveas(gcf,[OutDir,'/',fname_,'_rmse_mc_lnlik',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_mc_lnlik',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_mc_lnlik',int2str(ifig)]);
- end
- end
- close(gcf)
- end
-end
-ifig=0;
-for i=1:size(vvarvecm,1),
- if mod(i,9)==1,
- ifig=ifig+1;
- figure('name',['Posterior ',int2str(ifig)])
- end
- subplot(3,3,i-9*(ifig-1))
- h=cumplot(logpo2(ixx(1:nfilt0(i),i)));
- set(h,'color','red')
- hold on, h=cumplot(logpo2);
- h=cumplot(logpo2(ixx(nfilt0(i)+1:end,i)));
- set(h,'color','green')
- title(vvarvecm(i,:))
- if options_.opt_gsa.ppost==0,
- set(gca,'xlim',[min( logpo2(ixx(1:nfilt0(i),i)) ) max( logpo2(ixx(1:nfilt0(i),i)) )])
- end
- if mod(i,9)==0 | i==size(vvarvecm,1)
- if options_.opt_gsa.ppost
- saveas(gcf,[OutDir,'/',fname_,'_rmse_post_lnpost',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_post_lnpost',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_post_lnpost',int2str(ifig)]);
- else
- if options_.opt_gsa.pprior
- saveas(gcf,[OutDir,'/',fname_,'_rmse_prior_lnpost',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_prior_lnpost',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_prior_lnpost',int2str(ifig)]);
- else
- saveas(gcf,[OutDir,'/',fname_,'_rmse_mc_lnpost',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_mc_lnpost',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_mc_lnpost',int2str(ifig)]);
- end
- end
- close(gcf)
- end
-end
-
-param_names='';
-for j=1:npar+nshock,
- param_names=str2mat(param_names, bayestopt_.name{j});
-end
-param_names=param_names(2:end,:);
-
-disp(' ')
-disp('RMSE over the MC sample:')
-disp(' min yr RMSE max yr RMSE')
-for j=1:size(vvarvecm,1),
- disp([vvarvecm(j,:), sprintf('%15.5g',[(min(rmse_MC(:,j))) [(max(rmse_MC(:,j)))]])])
-end
-invar = find( std(rmse_MC)./mean(rmse_MC)<=0.0001 );
-if ~isempty(invar)
- disp(' ')
- disp(' ')
- disp('RMSE is not varying significantly over the MC sample for the following variables:')
- disp(vvarvecm(invar,:))
- disp('These variables are excluded from SA')
- disp('[Unless you treat these series as exogenous, there is something wrong in your estimation !]')
-end
-ivar = find( std(rmse_MC)./mean(rmse_MC)>0.0001 );
-vvarvecm=vvarvecm(ivar,:);
-rmse_MC=rmse_MC(:,ivar);
-
-disp(' ')
-% if options_.opt_gsa.ppost==0 & options_.opt_gsa.pprior,
- disp(['Sample filtered the ',num2str(pfilt*100),'% best RMSE''s for each observed series ...' ])
-% else
-% disp(['Sample filtered the best RMSE''s smaller than RMSE at the posterior mean ...' ])
-% end
-% figure, boxplot(rmse_MC)
-% set(gca,'xticklabel',vvarvecm)
-% saveas(gcf,[fname_,'_SA_RMSE'])
-
-disp(' ')
-disp(' ')
-disp('RMSE ranges after filtering:')
-if options_.opt_gsa.ppost==0 & options_.opt_gsa.pprior,
- disp([' best ',num2str(pfilt*100),'% filtered remaining 90%'])
- disp([' min max min max posterior mode'])
-else
- disp([' best filtered remaining '])
- disp([' min max min max posterior mean'])
-end
-for j=1:size(vvarvecm,1),
- disp([vvarvecm(j,:), sprintf('%15.5g',[min(rmse_MC(ixx(1:nfilt0(j),j),j)) ...
- max(rmse_MC(ixx(1:nfilt0(j),j),j)) ...
- min(rmse_MC(ixx(nfilt0(j)+1:end,j),j)) ...
- max(rmse_MC(ixx(nfilt0(j)+1:end,j),j)) ...
- rmse_txt(j)])])
- % disp([vvarvecm(j,:), sprintf('%15.5g',[min(logpo2(ixx(1:nfilt,j))) ...
- % max(logpo2(ixx(1:nfilt,j))) ...
- % min(logpo2(ixx(nfilt+1:end,j))) ...
- % max(logpo2(ixx(nfilt+1:end,j)))])])
-end
-
-SP=zeros(npar+nshock,size(vvarvecm,1));
-for j=1:size(vvarvecm,1),
- ns=find(PP(:,j)<alpha);
- SP(ns,j)=ones(size(ns));
- SS(:,j)=SS(:,j).*SP(:,j);
-end
-
-for j=1:npar+nshock, %estim_params_.np,
- nsp(j)=length(find(SP(j,:)));
-end
-snam0=param_names(find(nsp==0),:);
-snam1=param_names(find(nsp==1),:);
-snam2=param_names(find(nsp>1),:);
-snam=param_names(find(nsp>0),:);
-% snam0=bayestopt_.name(find(nsp==0));
-% snam1=bayestopt_.name(find(nsp==1));
-% snam2=bayestopt_.name(find(nsp>1));
-% snam=bayestopt_.name(find(nsp>0));
-nsnam=(find(nsp>1));
-
-disp(' ')
-disp(' ')
-disp('These parameters do not affect significantly the fit of ANY observed series:')
-disp(snam0)
-disp(' ')
-disp('These parameters affect ONE single observed series:')
-disp(snam1)
-disp(' ')
-disp('These parameters affect MORE THAN ONE observed series: trade off exists!')
-disp(snam2)
-
-
-%pnam=bayestopt_.name(end-estim_params_.np+1:end);
-pnam=bayestopt_.name;
-
-% plot trade-offs
-a00=jet(size(vvarvecm,1));
-for ix=1:ceil(length(nsnam)/5),
- figure,
- for j=1+5*(ix-1):min(size(snam2,1),5*ix),
- subplot(2,3,j-5*(ix-1))
- %h0=cumplot(x(:,nsnam(j)+nshock));
- h0=cumplot(x(:,nsnam(j)));
- set(h0,'color',[0 0 0])
- hold on,
- np=find(SP(nsnam(j),:));
- %a0=jet(nsp(nsnam(j)));
- a0=a00(np,:);
- for i=1:nsp(nsnam(j)), %size(vvarvecm,1),
- %h0=cumplot(x(ixx(1:nfilt,np(i)),nsnam(j)+nshock));
- h0=cumplot(x(ixx(1:nfilt0(np(i)),np(i)),nsnam(j)));
- set(h0,'color',a0(i,:))
- end
- ydum=get(gca,'ylim');
- %xdum=xparam1(nshock+nsnam(j));
- if exist('xparam1')
- xdum=xparam1(nsnam(j));
- h1=plot([xdum xdum],ydum);
- set(h1,'color',[0.85 0.85 0.85],'linewidth',2)
- end
- xlabel('')
- title([pnam{nsnam(j)}],'interpreter','none')
- end
- %subplot(3,2,6)
- h0=legend(str2mat('base',vvarvecm(np,:)),0);
- set(h0,'fontsize',6,'position',[0.7 0.1 0.2 0.3],'interpreter','none')
- %h0=legend({'base',vnam{np}}',0);
- %set(findobj(get(h0,'children'),'type','text'),'interpreter','none')
- if options_.opt_gsa.ppost
- saveas(gcf,[OutDir,'/',fname_,'_rmse_post_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_post_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_post_' int2str(ix)]);
- else
- if options_.opt_gsa.pprior
- saveas(gcf,[OutDir,'/',fname_,'_rmse_prior_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_prior_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_prior_' int2str(ix)]);
- else
- saveas(gcf,[OutDir,'/',fname_,'_rmse_mc_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_mc_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_mc_' int2str(ix)]);
- end
- end
-end
-close all
-
-for j=1:size(SP,2),
- nsx(j)=length(find(SP(:,j)));
-end
-
-number_of_grid_points = 2^9; % 2^9 = 512 !... Must be a power of two.
-bandwidth = 0; % Rule of thumb optimal bandwidth parameter.
-kernel_function = 'gaussian'; % Gaussian kernel for Fast Fourrier Transform approximaton.
-%kernel_function = 'uniform'; % Gaussian kernel for Fast Fourrier Transform approximaton.
-
-for ix=1:ceil(length(nsnam)/5),
- figure,
- for j=1+5*(ix-1):min(size(snam2,1),5*ix),
- subplot(2,3,j-5*(ix-1))
- optimal_bandwidth = mh_optimal_bandwidth(x(:,nsnam(j)),size(x,1),bandwidth,kernel_function);
- [x1,f1] = kernel_density_estimate(x(:,nsnam(j)),number_of_grid_points,...
- size(x,1),optimal_bandwidth,kernel_function);
- h0 = plot(x1, f1,'k');
- hold on,
- np=find(SP(nsnam(j),:));
- %a0=jet(nsp(nsnam(j)));
- a0=a00(np,:);
- for i=1:nsp(nsnam(j)), %size(vvarvecm,1),
- optimal_bandwidth = mh_optimal_bandwidth(x(ixx(1:nfilt0(np(i)),np(i)),nsnam(j)),nfilt,bandwidth,kernel_function);
- [x1,f1] = kernel_density_estimate(x(ixx(1:nfilt0(np(i)),np(i)),nsnam(j)),number_of_grid_points,...
- nfilt, optimal_bandwidth,kernel_function);
- h0 = plot(x1, f1);
- set(h0,'color',a0(i,:))
- end
- ydum=get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)]);
- if exist('xparam1')
- %xdum=xparam1(nshock+nsnam(j));
- xdum=xparam1(nsnam(j));
- h1=plot([xdum xdum],[0 ydum(2)]);
- set(h1,'color',[0.85 0.85 0.85],'linewidth',2)
- end
- xlabel('')
- title([pnam{nsnam(j)}],'interpreter','none')
- end
- h0=legend(str2mat('base',vvarvecm(np,:)),0);
- set(h0,'fontsize',6,'position',[0.7 0.1 0.2 0.3],'interpreter','none')
- %h0=legend({'base',vnam{np}}',0);
- %set(findobj(get(h0,'children'),'type','text'),'interpreter','none')
- if options_.opt_gsa.ppost
- saveas(gcf,[OutDir,'/',fname_,'_rmse_post_dens_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_post_dens_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_post_dens_' int2str(ix)]);
- else
- if options_.opt_gsa.pprior
- saveas(gcf,[OutDir,'/',fname_,'_rmse_prior_dens_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_prior_dens_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_prior_dens_' int2str(ix)]);
- else
- saveas(gcf,[OutDir,'/',fname_,'_rmse_mc_dens_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_mc_dens_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_mc_dens_' int2str(ix)]);
- end
- end
-end
-close all
-
-% for j=1:size(SP,2),
-% nfig=0;
-% np=find(SP(:,j));
-% for i=1:nsx(j), %size(vvarvecm,1),
-% if mod(i,12)==1,
-% nfig=nfig+1;
-% %figure('name',['Sensitivity of fit of ',vnam{j}]),
-% figure('name',['Sensitivity of fit of ',deblank(vvarvecm(j,:)),' ',num2str(nfig)]),
-% end
-%
-% subplot(3,4,i-12*(nfig-1))
-% optimal_bandwidth = mh_optimal_bandwidth(x(ixx(1:nfilt,j),np(i)),nfilt,bandwidth,kernel_function);
-% [x1,f1] = kernel_density_estimate(x(ixx(1:nfilt,j),np(i)),number_of_grid_points,...
-% nfilt, optimal_bandwidth,kernel_function);
-% plot(x1, f1,':k','linewidth',2)
-% optimal_bandwidth = mh_optimal_bandwidth(x(ixx(nfilt+1:end,j),np(i)),nruns-nfilt,bandwidth,kernel_function);
-% [x1,f1] = kernel_density_estimate(x(ixx(nfilt+1:end,j),np(i)),number_of_grid_points,...
-% nruns-nfilt,optimal_bandwidth,kernel_function);
-% hold on, plot(x1, f1,'k','linewidth',2)
-% ydum=get(gca,'ylim');
-% %xdum=xparam1(nshock+np(i));
-% xdum=xparam1(np(i));
-% h1=plot([xdum xdum],ydum);
-% set(h1,'color',[0.85 0.85 0.85],'linewidth',2)
-% %xdum1=mean(x(ixx(1:nfilt,j),np(i)+nshock));
-% xdum1=mean(x(ixx(1:nfilt,j),np(i)));
-% h2=plot([xdum1 xdum1],ydum);
-% set(h2,'color',[0 1 0],'linewidth',2)
-% % h0=cumplot(x(nfilt+1:end,np(i)+nshock));
-% % set(h0,'color',[1 1 1])
-% % hold on,
-% % h0=cumplot(x(ixx(1:nfilt,j),np(i)+nshock));
-% % set(h0,'linestyle',':','color',[1 1 1])
-% %title([pnam{np(i)}])
-% title([pnam{np(i)},'. K-S prob ', num2str(PP(np(i),j))],'interpreter','none')
-% xlabel('')
-% if mod(i,12)==0 | i==nsx(j),
-% saveas(gcf,[fname_,'_rmse_',deblank(vvarvecm(j,:)),'_',int2str(nfig)])
-% close(gcf)
-% end
-% end
-% end
-
-
-disp(' ')
-disp(' ')
-disp('Sensitivity table (significance and direction):')
-vav=char(zeros(1, size(param_names,2)+3 ));
-ibl = 12-size(vvarvecm,2);
-for j=1:size(vvarvecm,1),
- vav = [vav, char(zeros(1,ibl)),vvarvecm(j,:)];
-end
-disp(vav)
-for j=1:npar+nshock, %estim_params_.np,
- %disp([param_names(j,:), sprintf('%8.5g',SP(j,:))])
- disp([param_names(j,:),' ', sprintf('%12.3g',PP(j,:))])
- disp([char(zeros(1, size(param_names,2)+3 )),sprintf(' (%6g)',SS(j,:))])
-end
-
-
-disp(' ')
-disp(' ')
-disp('Starting bivariate analysis:')
-
-for i=1:size(vvarvecm,1)
- if options_.opt_gsa.ppost
- fnam = ['rmse_post_',deblank(vvarvecm(i,:))];
- else
- if options_.opt_gsa.pprior
- fnam = ['rmse_prior_',deblank(vvarvecm(i,:))];
- else
- fnam = ['rmse_mc_',deblank(vvarvecm(i,:))];
- end
- end
- stab_map_2(x(ixx(1:nfilt0(i),i),:),alpha2,fnam, OutDir);
-
- % [pc,latent,explained] = pcacov(c0);
- % %figure, bar([explained cumsum(explained)])
- % ifig=0;
- % j2=0;
- % for j=1:npar+nshock,
- % i2=find(abs(pc(:,j))>alphaPC);
- % if ~isempty(i2),
- % j2=j2+1;
- % if mod(j2,12)==1,
- % ifig=ifig+1;
- % figure('name',['PCA of the filtered sample ',deblank(vvarvecm(i,:)),' ',num2str(ifig)]),
- % end
- % subplot(3,4,j2-(ifig-1)*12)
- % bar(pc(i2,j)),
- % set(gca,'xticklabel',bayestopt_.name(i2)),
- % set(gca,'xtick',[1:length(i2)])
- % title(['PC ',num2str(j),'. Explained ',num2str(explained(j)),'%'])
- % end
- % if (mod(j2,12)==0 | j==(npar+nshock)) & j2,
- % saveas(gcf,[fname_,'_SA_PCA_',deblank(vvarvecm(i,:)),'_',int2str(ifig)])
- % end
- % end
- % close all
-end
-
-end
\ No newline at end of file
diff --git a/GSA_distrib/4.1/gamm_cdf.m b/GSA_distrib/4.1/gamm_cdf.m
deleted file mode 100644
index a11d0962a4cd911ae962b4830afdb383572d532f..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/gamm_cdf.m
+++ /dev/null
@@ -1,27 +0,0 @@
-function cdf = gamm_cdf (x, a)
-% PURPOSE: returns the cdf at x of the gamma(a) distribution
-%---------------------------------------------------
-% USAGE: cdf = gamm_cdf(x,a)
-% where: x = a vector
-% a = a scalar gamma(a)
-%---------------------------------------------------
-% RETURNS:
-% a vector of cdf at each element of x of the gamma(a) distribution
-% --------------------------------------------------
-% SEE ALSO: gamm_d, gamm_pdf, gamm_rnd, gamm_inv
-%---------------------------------------------------
-
-% Anders Holtsberg, 18-11-93
-% Copyright (c) Anders Holtsberg
-
-if nargin ~= 2
-error('Wrong # of arguments to gamm_cdf');
-end;
-
-if any(any(a<=0))
- error('gamm_cdf: parameter a is wrong')
-end
-
-cdf = gammainc(x,a);
-I0 = find(x<0);
-cdf(I0) = zeros(size(I0));
diff --git a/GSA_distrib/4.1/gamm_inv.m b/GSA_distrib/4.1/gamm_inv.m
deleted file mode 100644
index 3bede95ba39a4309c86bc5e2c5e347c840dbb23f..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/gamm_inv.m
+++ /dev/null
@@ -1,50 +0,0 @@
-function x = gamm_inv(p,a,b)
-% PURPOSE: returns the inverse of the cdf at p of the gamma(a,b) distribution
-%---------------------------------------------------
-% USAGE: x = gamm_inv(p,a)
-% where: p = a vector of probabilities
-% a = a scalar parameter gamma(a)
-% b = scaling factor for gamma
-%---------------------------------------------------
-% RETURNS:
-% a vector x of the quantile at each element of p of the gamma(a) distribution
-% --------------------------------------------------
-% SEE ALSO: gamm_d, gamm_pdf, gamm_rnd, gamm_cdf
-%---------------------------------------------------
-
-% Anders Holtsberg, 18-11-93
-% Copyright (c) Anders Holtsberg
-% documentation modified by LeSage to fit the format
-% of the econometrics toolbox
-
- if (nargin < 2 | isempty(b))
- b=1;
- end
-
- if (nargin > 3)
- error('Wrong # of arguments to gamm_inv');
- end
-
-
-if any(any(abs(2*p-1)>1))
- error('gamm_inv: a probability should be 0<=p<=1')
-end
-if any(any(a<=0))
- error('gamma_inv: parameter a is wrong')
-end
-
-x = max(a-1,0.1);
-dx = 1;
-while any(any(abs(dx)>256*eps*max(x,1)))
- dx = (gamm_cdf(x,a) - p) ./ gamm_pdf(x,a);
- x = x - dx;
- x = x + (dx - x) / 2 .* (x<0);
-end
-
-I0 = find(p==0);
-x(I0) = zeros(size(I0));
-I1 = find(p==1);
-x(I1) = zeros(size(I0)) + Inf;
-
-
-x=x.*b;
diff --git a/GSA_distrib/4.1/gamm_pdf.m b/GSA_distrib/4.1/gamm_pdf.m
deleted file mode 100644
index 86f4ffb1deb909af6fd7a5fddc4825f9c996ffc2..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/gamm_pdf.m
+++ /dev/null
@@ -1,27 +0,0 @@
-function f = gamm_pdf (x, a)
-% PURPOSE: returns the pdf at x of the gamma(a) distribution
-%---------------------------------------------------
-% USAGE: pdf = gamm_pdf(x,a)
-% where: x = a vector
-% a = a scalar for gamma(a)
-%---------------------------------------------------
-% RETURNS:
-% a vector of pdf at each element of x of the gamma(a) distribution
-% --------------------------------------------------
-% SEE ALSO: gamm_cdf, gamm_rnd, gamm_inv
-%---------------------------------------------------
-
-% Anders Holtsberg, 18-11-93
-% Copyright (c) Anders Holtsberg
-
-if nargin ~= 2
-error('Wrong # of arguments to gamm_cdf');
-end;
-
-if any(any(a<=0))
- error('gamm_pdf: parameter a is wrong')
-end
-
-f = x .^ (a-1) .* exp(-x) ./ gamma(a);
-I0 = find(x<0);
-f(I0) = zeros(size(I0));
diff --git a/GSA_distrib/4.1/gsa.zip b/GSA_distrib/4.1/gsa.zip
deleted file mode 100644
index 8a40d3f8f26095d1f0bbccf82d6d41a4a22a4544..0000000000000000000000000000000000000000
Binary files a/GSA_distrib/4.1/gsa.zip and /dev/null differ
diff --git a/GSA_distrib/4.1/log_trans_.m b/GSA_distrib/4.1/log_trans_.m
deleted file mode 100644
index b0ff26ddfa8afd10f51f6e8eab91dfa3ca88fcc2..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/log_trans_.m
+++ /dev/null
@@ -1,54 +0,0 @@
-function [yy, xdir, isig, lam]=log_trans_(y0,xdir0)
-
-if nargin==1,
- xdir0='';
-end
-f=inline('skewness(log(y+lam))','lam','y');
-isig=1;
-if ~(max(y0)<0 | min(y0)>0)
- if skewness(y0)<0,
- isig=-1;
- y0=-y0;
- end
- n=hist(y0,10);
- if n(1)>20*n(end),
- try lam=fzero(f,[-min(y0)+10*eps -min(y0)+abs(median(y0))],[],y0);
- catch
- yl(1)=f(-min(y0)+10*eps,y0);
- yl(2)=f(-min(y0)+abs(median(y0)),y0);
- if abs(yl(1))<abs(yl(2))
- lam=-min(y0)+eps;
- else
- lam = -min(y0)+abs(median(y0)); %abs(100*(1+min(y0)));
- end
- end
- yy = log(y0+lam);
- xdir=[xdir0,'_logskew'];
- else
- isig=0;
- lam=0;
- yy = log(y0.^2);
- xdir=[xdir0,'_logsquared'];
- end
-else
- if max(y0)<0
- isig=-1;
- y0=-y0;
- %yy=log(-y0);
- xdir=[xdir0,'_minuslog'];
- elseif min(y0)>0
- %yy=log(y0);
- xdir=[xdir0,'_log'];
- end
- try lam=fzero(f,[-min(y0)+10*eps -min(y0)+median(y0)],[],y0);
- catch
- yl(1)=f(-min(y0)+10*eps,y0);
- yl(2)=f(-min(y0)+abs(median(y0)),y0);
- if abs(yl(1))<abs(yl(2))
- lam=-min(y0)+eps;
- else
- lam = -min(y0)+abs(median(y0)); %abs(100*(1+min(y0)));
- end
- end
- yy = log(y0+lam);
-end
diff --git a/GSA_distrib/4.1/lptauSEQ.m b/GSA_distrib/4.1/lptauSEQ.m
deleted file mode 100644
index 3f34e9ef4a50c90d6d3d6674f84be7544c201f38..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/lptauSEQ.m
+++ /dev/null
@@ -1,25 +0,0 @@
-function [lpmat] = lptauSEQ(Nsam,Nvar)
-
-% [lpmat] = lptauSEQ(Nsam,Nvar)
-%
-% function call LPTAU and generates a sample of dimension Nsam for a
-% number of parameters Nvar
-%
-% Copyright (C) 2005 Marco Ratto
-% THIS PROGRAM WAS WRITTEN FOR MATLAB BY
-% Marco Ratto,
-% Unit of Econometrics and Statistics AF
-% (http://www.jrc.cec.eu.int/uasa/),
-% IPSC, Joint Research Centre
-% The European Commission,
-% TP 361, 21020 ISPRA(VA), ITALY
-% marco.ratto@jrc.it
-%
-
-
-clear lptau
-lpmat = zeros(Nsam, Nvar);
-for j=1:Nsam,
- lpmat(j,:)=LPTAU(j,Nvar);
-end
-return
diff --git a/GSA_distrib/4.1/map_ident_.m b/GSA_distrib/4.1/map_ident_.m
deleted file mode 100644
index 96c28557440c8b04b5a89d15b15b9bc0731318fd..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/map_ident_.m
+++ /dev/null
@@ -1,1531 +0,0 @@
-function map_ident_(OutputDirectoryName)
-global bayestopt_ M_ options_ estim_params_ oo_
-
-opt_gsa = options_.opt_gsa;
-fname_ = M_.fname;
-nliv = opt_gsa.morris_nliv;
-ntra = opt_gsa.morris_ntra;
-itrans = opt_gsa.trans_ident;
-
-np = estim_params_.np;
-if opt_gsa.load_ident_files,
- gsa_flag=0;
-else
- gsa_flag=-2;
-end
-
-pnames = M_.param_names(estim_params_.param_vals(:,1),:);
-
-filetoload=[OutputDirectoryName '/' fname_ '_prior'];
-load(filetoload,'lpmat','lpmat0','istable','T','yys','nspred','nboth','nfwrd')
-if ~isempty(lpmat0),
- lpmatx=lpmat0(istable,:);
-else
- lpmatx=[];
-end
-Nsam = size(lpmat,1);
-nshock = size(lpmat0,2);
-npT = np+nshock;
-
-fname_ = M_.fname;
-
-if opt_gsa.load_ident_files==0,
- % th moments
-% options_.ar = min(3,options_.ar);
-
- mss = yys(bayestopt_.mfys,:);
- mss = teff(mss(:,istable),Nsam,istable);
- yys = teff(yys(oo_.dr.order_var,istable),Nsam,istable);
- [vdec, cc, ac] = mc_moments(T, lpmatx, oo_.dr);
-
-
- if opt_gsa.morris==2,
- [pdraws, TAU, GAM] = dynare_identification(options_.options_ident,[lpmatx lpmat(istable,:)]);
- if max(max(abs(pdraws-[lpmatx lpmat(istable,:)])))==0,
- disp(['Sample check OK ', num2str(max(max(abs(pdraws-[lpmatx lpmat(istable,:)]))))]),
- clear pdraws;
- end
-% for j=1:length(istable), gas(:,j)=[vech(cc(:,:,j)); vec(ac(:,:,j))]; end
-% if ~isempty(mss),
-% gas = [mss(istable,:)'; gas];
-% end
-% if max(max(abs(GAM-gas)))<=1.e-8,
-% disp(['Moments check OK ',num2str(max(max(abs(GAM-gas))))]),
- clear GAM gas
-% end
- end
- if opt_gsa.morris~=1 & M_.exo_nbr>1,
- ifig=0;
- for j=1:M_.exo_nbr,
- if mod(j,6)==1
- figure('name',['Variance decomposition shocks']);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(2,3,iplo)
- myboxplot(squeeze(vdec(:,j,:))',[],'.',[],10)
- % boxplot(squeeze(vdec(:,j,:))','whis',10,'symbol','.r')
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:size(options_.varobs,1)])
- set(gca,'xlim',[0.5 size(options_.varobs,1)+0.5])
- set(gca,'ylim',[-2 102])
- for ip=1:size(options_.varobs,1),
- text(ip,-4,deblank(options_.varobs(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- ylabel(' ')
- title(M_.exo_names(j,:),'interpreter','none')
- if mod(j,6)==0 | j==M_.exo_nbr,
- saveas(gcf,[OutputDirectoryName,'/',fname_,'_vdec_exo_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_vdec_exo_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_vdec_exo_',int2str(ifig)]);
- close(gcf),
- end
- end
- end
- for j=1:size(cc,1)
- cc(j,j,:)=stand_(squeeze(log(cc(j,j,:))))./2;
- end
- [vdec, j0, ir_vdec, ic_vdec] = teff(vdec,Nsam,istable);
- [cc, j0, ir_cc, ic_cc] = teff(cc,Nsam,istable);
- [ac, j0, ir_ac, ic_ac] = teff(ac,Nsam,istable);
-
- [nr1, nc1, nnn] = size(T);
- endo_nbr = M_.endo_nbr;
- nstatic = oo_.dr.nstatic;
- npred = oo_.dr.npred;
- iv = (1:endo_nbr)';
- ic = [ nstatic+(1:npred) endo_nbr+(1:size(oo_.dr.ghx,2)-npred) ]';
- aux = oo_.dr.transition_auxiliary_variables;
- k = find(aux(:,2) > npred);
- aux(:,2) = aux(:,2) + nstatic;
- aux(k,2) = aux(k,2) + oo_.dr.nfwrd;
-
- dr.ghx = T(:, [1:(nc1-M_.exo_nbr)],1);
- dr.ghu = T(:, [(nc1-M_.exo_nbr+1):end], 1);
- [Aa,Bb] = kalman_transition_matrix(dr, ...
- iv, ic, aux, M_.exo_nbr);
-% bayestopt_.restrict_var_list, ...
-% bayestopt_.restrict_columns, ...
-% bayestopt_.restrict_aux, M_.exo_nbr);
- A = zeros(size(Aa,1),size(Aa,2)+size(Aa,1),length(istable));
- % Sig(estim_params_.var_exo(:,1))=lpmatx(1,:).^2;
- set_shocks_param(lpmatx(1,:));
- A(:,:,1)=[Aa, triu(Bb*M_.Sigma_e*Bb')];
- for j=2:length(istable),
- dr.ghx = T(:, [1:(nc1-M_.exo_nbr)],j);
- dr.ghu = T(:, [(nc1-M_.exo_nbr+1):end], j);
- [Aa,Bb] = kalman_transition_matrix(dr, ...
- iv, ic, aux, M_.exo_nbr);
-% bayestopt_.restrict_var_list, ...
-% bayestopt_.restrict_columns, ...
-% bayestopt_.restrict_aux, M_.exo_nbr);
- set_shocks_param(lpmatx(j,:));
- A(:,:,j)=[Aa, triu(Bb*M_.Sigma_e*Bb')];
- end
- clear T;
- clear lpmatx;
-
- [nr,nc,nn]=size(A);
- io=bayestopt_.mf2;
- % T1=A(io,1:nr,:);
- % ino=find(~ismember([1:nr],io));
- % T2=A(ino,1:nr,:);
- R=A(:,nr+1:nc,:);
-% [tadj, iff] = speed(A(1:nr,1:nr,:),R,io,0.5);
-% [tadj, j0, ir_tadj, ic_tadj] = teff(tadj,Nsam,istable);
-% [iff, j0, ir_if, ic_if] = teff(iff,Nsam,istable);
-
-
- [yt, j0]=teff(A,Nsam,istable);
- yt = [yys yt];
- if opt_gsa.morris==2,
-% iii=find(std(yt(istable,:))>1.e-8);
-% if max(max(abs(TAU-yt(istable,iii)')))<= 1.e-8,
-% err = max(max(abs(TAU-yt(istable,iii)')));
-% disp(['Model check OK ',num2str(err)]),
- clear TAU A
-% end
- else
- clear A,
- end
- % [yt1, j01]=teff(T1,Nsam,istable);
- % [yt2, j02]=teff(T2,Nsam,istable);
- % [ytr, j0r]=teff(R,Nsam,istable);
- %
- % yt=[yt1 yt2 ytr];
- save([OutputDirectoryName,'/',fname_,'_main_eff'],'ac','cc','vdec','yt','mss')
-else
- if opt_gsa.morris==2,
-% [pdraws, TAU, GAM] = dynare_identification([1:npT]); %,[lpmatx lpmat(istable,:)]);
- [pdraws, TAU, GAM] = dynare_identification(options_.options_ident);
- end
- load([OutputDirectoryName,'/',fname_,'_main_eff'],'ac','cc','vdec','yt','mss')
-end
-
-% for j=1:nr,
-% for i=1:nc,
-% y0=squeeze(A(j,i,:));
-% if max(y0)-min(y0)>1.e-10,
-% j0=j0+1;
-% y1=ones(size(lpmat,1),1)*NaN;
-% y1(istable,1)=y0;
-% yt(:,j0)=y1;
-% end
-% end
-% end
-% yt = yt(:,j0);
-
-if opt_gsa.morris==1,
- %OutputDir = CheckPath('GSA/SCREEN');
- if ~isempty(vdec),
- if opt_gsa.load_ident_files==0,
- SAMorris = [];
- for i=1:size(vdec,2),
- [SAmeas, SAMorris(:,:,i)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], vdec(:,i),nliv);
- end
- SAvdec = squeeze(SAMorris(:,1,:))';
- save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAvdec','vdec','ir_vdec','ic_vdec')
- else
- load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAvdec','vdec','ir_vdec','ic_vdec')
- end
-
- figure,
-% boxplot(SAvdec,'whis',10,'symbol','r.')
- myboxplot(SAvdec,[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:npT,
- text(ip,-2,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('All variance decomposition')
- saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_vdec'])
- eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_vdec']);
- eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_vdec']);
- close(gcf)
- else
- save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'vdec')
-
- end
-
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['EET variance decomposition observed variables']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_vdec==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAvdec(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAvdec(iv,:),[],'.',[],3)
-% else
-% plot(SAvdec(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-2,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_vdec_varobs_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_vdec_varobs_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_vdec_varobs_',int2str(ifig)]);
-% close(gcf)
-% end
-% end
-%
-% ifig = 0;
-% for j=1:M_.exo_nbr,
-% if mod(j,6)==1
-% figure('name',['EET variance decomposition shocks']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ic_vdec==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAvdec(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAvdec(iv,:),[],'.',[],3)
-% else
-% plot(SAvdec(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-2,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(M_.exo_names(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==M_.exo_nbr,
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_vdec_exo_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_vdec_exo_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_vdec_exo_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
-
- if opt_gsa.load_ident_files==0,
- SAMorris = [];
- ccac = [mss cc ac];
- for i=1:size(ccac,2),
- [SAmeas, SAMorris(:,:,i)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], [ccac(:,i)],nliv);
- end
- SAcc = squeeze(SAMorris(:,1,:))';
- SAcc = SAcc./(max(SAcc')'*ones(1,npT));
- save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAcc','cc','ir_cc','ic_cc','-append')
- save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'ac','ir_ac','ic_ac','-append')
- else
- load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAcc','cc','ir_cc','ic_cc')
- load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'ac','ir_ac','ic_ac')
- end
-
- figure,
-% boxplot(SAcc,'whis',10,'symbol','r.')
- myboxplot(SAcc,[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 1])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('EET All moments')
- saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_moments'])
- eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_moments']);
- eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_moments']);
-% close(gcf),
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% MORRIS FOR DERIVATIVES
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-% if opt_gsa.load_ident_files==0,
-% for j=1:npT,
-% SAMorris = [];
-% ddd=NaN(size(lpmat,1),size(JJ,1));
-% ddd(istable,:) = squeeze(JJ(:,j,:))';
-% for i=1:size(ddd,2),
-% [SAmeas, SAMorris(:,:,i)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], [ddd(:,i)],nliv);
-% end
-% SAddd(:,:,j) = squeeze(SAMorris(:,1,:))';
-% SAddd(:,:,j) = SAddd(:,:,j)./(max(SAddd(:,:,j)')'*ones(1,npT));
-% sad(:,j) = median(SAddd(find(~isnan(squeeze(SAddd(:,1,j)))),:,j))';
-% end
-% save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAddd','sad','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAddd','sad')
-% end
-% figure,
-% contourf(sad,10), colorbar
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
-% set(gca,'yticklabel',' ','fontsize',10,'ytick',[1:npT])
-% for ip=1:npT,
-% text(ip,0.9,['D(',bayestopt_.name{ip},')'],'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% text(0.9,ip,[bayestopt_.name{ip}],'rotation',0,'HorizontalAlignment','right','interpreter','none')
-% end
-% [m,im]=max(sad);
-% iii = find((im-[1:npT])==0);
-% disp('Most identified params')
-% disp(bayestopt_.name(iii))
-
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% END OF MORRIS FOR DERIVATIVES
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['EET cross-correlations']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_cc==j);
-% iv = [iv; find(ic_cc==j)];
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAcc(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAcc(iv,:),[],'.',[],3)
-% else
-% plot(SAcc(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_cc_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_cc_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_cc_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
-
-% if opt_gsa.load_ident_files==0,
-% SAMorris = [];
-% for i=1:size(ac,2),
-% [SAmeas, SAMorris(:,:,i)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], ac(:,i),nliv);
-% end
-% %end
-% SAac = squeeze(SAMorris(:,1,:))';
-% save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAac','ac','ir_ac','ic_ac','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAac','ac','ir_ac','ic_ac')
-% end
-% figure,
-% % boxplot(SAac,'whis',10,'symbol','r.')
-% myboxplot(SAac,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title('EET All auto-correlations')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_ac'])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_ac']);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_ac']);
-% close(gcf),
-
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['EET auto-correlations']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_ac==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAac(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAac(iv,:),[],'.',[],3)
-% else
-% plot(SAac(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_ac_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_ac_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_ac_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
-% if opt_gsa.load_ident_files==0,
-% js=0;
-% %for j=1:size(tadj,1),
-% SAMorris = [];
-% for i=1:size(tadj,2),
-% js=js+1;
-% [SAmeas, SAMorris(:,:,js)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], tadj(:,i),nliv);
-% end
-% %end
-% SAM = squeeze(SAMorris(nshock+1:end,1,:));
-% for j=1:js,
-% SAtadj(:,j)=SAM(:,j)./(max(SAM(:,j))+eps);
-% end
-% SAtadj = SAtadj';
-% save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAtadj','tadj','ir_tadj','ic_tadj','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAtadj','tadj','ir_tadj','ic_tadj')
-% end
-% if opt_gsa.load_ident_files==0,
-% js=0;
-% SAMorris = [];
-% for i=1:size(iff,2),
-% js=js+1;
-% [SAmeas, SAMorriss(:,:,js)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], iff(:,i),nliv);
-% end
-% SAM = squeeze(SAMorriss(nshock+1:end,1,:));
-% for j=1:js,
-% SAIF(:,j)=SAM(:,j)./(max(SAM(:,j))+eps);
-% end
-% SAIF = SAIF';
-% save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAIF','iff','ir_if','ic_if','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAIF','iff','ir_if','ic_if')
-% end
-% figure,
-% %bar(SAtadj),
-% % boxplot(SAtadj,'whis',10,'symbol','r.')
-% myboxplot(SAtadj,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% set(gca,'ylim',[0 1])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title('All half-life')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_tadj'])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_tadj']);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_tadj']);
-% close(gcf),
-
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['EET speed of adjustment observed variables']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_tadj==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAtadj(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAtadj(iv,:),[],'.',[],3)
-% else
-% plot(SAtadj(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_tadj_varobs_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_tadj_varobs_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_tadj_varobs_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
-% ifig = 0;
-% for j=1:M_.exo_nbr,
-% if mod(j,6)==1
-% figure('name',['EET speed of adjustment shocks']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ic_tadj==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAtadj(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAtadj(iv,:),[],'.',[],3)
-% else
-% plot(SAtadj(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(M_.exo_names(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==M_.exo_nbr,
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_tadj_exo_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_tadj_exo_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_tadj_exo_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
-% figure,
-% %bar(SAIF),
-% % boxplot(SAIF,'whis',10,'symbol','r.')
-% myboxplot(SAIF,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% set(gca,'ylim',[0 1])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% ylabel('Elementary Effects')
-% title('Steady state gains (impact factors)')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_gain'])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_gain']);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_gain']);
-% close(gcf),
- %figure, bar(SAIF'), title('All Gain Relationships')
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['EET steady state gain observed series']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_if==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAIF(iv,:),'whis',10,'symbol','r.');
-% myboxplot(SAIF(iv,:),[],'.',[],10)
-% else
-% plot(SAIF(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_gain_varobs_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_gain_varobs_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_gain_varobs_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-%
-% ifig = 0;
-% for j=1:M_.exo_nbr,
-% if mod(j,6)==1
-% figure('name',['EET steady state gain shocks']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ic_if==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAIF(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAIF(iv,:),[],'.',[],3)
-% else
-% plot(SAIF(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(M_.exo_names(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==M_.exo_nbr,
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_gain_exo_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_gain_exo_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_gain_exo_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
-
- if opt_gsa.load_ident_files==0,
- SAMorris = [];
- for j=1:j0,
- [SAmeas, SAMorris(:,:,j)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], yt(:,j),nliv);
- end
-
-% SAM = squeeze(SAMorris(nshock+1:end,1,:));
- SAM = squeeze(SAMorris(1:end,1,:));
- for j=1:j0
- SAnorm(:,j)=SAM(:,j)./max(SAM(:,j));
- irex(j)=length(find(SAnorm(:,j)>0.01));
- end
- [dum, irel]=sort(irex);
-
-% SAMmu = squeeze(SAMorris(nshock+1:end,2,:));
- SAMmu = squeeze(SAMorris(1:end,2,:));
- for j=1:j0
- SAmunorm(:,j)=SAMmu(:,j)./max(SAM(:,j)); % normalised w.r.t. mu*
- end
-% SAMsig = squeeze(SAMorris(nshock+1:end,3,:));
- SAMsig = squeeze(SAMorris(1:end,3,:));
- for j=1:j0
- SAsignorm(:,j)=SAMsig(:,j)./max(SAMsig(:,j));
- end
- save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAnorm','SAmunorm','SAsignorm','-append')
- else
- load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAnorm','SAmunorm','SAsignorm')
- end
- figure, %bar(SAnorm(:,irel))
-% boxplot(SAnorm','whis',10,'symbol','r.')
- myboxplot(SAnorm',[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- set(gca,'ylim',[0 1])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- xlabel(' ')
- for ip=1:npT,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('Elementary effects in the model')
- saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_par'])
- eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_par']);
- eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_par']);
-
- figure, %bar(SAmunorm(:,irel))
-% boxplot(SAmunorm','whis',10,'symbol','r.')
- myboxplot(SAmunorm',[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- set(gca,'ylim',[-1 1])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- xlabel(' ')
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('\mu in the model')
- saveas(gcf,[OutputDirectoryName,'/',fname_,'_morrismu_par'])
- eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morrismu_par']);
- eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morrismu_par']);
- close(gcf),
-
- figure, %bar(SAsignorm(:,irel))
-% boxplot(SAsignorm','whis',10,'symbol','r.')
- myboxplot(SAsignorm',[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- set(gca,'ylim',[0 1])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- xlabel(' ')
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('\sigma in the model')
- saveas(gcf,[OutputDirectoryName,'/',fname_,'_morrissig_par'])
- eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morrissig_par']);
- eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morrissig_par']);
- close(gcf),
-
- % figure, bar(SAnorm(:,irel)')
- % set(gca,'xtick',[1:j0])
- % set(gca,'xlim',[0.5 j0+0.5])
- % title('Elementary effects relationships')
- % saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_redform'])
- % eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_redform']);
- % eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_redform']);
-
-elseif opt_gsa.morris==3,
- np=estim_params_.np;
- na=(4*np+1)*opt_gsa.Nsam;
- for j=1:j0,
- [idex(j,:), yd(j,:)] = spop_ide(lpmat, yt(:,j), opt_gsa.Nsam, 5-1);
- end
- iok=find(~isnan(yt(1:opt_gsa.Nsam,1)));
- yr=NaN*ones(size(lpmat,1),j0);
- for j=1:j0,
- ys(j,:)=yd(j,:)./max(yd(j,:));
- [dum, is]=sort(yt(iok,j));
- yr(iok(is),j)=[1:length(iok)]'./length(iok);
- yr(istable(length(iok)+1:end),j) = interp1(yt(iok,j),yr(iok,j),yt(istable(length(iok)+1:end),j),'','extrap');
- ineg=find(yr(:,j)<0);
- if any(ineg),
- [dum, is]=sort(yr(ineg,j));
- yr(ineg(is),j)=-[length(ineg):-1:1]./length(iok);
-
- end
- [idex_r(j,:), yd_r(j,:)] = spop_ide(lpmat, yr(:,j), opt_gsa.Nsam, 5-1);
- ys_r(j,:)=yd_r(j,:)./max(yd_r(j,:));
-
- end,
- figure, bar((idex.*ys)./opt_gsa.Nsam), title('Relationships')
- figure, bar((idex.*ys)'./opt_gsa.Nsam), title('Parameters')
- figure, bar((idex_r.*ys_r)./opt_gsa.Nsam), title('Relationships rank')
- figure, bar((idex_r.*ys_r)'./opt_gsa.Nsam), title('Parameters rank')
- [v0,d0]=eig(corrcoef(yt(iok,:)));
- ee=diag(d0);
- ee=ee([end:-1:1])./j0;
- i0=length(find(ee>0.01));
- v0=v0(:,[end:-1:1]);
- for j=1:i0,
- [idex_pc(j,:), yd_pc(j,:)] = spop_ide(lpmat, yt*v0(:,j), opt_gsa.Nsam, 5-1);
- end
- for j=1:i0,
- ys_pc(j,:)=yd_pc(j,:)./max(yd_pc(j,:));
- end,
- figure, bar((idex_pc.*ys_pc)./opt_gsa.Nsam), title('Relationships PCA')
- figure, bar((idex_pc.*ys_pc)'./opt_gsa.Nsam), title('Parameters PCA')
-
- [vr,dr]=eig(corrcoef(yr(iok,:)));
- er=diag(dr);
- er=er([end:-1:1])./j0;
- ir0=length(find(er>0.01));
- vr=vr(:,[end:-1:1]);
- for j=1:ir0,
- [idex_pcr(j,:), yd_pcr(j,:)] = spop_ide(lpmat, yr*vr(:,j), opt_gsa.Nsam, 5-1);
- end
- for j=1:ir0,
- ys_pcr(j,:)=yd_pcr(j,:)./max(yd_pcr(j,:));
- end,
- figure, bar((idex_pcr.*ys_pcr)./opt_gsa.Nsam), title('Relationships rank PCA')
- figure, bar((idex_pcr.*ys_pcr)'./opt_gsa.Nsam), title('Parameters rank PCA')
-
-elseif opt_gsa.morris==2, % ISKREV staff
- return,
-
-
-else, % main effects analysis
-
- if itrans==0,
- fsuffix = '';
- elseif itrans==1,
- fsuffix = '_log';
- else
- fsuffix = '_rank';
- end
-
- imap=[1:npT];
-
- x0=[lpmat0(istable,:), lpmat(istable,:)];
- nrun=length(istable);
- nest=min(250,nrun);
- nfit=min(1000,nrun);
-
-% opt_gsa.load_ident_files=0;
-
-% if opt_gsa.load_ident_files==0,
-% try
-% EET=load([OutputDirectoryName,'/SCREEN/',fname_,'_morris_IDE'],'SAvdec','vdec','ir_vdec','ic_vdec');
-% catch
-% EET=[];
-% end
-% SAvdec=zeros(size(vdec,2),npT);
-%
-% for j=1:size(vdec,2),
-% if itrans==0,
-% y0 = vdec(istable,j);
-% elseif itrans==1,
-% y0 = log_trans_(vdec(istable,j));
-% else
-% y0 = trank(vdec(istable,j));
-% end
-% if ~isempty(EET),
-% % imap=find(EET.SAvdec(j,:));
-% % [dum, isort]=sort(-EET.SAvdec(j,:));
-% imap=find(EET.SAvdec(j,:) >= (0.1.*max(EET.SAvdec(j,:))) );
-% end
-% gsa_(j) = gsa_sdp(y0(1:nest), x0(1:nest,imap), ...
-% 2, [],[],[],0,[OutputDirectoryName,'/map_vdec',fsuffix,int2str(j)], pnames);
-% if nfit>nest,
-% gsa_(j) = gsa_sdp(y0(1:nfit), x0(1:nfit,imap), ...
-% -2, gsa_(j).nvr*nest^3/nfit^3,[],[],0,[OutputDirectoryName,'/map_vdec',fsuffix,int2str(j)], pnames);
-% end
-%
-% SAvdec(j,imap)=gsa_(j).si;
-% imap_vdec{j}=imap;
-% end
-% save([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_vdec','SAvdec','vdec','ir_vdec','ic_vdec','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_vdec','SAvdec','vdec','ir_vdec','ic_vdec')
-% end
-% figure,
-% % boxplot(SAvdec,'whis',10,'symbol','r.')
-% myboxplot(SAvdec,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Main effects variance decomposition ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_vdec',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_vdec',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_vdec',fsuffix]);
-% close(gcf),
-%
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['Main effects observed variance decomposition ',fsuffix]);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_vdec==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAvdec(iv,:),'whis',10,'symbol','r.');
-% myboxplot(SAvdec(iv,:),[],'.',[],10)
-% else
-% plot(SAvdec(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_vdec',fsuffix,'_varobs_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_vdec',fsuffix,'_varobs_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_vdec',fsuffix,'_varobs_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-%
-% ifig = 0;
-% for j=1:M_.exo_nbr,
-% if mod(j,6)==1
-% figure('name',['Main effects shocks variance decomposition ',fsuffix]);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ic_vdec==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAvdec(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAvdec(iv,:),[],'.',[],10)
-% else
-% plot(SAvdec(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',3,'xtick',[1:np])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% set(gca,'fontsize',10)
-% end
-% title(M_.exo_names(j,:),'interpreter','none','fontsize',10)
-% if mod(j,6)==0 | j==M_.exo_nbr
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_vdec',fsuffix,'_exo_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_vdec',fsuffix,'_exo_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_vdec',fsuffix,'_exo_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
- if opt_gsa.load_ident_files==0,
- try
- EET=load([OutputDirectoryName,'/SCREEN/',fname_,'_morris_IDE'],'SAcc','ir_cc','ic_cc');
- catch
- EET=[];
- end
- ccac = stand_([mss cc ac]);
- [pcc, dd] = eig(cov(ccac(istable,:)));
- [latent, isort] = sort(-diag(dd));
- latent = -latent;
- figure, bar(latent)
- title('Eigenvalues in PCA')
- pcc=pcc(:,isort);
- ccac = ccac*pcc;
-% npca = min(40, max(find(cumsum(latent)./length(latent)<0.99))+1);
- npca = max(find(cumsum(latent)./length(latent)<0.99))+1;
- siPCA = (EET.SAcc'*abs(pcc'))';
-% siPCA = siPCA./(max(siPCA')'*ones(1,npT)).*(latent*ones(1,npT));
- siPCA = siPCA./(max(siPCA')'*ones(1,npT));
-% siPCA = sum(siPCA,1);
-% siPCA = siPCA./max(siPCA);
- SAcc=zeros(size(ccac,2),npT);
- for j=1:npca, %size(ccac,2),
- if itrans==0,
- y0 = ccac(istable,j);
- elseif itrans==1,
- y0 = log_trans_(ccac(istable,j));
- else
- y0 = trank(ccac(istable,j));
- end
- if ~isempty(EET),
-% imap=find(EET.SAvdec(j,:));
-% [dum, isort]=sort(-EET.SAvdec(j,:));
- imap=find(siPCA(j,:) >= (0.1.*max(siPCA(j,:))) );
-% imap=find(EET.SAcc(j,:) >= (0.1.*max(EET.SAcc(j,:))) );
- end
- gsa_(j) = gsa_sdp(y0(1:nest), x0(1:nest,imap), ...
- 2, [],[],[],0,[OutputDirectoryName,'/map_cc',fsuffix,int2str(j)], pnames);
-% if nfit>nest,
-% gsa_(j) = gsa_sdp(y0(1:nfit), x0(1:nfit,imap), ...
-% -2, gsa_(j).nvr*nest^3/nfit^3,[],[],0,[OutputDirectoryName,'/map_cc',fsuffix,int2str(j)], pnames);
-% end
- SAcc(j,imap)=gsa_(j).si;
- imap_cc{j}=imap;
-
- end
- save([OutputDirectoryName,'/map_cc',fsuffix],'gsa_')
- save([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_cc','SAcc','ccac','-append')
- else
- load([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_cc','SAcc','ccac')
-
- end
-% figure,
-% % boxplot(SAcc,'whis',10,'symbol','r.')
-% myboxplot(SAcc,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% ylabel(' ')
-% title(['Main effects moments''s PCA ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_cc',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_moments',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_moments',fsuffix]);
-% close(gcf),
-
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['Main effects cross-covariances ',fsuffix]);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_cc==j);
-% iv = [iv; find(ic_cc==j)];
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAcc(iv,:),'whis',10,'symbol','r.');
-% myboxplot(SAcc(iv,:),[],'.',[],10)
-% else
-% plot(SAcc(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% set(gca,'fontsize',10)
-% end
-% title(options_.varobs(j,:),'interpreter','none','fontsize',10)
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_cc',fsuffix,'_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_cc',fsuffix,'_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_cc',fsuffix,'_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-%
-% if opt_gsa.load_ident_files==0,
-% try
-% EET=load([OutputDirectoryName,'/SCREEN/',fname_,'_morris_IDE'],'SAac','ir_ac','ic_ac');
-% catch
-% EET=[];
-% end
-% SAac=zeros(size(ac,2),npT);
-% for j=1:size(ac,2),
-% if itrans==0,
-% y0 = ac(istable,j);
-% elseif itrans==1,
-% y0 = log_trans_(ac(istable,j));
-% else
-% y0 = trank(ac(istable,j));
-% end
-% if ~isempty(EET),
-% imap=find(EET.SAac(j,:) >= (0.1.*max(EET.SAac(j,:))) );
-% end
-% % gsa_(j) = gsa_sdp_dyn( y0, lpmat(istable,:), ...
-% % gsa_flag, [],[],[],0,[OutputDirectoryName,'/map_ac',fsuffix,int2str(j)], pnames);
-% gsa_(j) = gsa_sdp(y0(1:nest), x0(1:nest,imap), ...
-% 2, [],[],[],0,[OutputDirectoryName,'/map_ac',fsuffix,int2str(j)], pnames);
-% if nfit>nest,
-% gsa_(j) = gsa_sdp(y0(1:nfit), x0(1:nfit,imap), ...
-% -2, gsa_(j).nvr*nest^3/nfit^3,[],[],0,[OutputDirectoryName,'/map_ac',fsuffix,int2str(j)], pnames);
-% end
-% SAac(j,imap)=gsa_(j).si;
-% imap_ac{j}=imap;
-%
-% end
-% save([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_ac','SAac','ac','ir_ac','ic_ac','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_ac','SAac','ac','ir_ac','ic_ac')
-% end
-%
-% figure,
-% % boxplot(SAac,'whis',10,'symbol','r.')
-% myboxplot(SAac,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Main effects 1 lag auto-covariances ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_ac',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_ac',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_ac',fsuffix]);
-% close(gcf),
-%
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['Main effects auto-covariances ',fsuffix]);
-% ifig=ifig+1;
-% iplo = 0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_ac==j);
-% %iv = [iv; find(ic_ac==j)];
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAac(iv,:),'whis',10,'symbol','r.');
-% myboxplot(SAac(iv,:),[],'.',[],10)
-% else
-% plot(SAac(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% set(gca,'fontsize',10)
-% end
-% title(options_.varobs(j,:),'interpreter','none','fontsize',10)
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_ac',fsuffix,'_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_ac',fsuffix,'_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_ac',fsuffix,'_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
-% x0=x0(:,nshock+1:end);
- imap=[1:npT];
-
-% if opt_gsa.load_ident_files==0,
-% try
-% EET=load([OutputDirectoryName,'/SCREEN/',fname_,'_morris_IDE'],'SAtadj','ir_tadj','ic_tadj');
-% ny=size(EET.SAtadj,1);
-% catch
-% EET=[];
-% end
-% SAtadj=zeros(size(tadj,2),np);
-% for j=1:size(tadj,2),
-% if itrans==0,
-% y0 = tadj(istable,j);
-% elseif itrans==1,
-% y0 = log_trans_(tadj(istable,j));
-% else
-% y0 = trank(tadj(istable,j));
-% end
-% if ~isempty(EET),
-% if size(tadj,2)~=ny,
-% jj=find(EET.ir_tadj==ir_tadj(j));
-% jj=jj(find(EET.ic_tadj(jj)==ic_tadj(j)));
-% if ~isempty(jj),
-% imap=find(EET.SAtadj(jj,:) >= (0.1.*max(EET.SAtadj(jj,:))) );
-% else
-% imap=[1:np];
-% end
-% else
-% imap=find(EET.SAtadj(j,:) >= (0.1.*max(EET.SAtadj(j,:))) );
-% end
-% end
-% % gsa_(j) = gsa_sdp_dyn( y0, lpmat(istable,:), ...
-% % gsa_flag, [],[],[],0,[OutputDirectoryName,'/map_tadj',fsuffix,int2str(j)], pnames);
-% gsa_(j) = gsa_sdp(y0(1:nest), x0(1:nest,imap), ...
-% 2, [],[],[],0,[OutputDirectoryName,'/map_tadj',fsuffix,int2str(j)], pnames);
-% if nfit>nest,
-% gsa_(j) = gsa_sdp(y0(1:nfit), x0(1:nfit,imap), ...
-% -2, gsa_(j).nvr*nest^3/nfit^3,[],[],0,[OutputDirectoryName,'/map_tadj',fsuffix,int2str(j)], pnames);
-% end
-% SAtadj(j,imap)=gsa_(j).si;
-% imap_tadj{j}=imap;
-%
-% end
-% save([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_tadj','SAtadj','tadj','ir_tadj','ic_tadj','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_tadj','SAtadj','tadj','ir_tadj','ic_tadj')
-% end
-%
-% figure,
-% % boxplot(SAtadj,'whis',10,'symbol','r.')
-% myboxplot(SAtadj,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Main effects speed of adjustment ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_tadj',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_tadj',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_tadj',fsuffix]);
-% close(gcf),
-%
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['Main effects observed speed adjustment ',fsuffix]);
-% ifig=ifig+1;
-% iplo = 0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_tadj==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAtadj(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAtadj(iv,:),[],'.',[],10)
-% else
-% plot(SAtadj(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_tadj',fsuffix,'_varobs_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_tadj',fsuffix,'_varobs_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_tadj',fsuffix,'_varobs_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-%
-% ifig = 0;
-% for j=1:M_.exo_nbr,
-% if mod(j,6)==1
-% figure('name',['Main effects shocks speed of adjustment ',fsuffix]);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ic_tadj==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAtadj(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAtadj(iv,:),[],'.',[],10)
-% else
-% plot(SAtadj(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(M_.exo_names(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==M_.exo_nbr,
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_tadj',fsuffix,'_exo_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_tadj',fsuffix,'_exo_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_tadj',fsuffix,'_exo_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-%
-%
-% if opt_gsa.load_ident_files==0,
-% try
-% EET=load([OutputDirectoryName,'/SCREEN/',fname_,'_morris_IDE'],'SAIF','ir_if','ic_if');
-% catch
-% EET=[];
-% end
-% SAif=zeros(size(iff,2),np);
-% for j=1:size(iff,2),
-% if itrans==0,
-% y0 = iff(istable,j);
-% elseif itrans==1,
-% y0 = log_trans_(iff(istable,j));
-% else
-% y0 = trank(iff(istable,j));
-% end
-% if ~isempty(EET),
-% imap=find(EET.SAIF(j,:) >= (0.1.*max(EET.SAIF(j,:))) );
-% end
-% % gsa_(j) = gsa_sdp_dyn( y0, lpmat(istable,:), ...
-% % gsa_flag, [],[],[],0,[OutputDirectoryName,'/map_if',fsuffix,int2str(j)], pnames);
-% gsa_(j) = gsa_sdp(y0(1:nest), x0(1:nest,imap), ...
-% 2, [],[],[],0,[OutputDirectoryName,'/map_if',fsuffix,int2str(j)], pnames);
-% if nfit>nest,
-% gsa_(j) = gsa_sdp(y0(1:nfit), x0(1:nfit,imap), ...
-% -2, gsa_(j).nvr*nest^3/nfit^3,[],[],0,[OutputDirectoryName,'/map_if',fsuffix,int2str(j)], pnames);
-% end
-% SAif(j,imap)=gsa_(j).si;
-% imap_if{j}=imap;
-%
-% end
-% save([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_if','SAif','iff','ir_if','ic_if','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_if','SAif','iff','ir_if','ic_if')
-% end
-%
-% figure,
-% % boxplot(SAif,'whis',10,'symbol','r.')
-% myboxplot(SAif,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Main effects impact factors ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_if',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_if',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_if',fsuffix]);
-% close(gcf),
-%
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['Main effects observed impact factors ',fsuffix]);
-% ifig=ifig+1;
-% iplo = 0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_if==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAif(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAif(iv,:),[],'.',[],10)
-% else
-% plot(SAif(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_if',fsuffix,'_varobs_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_if',fsuffix,'_varobs_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_if',fsuffix,'_varobs_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-%
-% ifig = 0;
-% for j=1:M_.exo_nbr,
-% if mod(j,6)==1
-% figure('name',['Main effects shocks impact factors ',fsuffix]);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ic_if==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAif(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAif(iv,:),[],'.',[],10)
-% else
-% plot(SAif(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(M_.exo_names(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==M_.exo_nbr
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_if',fsuffix,'_exo_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_if',fsuffix,'_exo_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_if',fsuffix,'_exo_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-% SAmom = [SAvdec' SAcc' SAac']';
-% SAdyn = [SAtadj' SAif']';
-% SAall = [SAmom(:,nshock+1:end)' SAdyn']';
-%
-% figure,
-% % boxplot(SAtadj,'whis',10,'symbol','r.')
-% myboxplot(SAmom,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:npT,
-% % text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Main effects theoretical moments ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_moments',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_moments',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_moments',fsuffix]);
-% % close(gcf),
-%
-% figure,
-% % boxplot(SAtadj,'whis',10,'symbol','r.')
-% myboxplot(SAdyn,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Main effects short-long term dynamics ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_dynamics',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_dynamics',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_dynamics',fsuffix]);
-% % close(gcf),
-%
-% figure,
-% % boxplot(SAtadj,'whis',10,'symbol','r.')
-% myboxplot(SAall,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Main effects all ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_ALL',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_ALL',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_ALL',fsuffix]);
-% % close(gcf),
-
-% for j=1:size(SAall,1),
-% SAallN(j,:)=SAall(j,:)./max(SAall(j,:));
-% end
-% SAmean=mean(SAallN);
-% for j=1:size(SAmom,1),
-% SAmomN(j,:)=SAmom(j,1:nshock)./max(SAmom(j,1:nshock));
-% end
-% SAmomN(find(isnan(SAmomN)))=0;
-% SAmeanexo=mean(SAmomN(:,1:nshock));
-
-% figure, bar(latent'*SAcc),
- figure, bar(sum(SAcc)),
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:npT,
- text(ip,-0.02*(ydum(2)),bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- % text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title(['Identifiability indices in the ',fsuffix,' moments.'],'interpreter','none')
- saveas(gcf,[OutputDirectoryName,'/',fname_,'_ident_ALL',fsuffix])
- eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_ident_ALL',fsuffix]);
- eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_ident_ALL',fsuffix]);
-
-% figure, bar(SAmeanexo),
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:nshock])
-% set(gca,'xlim',[0.5 nshock+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:nshock,
-% % text(ip,-0.02*(ydum(2)),deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% text(ip,-0.02*(ydum(2)),bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Identifiability indices for shocks',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_ident_SHOCKS',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_ident_SHOCKS',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_ident_SHOCKS',fsuffix]);
-end
-
-return
diff --git a/GSA_distrib/4.1/mc_moments.m b/GSA_distrib/4.1/mc_moments.m
deleted file mode 100644
index 0f38ff6a66ed59781ecfe2ed45cef930103abf7f..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/mc_moments.m
+++ /dev/null
@@ -1,25 +0,0 @@
-function [vdec, cc, ac] = mc_moments(mm, ss, dr)
-global options_ M_
-
- [nr1, nc1, nsam] = size(mm);
- disp('Computing theoretical moments ...')
- h = waitbar(0,'Theoretical moments ...');
-
- for j=1:nsam,
- dr.ghx = mm(:, [1:(nc1-M_.exo_nbr)],j);
- dr.ghu = mm(:, [(nc1-M_.exo_nbr+1):end], j);
- if ~isempty(ss),
- set_shocks_param(ss(j,:));
- end
- [vdec(:,:,j), corr, autocorr, z, zz] = th_moments(dr,options_.varobs);
- cc(:,:,j)=triu(corr);
- dum=[];
- for i=1:options_.ar
- dum=[dum, autocorr{i}];
- end
- ac(:,:,j)=dum;
- waitbar(j/nsam,h)
- end
- close(h)
- disp(' ')
- disp('... done !')
diff --git a/GSA_distrib/4.1/myboxplot.m b/GSA_distrib/4.1/myboxplot.m
deleted file mode 100644
index 096d1a854a7cf11e29ad0124d1daa226122c186b..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/myboxplot.m
+++ /dev/null
@@ -1,158 +0,0 @@
-
-function sout = myboxplot (data,notched,symbol,vertical,maxwhisker)
-
-% sout = myboxplot (data,notched,symbol,vertical,maxwhisker)
-
-% % % % endif
-if nargin < 5 | isempty(maxwhisker), maxwhisker = 1.5; end
-if nargin < 4 | isempty(vertical), vertical = 1; end
-if nargin < 3 | isempty(symbol), symbol = ['+','o']; end
-if nargin < 2 | isempty(notched), notched = 0; end
-
-if length(symbol)==1, symbol(2)=symbol(1); end
-
-if notched==1, notched=0.25; end
-a=1-notched;
-
-% ## figure out how many data sets we have
-if iscell(data),
- nc = length(data);
-else
-% if isvector(data), data = data(:); end
- nc = size(data,2);
-end
-
-% ## compute statistics
-% ## s will contain
-% ## 1,5 min and max
-% ## 2,3,4 1st, 2nd and 3rd quartile
-% ## 6,7 lower and upper confidence intervals for median
-s = zeros(7,nc);
-box = zeros(1,nc);
-whisker_x = ones(2,1)*[1:nc,1:nc];
-whisker_y = zeros(2,2*nc);
-outliers_x = [];
-outliers_y = [];
-outliers2_x = [];
-outliers2_y = [];
-
-for i=1:nc
- % ## Get the next data set from the array or cell array
- if iscell(data)
- col = data{i}(:);
- else
- col = data(:,i);
- end
-% ## Skip missing data
-% % % % % % % col(isnan(col) | isna (col)) = [];
- col(isnan(col)) = [];
-
- % ## Remember the data length
- nd = length(col);
- box(i) = nd;
- if (nd > 1)
-% ## min,max and quartiles
-% s(1:5,i) = statistics(col)(1:5);
-s(1,i)=min(col);
-s(5,i)=max(col);
-s(2,i)=myprctilecol(col,25);
-s(3,i)=myprctilecol(col,50);
-s(4,i)=myprctilecol(col,75);
-
-
-
-
-
-
-
-
-% ## confidence interval for the median
- est = 1.57*(s(4,i)-s(2,i))/sqrt(nd);
- s(6,i) = max([s(3,i)-est, s(2,i)]);
- s(7,i) = min([s(3,i)+est, s(4,i)]);
-% ## whiskers out to the last point within the desired inter-quartile range
- IQR = maxwhisker*(s(4,i)-s(2,i));
- whisker_y(:,i) = [min(col(col >= s(2,i)-IQR)); s(2,i)];
- whisker_y(:,nc+i) = [max(col(col <= s(4,i)+IQR)); s(4,i)];
-% ## outliers beyond 1 and 2 inter-quartile ranges
- outliers = col((col < s(2,i)-IQR & col >= s(2,i)-2*IQR) | (col > s(4,i)+IQR & col <= s(4,i)+2*IQR));
- outliers2 = col(col < s(2,i)-2*IQR | col > s(4,i)+2*IQR);
- outliers_x = [outliers_x; i*ones(size(outliers))];
- outliers_y = [outliers_y; outliers];
- outliers2_x = [outliers2_x; i*ones(size(outliers2))];
- outliers2_y = [outliers2_y; outliers2];
- elseif (nd == 1)
-% ## all statistics collapse to the value of the point
- s(:,i) = col;
-% ## single point data sets are plotted as outliers.
- outliers_x = [outliers_x; i];
- outliers_y = [outliers_y; col];
- else
-% ## no statistics if no points
- s(:,i) = NaN;
- end
-end
-% % % % if isempty(outliers2_y)
-% % % % outliers2_y=
-% ## Note which boxes don't have enough stats
-chop = find(box <= 1);
-
-% ## Draw a box around the quartiles, with width proportional to the number of
-% ## items in the box. Draw notches if desired.
-box = box*0.23/max(box);
-quartile_x = ones(11,1)*[1:nc] + [-a;-1;-1;1;1;a;1;1;-1;-1;-a]*box;
-quartile_y = s([3,7,4,4,7,3,6,2,2,6,3],:);
-
-% ## Draw a line through the median
-median_x = ones(2,1)*[1:nc] + [-a;+a]*box;
-% median_x=median(col);
-median_y = s([3,3],:);
-
-% ## Chop all boxes which don't have enough stats
-quartile_x(:,chop) = [];
-quartile_y(:,chop) = [];
-whisker_x(:,[chop,chop+nc]) = [];
-whisker_y(:,[chop,chop+nc]) = [];
-median_x(:,chop) = [];
-median_y(:,chop) = [];
-% % % %
-% ## Add caps to the remaining whiskers
-cap_x = whisker_x;
-cap_x(1,:) =cap_x(1,:)- 0.05;
-cap_x(2,:) =cap_x(2,:)+ 0.05;
-cap_y = whisker_y([1,1],:);
-
-% #quartile_x,quartile_y
-% #whisker_x,whisker_y
-% #median_x,median_y
-% #cap_x,cap_y
-%
-% ## Do the plot
-
-mm=min(min(data));
-MM=max(max(data));
-
-if vertical
- plot (quartile_x, quartile_y, 'b', ...
- whisker_x, whisker_y, 'b--', ...
- cap_x, cap_y, 'k', ...
- median_x, median_y, 'r', ...
- outliers_x, outliers_y, [symbol(1),'r'], ...
- outliers2_x, outliers2_y, [symbol(2),'r']);
- set(gca,'XTick',1:nc);
- set(gca, 'XLim', [0.5, nc+0.5]);
- set(gca, 'YLim', [mm-(MM-mm)*0.05-eps, MM+(MM-mm)*0.05+eps]);
-
-else
-% % % % % plot (quartile_y, quartile_x, "b;;",
-% % % % % whisker_y, whisker_x, "b;;",
-% % % % % cap_y, cap_x, "b;;",
-% % % % % median_y, median_x, "r;;",
-% % % % % outliers_y, outliers_x, [symbol(1),"r;;"],
-% % % % % outliers2_y, outliers2_x, [symbol(2),"r;;"]);
-end
-
-if nargout,
- sout=s;
-end
-% % % endfunction
\ No newline at end of file
diff --git a/GSA_distrib/4.1/myprctilecol.m b/GSA_distrib/4.1/myprctilecol.m
deleted file mode 100644
index d99d5ad5009d0081ba192acfc1595b2e054f8536..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/myprctilecol.m
+++ /dev/null
@@ -1,20 +0,0 @@
-function y = myprctilecol(x,p);
-xx = sort(x);
-[m,n] = size(x);
-
-if m==1 | n==1
- m = max(m,n);
- if m == 1,
- y = x*ones(length(p),1);
- return;
- end
- n = 1;
- q = 100*(0.5:m - 0.5)./m;
- xx = [min(x); xx(:); max(x)];
-else
- q = 100*(0.5:m - 0.5)./m;
- xx = [min(x); xx; max(x)];
-end
-
-q = [0 q 100];
-y = interp1(q,xx,p);
\ No newline at end of file
diff --git a/GSA_distrib/4.1/norm_inv.m b/GSA_distrib/4.1/norm_inv.m
deleted file mode 100644
index e676be94edb12acb24a3719eb97af6b80e02d517..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/norm_inv.m
+++ /dev/null
@@ -1,49 +0,0 @@
-function invp = norm_inv(x, m, sd)
-% PURPOSE: computes the quantile (inverse of the CDF)
-% for each component of x with mean m, standard deviation sd
-%---------------------------------------------------
-% USAGE: invp = norm_inv(x,m,v)
-% where: x = variable vector (nx1)
-% m = mean vector (default=0)
-% sd = standard deviation vector (default=1)
-%---------------------------------------------------
-% RETURNS: invp (nx1) vector
-%---------------------------------------------------
-% SEE ALSO: norm_d, norm_rnd, norm_inv, norm_cdf
-%---------------------------------------------------
-
-% Written by KH (Kurt.Hornik@ci.tuwien.ac.at) on Oct 26, 1994
-% Copyright Dept of Probability Theory and Statistics TU Wien
-% Converted to MATLAB by JP LeSage, jpl@jpl.econ.utoledo.edu
-
- if nargin > 3
- error ('Wrong # of arguments to norm_inv');
- end
-
- [r, c] = size (x);
- s = r * c;
-
- if (nargin == 1)
- m = zeros(1,s);
- sd = ones(1,s);
- end
-
-
- if length(m)==1,
- m = repmat(m,1,s);
- end
- if length(sd)==1,
- sd = repmat(sd,1,s);
- end
- x = reshape(x,1,s);
- m = reshape(m,1,s);
- sd = reshape(sd,1,s);
-
- invp = zeros (1,s);
-
- invp = m + sd .* (sqrt(2) * erfinv(2 * x - 1));
-
-
-
- invp = reshape (invp, r, c);
-
diff --git a/GSA_distrib/4.1/optget.m b/GSA_distrib/4.1/optget.m
deleted file mode 100644
index b2893e2ceece29d6d08e7b9657ab54d2632502e8..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/optget.m
+++ /dev/null
@@ -1,39 +0,0 @@
-% OPTGET Utility to get previously set function default values
-% USAGE
-% optvalue=optget(funcname,optname,optvalue);
-% INPUTS
-% funcname : name of function
-% optname : name of option
-% optval : option value
-% OUTPUT
-% optval : the current value of the option
-%
-% If the named field is not already defined, it will be set to
-% optvalue, but optvalue has no effect if the field has already
-% been set. Use OPTSET to change a previously set field.
-%
-% optget(funcname) returns the current values of the options structure.
-
-% Copyright (c) 1997-2000, Paul L. Fackler & Mario J. Miranda
-% paul_fackler@ncsu.edu, miranda.4@osu.edu
-
-function optvalue = optget(funcname,optname,optvalue)
-
-funcname = lower(funcname);
-optvar=[funcname '_options'];
-eval(['global ' optvar]) % declare a global variable
-
-if nargin==1 % return the whole option structure
- optvalue=(eval(optvar));
- return
-end
-
-optname = lower(optname);
-% if structure is empty or the named field does not exist
-% set to the value passed
-if isempty(eval(optvar)) | ~isfield(eval(optvar),optname)
- eval([optvar '.' optname '=optvalue;']);
-% otherwise return the value in the field
-else
- optvalue = eval([optvar '.' optname]);
-end
diff --git a/GSA_distrib/4.1/prior_draw_gsa.m b/GSA_distrib/4.1/prior_draw_gsa.m
deleted file mode 100644
index 278e1e23775e008e7cc37cc7865efe6e441fb67c..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/prior_draw_gsa.m
+++ /dev/null
@@ -1,105 +0,0 @@
-function pdraw = prior_draw_gsa(init,rdraw)
-% Draws from the prior distributions
-% Adapted by M. Ratto from prior_draw (of DYNARE, copyright M. Juillard),
-% for use with Sensitivity Toolbox for DYNARE
-%
-%
-% INPUTS
-% o init [integer] scalar equal to 1 (first call) or 0.
-% o rdraw
-%
-% OUTPUTS
-% o pdraw [double] draw from the joint prior density.
-%
-% ALGORITHM
-% ...
-%
-% SPECIAL REQUIREMENTS
-% MATLAB Statistics Toolbox
-%
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-% global M_ options_ estim_params_ bayestopt_
-global bayestopt_
-persistent npar pshape p6 p7 p3 p4 lbcum ubcum
-
-if init
- pshape = bayestopt_.pshape;
- p6 = bayestopt_.p6;
- p7 = bayestopt_.p7;
- p3 = bayestopt_.p3;
- p4 = bayestopt_.p4;
- npar = length(p6);
- pdraw = zeros(npar,1);
- lbcum = zeros(npar,1);
- ubcum = ones(npar,1);
-
- % set bounds for cumulative probabilities
- for i = 1:npar
- switch pshape(i)
- case 5% Uniform prior.
- p4(i) = min(p4(i),bayestopt_.ub(i));
- p3(i) = max(p3(i),bayestopt_.lb(i));
- case 3% Gaussian prior.
- lbcum(i) = 0.5 * erfc(-(bayestopt_.lb(i)-p6(i))/p7(i) ./ sqrt(2));;
- ubcum(i) = 0.5 * erfc(-(bayestopt_.ub(i)-p6(i))/p7(i) ./ sqrt(2));;
- case 2% Gamma prior.
- lbcum(i) = gamm_cdf((bayestopt_.lb(i)-p3(i))/p7(i),p6(i));
- ubcum(i) = gamm_cdf((bayestopt_.ub(i)-p3(i))/p7(i),p6(i));
- case 1% Beta distribution (TODO: generalized beta distribution)
- lbcum(i) = betainc((bayestopt_.lb(i)-p3(i))./(p4(i)-p3(i)),p6(i),p7(i));
- ubcum(i) = betainc((bayestopt_.ub(i)-p3(i))./(p4(i)-p3(i)),p6(i),p7(i));
- case 4% INV-GAMMA1 distribution
- % TO BE CHECKED
- lbcum(i) = gamm_cdf((1/(bayestopt_.ub(i)-p3(i))^2)/(2/p6(i)),p7(i)/2);
- ubcum(i) = gamm_cdf((1/(bayestopt_.lb(i)-p3(i))^2)/(2/p6(i)),p7(i)/2);
- case 6% INV-GAMMA2 distribution
- % TO BE CHECKED
- lbcum(i) = gamm_cdf((1/(bayestopt_.ub(i)-p3(i)))/(2/p6(i)),p7(i)/2);
- ubcum(i) = gamm_cdf((1/(bayestopt_.lb(i)-p3(i)))/(2/p6(i)),p7(i)/2);
- otherwise
- % Nothing to do here.
- end
- end
- return
-end
-
-
-for i = 1:npar
- rdraw(:,i) = rdraw(:,i).*(ubcum(i)-lbcum(i))+lbcum(i);
- switch pshape(i)
- case 5% Uniform prior.
- pdraw(:,i) = rdraw(:,i)*(p4(i)-p3(i)) + p3(i);
- case 3% Gaussian prior.
- pdraw(:,i) = norm_inv(rdraw(:,i),p6(i),p7(i));
- case 2% Gamma prior.
- pdraw(:,i) = gamm_inv(rdraw(:,i),p6(i),p7(i))+p3(i);
- case 1% Beta distribution (TODO: generalized beta distribution)
- pdraw(:,i) = beta_inv(rdraw(:,i),p6(i),p7(i))*(p4(i)-p3(i))+p3(i);
- case 4% INV-GAMMA1 distribution
- % TO BE CHECKED
- pdraw(:,i) = sqrt(1./gamm_inv(rdraw(:,i),p7(i)/2,2/p6(i)))+p3(i);
- case 6% INV-GAMMA2 distribution
- % TO BE CHECKED
- pdraw(:,i) = 1./gamm_inv(rdraw(:,i),p7(i)/2,2/p6(i))+p3(i);
- otherwise
- % Nothing to do here.
- end
-end
-
-
diff --git a/GSA_distrib/4.1/priorcdf.m b/GSA_distrib/4.1/priorcdf.m
deleted file mode 100644
index 53d8ec34d39523151df6b3d9f9909d024f7de7a3..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/priorcdf.m
+++ /dev/null
@@ -1,50 +0,0 @@
-function [xcum] = priorcdf(para, pshape, p6, p7, p3, p4)
-% This procedure transforms x vectors into cumulative values
-% pshape: 0 is point mass, both para and p2 are ignored
-% 1 is BETA(mean,stdd)
-% 2 is GAMMA(mean,stdd)
-% 3 is NORMAL(mean,stdd)
-% 4 is INVGAMMA(s^2,nu)
-% 5 is UNIFORM [p1,p2]
-% Adapted by M. Ratto from MJ priordens.m
-
-nprio = length(pshape);
-
-i = 1;
-while i <= nprio;
- a = 0;
- b = 0;
- if pshape(i) == 1; % (generalized) BETA Prior
-% mu = (p1(i)-p3(i))/(p4(i)-p3(i));
-% stdd = p2(i)/(p4(i)-p3(i));
-% a = (1-mu)*mu^2/stdd^2 - mu;
-% b = a*(1/mu - 1);
- %lnprior = lnprior + lpdfgbeta(para(i),a,b,p3(i),p4(i)) ;
- para(:,i) = (para(:,i)-p3(i))./(p4(i)-p3(i));
-% xcum(:,i) = betacdf(para(:,i),a,b) ;
- xcum(:,i) = betainc(para(:,i),p6(i),p7(i));
- elseif pshape(i) == 2; % GAMMA PRIOR
-% b = p2(i)^2/(p1(i)-p3(i));
-% a = (p1(i)-p3(i))/b;
- %lnprior = lnprior + lpdfgam(para(i)-p3(i),a,b);
-% xcum(:,i) = gamcdf(para(:,i)-p3(i),a,b);
- xcum(:,i) = gamm_cdf((para(:,i)-p3(i))./p7(i),p6(i));
- elseif pshape(i) == 3; % GAUSSIAN PRIOR
- %lnprior = lnprior + lpdfnorm(para(i),p1(i),p2(i));
-% xcum(:,i) = normcdf(para(:,i),p1(i),p2(i));
- xcum(:,i) = 0.5 * erfc(-(para(:,i)-p6(i))/p7(i) ./ sqrt(2));
- elseif pshape(i) == 4; % INVGAMMA1 PRIOR
- %lnprior = lnprior + lpdfig1(para(i),p1(i),p2(i));
-% xcum(:,i) = gamcdf(1/para(:,i).^2,p2(i)/2,2/p1(i));
- xcum(:,i) = gamm_cdf((1./(para(:,i)-p3(i)).^2)/(2/p6(i)),p7(i)/2);
- elseif pshape(i) == 5; % UNIFORM PRIOR
- %lnprior = lnprior + log(1/(p2(i)-p1(i)));
- xcum(:,i) = (para(:,i)-p3(i))./(p4(i)-p3(i));
- elseif pshape(i) == 6; % INVGAMMA2 PRIOR
-% lnprior = lnprior + lpdfig2(para(i),p1(i),p2(i));
-% xcum(:,i) = gamcdf(1/para(:,i),p2(i)/2,2/p1(i));
- xcum(:,i) = gamm_cdf((1./(para(:,i)-p3(i)))./(2/p6(i)),p7(i)/2);
- end;
- i = i+1;
-end;
-
diff --git a/GSA_distrib/4.1/read_data.m b/GSA_distrib/4.1/read_data.m
deleted file mode 100644
index f54f66cb67269238108c8d93383d5e0cdf66a458..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/read_data.m
+++ /dev/null
@@ -1,39 +0,0 @@
-function [gend, data] = read_data
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global options_ bayestopt_
-
-rawdata = read_variables(options_.datafile,options_.varobs,[],options_.xls_sheet,options_.xls_range);
-
-options_ = set_default_option(options_,'nobs',size(rawdata,1)-options_.first_obs+1);
-gend = options_.nobs;
-
-rawdata = rawdata(options_.first_obs:options_.first_obs+gend-1,:);
-if options_.loglinear == 1 & ~options_.logdata
- rawdata = log(rawdata);
-end
-if options_.prefilter == 1
- bayestopt_.mean_varobs = mean(rawdata,1);
- data = transpose(rawdata-ones(gend,1)*bayestopt_.mean_varobs);
-else
- data = transpose(rawdata);
-end
-
-if ~isreal(rawdata)
- error(['There are complex values in the data. Probably a wrong' ...
- ' transformation'])
-end
diff --git a/GSA_distrib/4.1/redform_map.m b/GSA_distrib/4.1/redform_map.m
deleted file mode 100644
index 2350c599356326ea0f25014ff44899f4fece0e81..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/redform_map.m
+++ /dev/null
@@ -1,351 +0,0 @@
-function redform_map(dirname)
-%function redform_map(dirname)
-% inputs (from opt_gsa structure
-% anamendo = options_gsa_.namendo;
-% anamlagendo = options_gsa_.namlagendo;
-% anamexo = options_gsa_.namexo;
-% iload = options_gsa_.load_redform;
-% pprior = options_gsa_.pprior;
-% ilog = options_gsa_.logtrans_redform;
-% threshold = options_gsa_.threshold_redform;
-% ksstat = options_gsa_.ksstat_redform;
-% alpha2 = options_gsa_.alpha2_redform;
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global M_ oo_ estim_params_ options_ bayestopt_
-
-options_gsa_ = options_.opt_gsa;
-
-anamendo = options_gsa_.namendo;
-anamlagendo = options_gsa_.namlagendo;
-anamexo = options_gsa_.namexo;
-iload = options_gsa_.load_redform;
-pprior = options_gsa_.pprior;
-ilog = options_gsa_.logtrans_redform;
-threshold = options_gsa_.threshold_redform;
-ksstat = options_gsa_.ksstat_redform;
-alpha2 = options_gsa_.alpha2_redform;
-
-pnames = M_.param_names(estim_params_.param_vals(:,1),:);
-if nargin==0,
- dirname='';
-end
-
-if pprior
- load([dirname,'/',M_.fname,'_prior']);
- adir=[dirname '/redform_stab'];
-else
- load([dirname,'/',M_.fname,'_mc']);
- adir=[dirname '/redform_mc'];
-end
-if ~exist('T')
- stab_map_(dirname);
-if pprior
- load([dirname,'/',M_.fname,'_prior'],'T');
-else
- load([dirname,'/',M_.fname,'_mc'],'T');
-end
-end
-if isempty(dir(adir))
- mkdir(adir)
-end
-adir0=pwd;
-%cd(adir)
-
-nspred=size(T,2)-M_.exo_nbr;
-x0=lpmat(istable,:);
-[kn, np]=size(x0);
-offset = length(bayestopt_.pshape)-np;
-if options_gsa_.prior_range,
- pshape=5*(ones(np,1));
- pd = [NaN(np,1) NaN(np,1) bayestopt_.lb(offset+1:end) bayestopt_.ub(offset+1:end)];
-else
- pshape = bayestopt_.pshape(offset+1:end);
- pd = [bayestopt_.p6(offset+1:end) bayestopt_.p7(offset+1:end) bayestopt_.p3(offset+1:end) bayestopt_.p4(offset+1:end)];
-end
-
-nsok = length(find(M_.lead_lag_incidence(M_.maximum_lag,:)));
-clear lpmat lpmat0 egg iunstable yys
-js=0;
-for j=1:size(anamendo,1)
- namendo=deblank(anamendo(j,:));
- iendo=strmatch(namendo,M_.endo_names(oo_.dr.order_var,:),'exact');
- ifig=0;
- iplo=0;
- for jx=1:size(anamexo,1)
- namexo=deblank(anamexo(jx,:));
- iexo=strmatch(namexo,M_.exo_names,'exact');
-
- if ~isempty(iexo),
- %y0=squeeze(T(iendo,iexo+nspred,istable));
- y0=squeeze(T(iendo,iexo+nspred,:));
- if (max(y0)-min(y0))>1.e-10,
- if mod(iplo,9)==0,
- ifig=ifig+1;
- hfig = figure('name',[namendo,' vs. shocks ',int2str(ifig)]);
- iplo=0;
- end
- iplo=iplo+1;
- js=js+1;
- xdir0 = [adir,'/',namendo,'_vs_', namexo];
- if ilog==0,
- if isempty(threshold)
- si(:,js) = redform_private(x0, y0, pshape, pd, iload, pnames, namendo, namexo, xdir0);
- else
- iy=find( (y0>threshold(1)) & (y0<threshold(2)));
- iyc=find( (y0<=threshold(1)) | (y0>=threshold(2)));
- xdir = [xdir0,'_cut'];
- if ~isempty(iy),
- si(:,js) = redform_private(x0(iy,:), y0(iy), pshape, pd, iload, pnames, namendo, namexo, xdir);
- end
- if ~isempty(iy) & ~isempty(iyc)
- delete([xdir, '/*cut*.*'])
- [proba, dproba] = stab_map_1(x0, iy, iyc, 'cut',0);
- indsmirnov = find(dproba>ksstat);
- stab_map_1(x0, iy, iyc, 'cut',1,indsmirnov,xdir);
- stab_map_2(x0(iy,:),alpha2,'cut',xdir)
- stab_map_2(x0(iyc,:),alpha2,'trim',xdir)
- end
- end
- else
- [yy, xdir] = log_trans_(y0,xdir0);
- silog(:,js) = redform_private(x0, yy, pshape, pd, iload, pnames, namendo, namexo, xdir);
- end
-
- figure(hfig)
- subplot(3,3,iplo),
- if ilog,
- [saso, iso] = sort(-silog(:,js));
- bar([silog(iso(1:min(np,10)),js)])
- logflag='log';
- else
- [saso, iso] = sort(-si(:,js));
- bar(si(iso(1:min(np,10)),js))
- logflag='';
- end
- %set(gca,'xticklabel',pnames(iso(1:min(np,10)),:),'fontsize',8)
- set(gca,'xticklabel',' ','fontsize',10)
- set(gca,'xlim',[0.5 10.5])
- for ip=1:min(np,10),
- text(ip,-0.02,deblank(pnames(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- title([logflag,' ',namendo,' vs. ',namexo],'interpreter','none')
- if iplo==9,
- saveas(gcf,[dirname,'/',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)]);
- close(gcf)
- end
-
- end
- end
- end
- if iplo<9 & iplo>0 & ifig,
- saveas(gcf,[dirname,'/',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)]);
- close(gcf)
- end
- ifig=0;
- iplo=0;
- for je=1:size(anamlagendo,1)
- namlagendo=deblank(anamlagendo(je,:));
- ilagendo=strmatch(namlagendo,M_.endo_names(oo_.dr.order_var(oo_.dr.nstatic+1:oo_.dr.nstatic+nsok),:),'exact');
-
- if ~isempty(ilagendo),
- %y0=squeeze(T(iendo,ilagendo,istable));
- y0=squeeze(T(iendo,ilagendo,:));
- if (max(y0)-min(y0))>1.e-10,
- if mod(iplo,9)==0,
- ifig=ifig+1;
- hfig = figure('name',[namendo,' vs. lags ',int2str(ifig)]);
- iplo=0;
- end
- iplo=iplo+1;
- js=js+1;
- xdir0 = [adir,'/',namendo,'_vs_', namlagendo];
- if ilog==0,
- if isempty(threshold)
- si(:,js) = redform_private(x0, y0, pshape, pd, iload, pnames, namendo, namlagendo, xdir0);
- else
- iy=find( (y0>threshold(1)) & (y0<threshold(2)));
- iyc=find( (y0<=threshold(1)) | (y0>=threshold(2)));
- xdir = [xdir0,'_cut'];
- if ~isempty(iy)
- si(:,js) = redform_private(x0(iy,:), y0(iy), pshape, pd, iload, pnames, namendo, namlagendo, xdir);
- end
- if ~isempty(iy) & ~isempty(iyc),
- delete([xdir, '/*cut*.*'])
- [proba, dproba] = stab_map_1(x0, iy, iyc, 'cut',0);
- indsmirnov = find(dproba>ksstat);
- stab_map_1(x0, iy, iyc, 'cut',1,indsmirnov,xdir);
- stab_map_2(x0(iy,:),alpha2,'cut',xdir)
- stab_map_2(x0(iyc,:),alpha2,'trim',xdir)
- end
- end
- else
- [yy, xdir] = log_trans_(y0,xdir0);
- silog(:,js) = redform_private(x0, yy, pshape, pd, iload, pnames, namendo, namlagendo, xdir);
- end
-
- figure(hfig),
- subplot(3,3,iplo),
- if ilog,
- [saso, iso] = sort(-silog(:,js));
- bar([silog(iso(1:min(np,10)),js)])
- logflag='log';
- else
- [saso, iso] = sort(-si(:,js));
- bar(si(iso(1:min(np,10)),js))
- logflag='';
- end
- %set(gca,'xticklabel',pnames(iso(1:min(np,10)),:),'fontsize',8)
- set(gca,'xticklabel',' ','fontsize',10)
- set(gca,'xlim',[0.5 10.5])
- for ip=1:min(np,10),
- text(ip,-0.02,deblank(pnames(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- title([logflag,' ',namendo,' vs. ',namlagendo,'(-1)'],'interpreter','none')
- if iplo==9,
- saveas(gcf,[dirname,'/',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)]);
- close(gcf)
- end
-
- end
- end
- end
- if iplo<9 & iplo>0 & ifig,
- saveas(gcf,[dirname,'/',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)]);
- close(gcf)
- end
-end
-
-if ilog==0,
-figure, %bar(si)
-% boxplot(si','whis',10,'symbol','r.')
-myboxplot(si',[],'.',[],10)
-xlabel(' ')
-set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-set(gca,'xlim',[0.5 np+0.5])
-set(gca,'ylim',[0 1])
-set(gca,'position',[0.13 0.2 0.775 0.7])
-for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-end
-title('Reduced form GSA')
-
-saveas(gcf,[dirname,'/',M_.fname,'_redform_gsa'])
-eval(['print -depsc2 ' dirname,'/',M_.fname,'_redform_gsa']);
-eval(['print -dpdf ' dirname,'/',M_.fname,'_redform_gsa']);
-
-else
-figure, %bar(silog)
-% boxplot(silog','whis',10,'symbol','r.')
-myboxplot(silog',[],'.',[],10)
-set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-xlabel(' ')
-set(gca,'xlim',[0.5 np+0.5])
-set(gca,'ylim',[0 1])
-set(gca,'position',[0.13 0.2 0.775 0.7])
-for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-end
-title('Reduced form GSA - Log-transformed elements')
-
-saveas(gcf,[dirname,'/',M_.fname,'_redform_gsa_log'])
-eval(['print -depsc2 ' dirname,'/',M_.fname,'_redform_gsa_log']);
-eval(['print -dpdf ' dirname,'/',M_.fname,'_redform_gsa_log']);
-
-end
-function si = redform_private(x0, y0, pshape, pd, iload, pnames, namy, namx, xdir)
-global bayestopt_ options_
-
-opt_gsa=options_.opt_gsa;
-np=size(x0,2);
-x00=x0;
- if opt_gsa.prior_range,
- for j=1:np,
- x0(:,j)=(x0(:,j)-pd(j,3))./(pd(j,4)-pd(j,3));
- end
- else
- x0=priorcdf(x0,pshape, pd(:,1), pd(:,2), pd(:,3), pd(:,4));
- end
-
-fname=[xdir,'/map'];
-if iload==0,
- figure, hist(y0,30), title([namy,' vs. ', namx])
- if isempty(dir(xdir))
- mkdir(xdir)
- end
- saveas(gcf,[xdir,'/', namy,'_vs_', namx])
- eval(['print -depsc2 ' xdir,'/', namy,'_vs_', namx]);
- eval(['print -dpdf ' xdir,'/', namy,'_vs_', namx]);
- close(gcf)
-% gsa_ = gsa_sdp_dyn(y0, x0, -2, [],[],[],1,fname, pnames);
- nrun=length(y0);
- nest=min(250,nrun);
- nfit=min(1000,nrun);
-% dotheplots = (nfit<=nest);
- gsa_ = gsa_sdp(y0(1:nest), x0(1:nest,:), 2, [],[-1 -1 -1 -1 -1 0],[],0,[fname,'_est'], pnames);
- if nfit>nest,
- gsa_ = gsa_sdp(y0(1:nfit), x0(1:nfit,:), -2, gsa_.nvr*nest^3/nfit^3,[-1 -1 -1 -1 -1 0],[],0,fname, pnames);
- end
- save([fname,'.mat'],'gsa_')
- [sidum, iii]=sort(-gsa_.si);
- gsa_.x0=x00(1:nfit,:);
- hfig=gsa_sdp_plot(gsa_,fname,pnames,iii(1:min(12,np)));
- close(hfig);
- gsa_.x0=x0(1:nfit,:);
-% copyfile([fname,'_est.mat'],[fname,'.mat'])
- figure,
- plot(y0(1:nfit),[gsa_.fit y0(1:nfit)],'.'),
- title([namy,' vs. ', namx,' fit'])
- saveas(gcf,[xdir,'/', namy,'_vs_', namx,'_fit'])
- eval(['print -depsc2 ' xdir,'/', namy,'_vs_', namx,'_fit']);
- eval(['print -dpdf ' xdir,'/', namy,'_vs_', namx,'_fit']);
- close(gcf)
- if nfit<nrun,
- npred=[nfit+1:nrun];
- yf = ss_anova_fcast(x0(npred,:), gsa_);
- figure,
- plot(y0(npred),[yf y0(npred)],'.'),
- title([namy,' vs. ', namx,' pred'])
- saveas(gcf,[xdir,'/', namy,'_vs_', namx,'_pred'])
- eval(['print -depsc2 ' xdir,'/', namy,'_vs_', namx,'_pred']);
- eval(['print -dpdf ' xdir,'/', namy,'_vs_', namx,'_pred']);
- close(gcf)
- end
-else
-% gsa_ = gsa_sdp_dyn(y0, x0, 0, [],[],[],0,fname, pnames);
- gsa_ = gsa_sdp(y0, x0, 0, [],[],[],0,fname, pnames);
- yf = ss_anova_fcast(x0, gsa_);
- figure,
- plot(y0,[yf y0],'.'),
- title([namy,' vs. ', namx,' pred'])
- saveas(gcf,[xdir,'/', namy,'_vs_', namx,'_pred'])
- eval(['print -depsc2 ' xdir,'/', namy,'_vs_', namx,'_pred']);
- eval(['print -dpdf ' xdir,'/', namy,'_vs_', namx,'_pred']);
- close(gcf)
-end
-% si = gsa_.multivariate.si;
-si = gsa_.si;
-
diff --git a/GSA_distrib/4.1/redform_screen.m b/GSA_distrib/4.1/redform_screen.m
deleted file mode 100644
index 56aae7c39e29c28f982d970f7fa4c6233accf3e9..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/redform_screen.m
+++ /dev/null
@@ -1,165 +0,0 @@
-function redform_screen(dirname)
-%function redform_map(dirname)
-% inputs (from opt_gsa structure
-% anamendo = options_gsa_.namendo;
-% anamlagendo = options_gsa_.namlagendo;
-% anamexo = options_gsa_.namexo;
-% iload = options_gsa_.load_redform;
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global M_ oo_ estim_params_ options_ bayestopt_
-
-options_gsa_ = options_.opt_gsa;
-
-anamendo = options_gsa_.namendo;
-anamlagendo = options_gsa_.namlagendo;
-anamexo = options_gsa_.namexo;
-iload = options_gsa_.load_redform;
-nliv = options_gsa_.morris_nliv;
-
-pnames = M_.param_names(estim_params_.param_vals(:,1),:);
-if nargin==0,
- dirname='';
-end
-
-load([dirname,'/',M_.fname,'_prior'],'lpmat','lpmat0','istable','T');
-
-nspred=oo_.dr.nspred;
-
-[kn, np]=size(lpmat);
-nshock = length(bayestopt_.pshape)-np;
-
-nsok = length(find(M_.lead_lag_incidence(M_.maximum_lag,:)));
-
-js=0;
-for j=1:size(anamendo,1),
- namendo=deblank(anamendo(j,:));
- iendo=strmatch(namendo,M_.endo_names(oo_.dr.order_var,:),'exact');
-
- iplo=0;
- ifig=0;
- for jx=1:size(anamexo,1)
- namexo=deblank(anamexo(jx,:));
- iexo=strmatch(namexo,M_.exo_names,'exact');
-
- if ~isempty(iexo),
- y0=teff(T(iendo,iexo+nspred,:),kn,istable);
- if ~isempty(y0),
- if mod(iplo,9)==0,
- ifig=ifig+1;
- figure('name',[namendo,' vs. shocks ',int2str(ifig)]),
- iplo=0;
- end
- iplo=iplo+1;
- js=js+1;
- subplot(3,3,iplo),
- [SAmeas, SAMorris] = Morris_Measure_Groups(np+nshock, [lpmat0 lpmat], y0,nliv);
- SAM = squeeze(SAMorris(nshock+1:end,1));
- SA(:,js)=SAM./(max(SAM)+eps);
- [saso, iso] = sort(-SA(:,js));
- bar(SA(iso(1:min(np,10)),js))
- %set(gca,'xticklabel',pnames(iso(1:min(np,10)),:),'fontsize',8)
- set(gca,'xticklabel',' ','fontsize',10)
- set(gca,'xlim',[0.5 10.5])
- for ip=1:min(np,10),
- text(ip,-0.02,deblank(pnames(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- title([namendo,' vs. ',namexo],'interpreter','none')
- if iplo==9,
- saveas(gcf,[dirname,'/',M_.fname,'_', namendo,'_vs_shock_',num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_', namendo,'_vs_shock_',num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_', namendo,'_vs_shock_',num2str(ifig)]);
- close(gcf)
- end
-
- end
- end
- end
- if iplo<9 & iplo>0 & ifig,
- saveas(gcf,[dirname,'/',M_.fname,'_', namendo,'_vs_shocks_',num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_', namendo,'_vs_shocks_',num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_', namendo,'_vs_shocks_',num2str(ifig)]);
- close(gcf)
- end
-
- iplo=0;
- ifig=0;
- for je=1:size(anamlagendo,1)
- namlagendo=deblank(anamlagendo(je,:));
- ilagendo=strmatch(namlagendo,M_.endo_names(oo_.dr.order_var(oo_.dr.nstatic+1:oo_.dr.nstatic+nsok),:),'exact');
-
- if ~isempty(ilagendo),
- y0=teff(T(iendo,ilagendo,:),kn,istable);
- if ~isempty(y0),
- if mod(iplo,9)==0,
- ifig=ifig+1;
- figure('name',[namendo,' vs. lagged endogenous ',int2str(ifig)]),
- iplo=0;
- end
- iplo=iplo+1;
- js=js+1;
- subplot(3,3,iplo),
- [SAmeas, SAMorris] = Morris_Measure_Groups(np+nshock, [lpmat0 lpmat], y0,nliv);
- SAM = squeeze(SAMorris(nshock+1:end,1));
- SA(:,js)=SAM./(max(SAM)+eps);
- [saso, iso] = sort(-SA(:,js));
- bar(SA(iso(1:min(np,10)),js))
- %set(gca,'xticklabel',pnames(iso(1:min(np,10)),:),'fontsize',8)
- set(gca,'xticklabel',' ','fontsize',10)
- set(gca,'xlim',[0.5 10.5])
- for ip=1:min(np,10),
- text(ip,-0.02,deblank(pnames(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
-
- title([namendo,' vs. ',namlagendo,'(-1)'],'interpreter','none')
- if iplo==9,
- saveas(gcf,[dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)]);
- close(gcf)
- end
- end
- end
- end
- if iplo<9 & iplo>0 & ifig,
- saveas(gcf,[dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)]);
- close(gcf)
- end
-end
-
-figure,
-%bar(SA)
-% boxplot(SA','whis',10,'symbol','r.')
-myboxplot(SA',[],'.',[],10)
-set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-set(gca,'xlim',[0.5 np+0.5])
-set(gca,'ylim',[0 1])
-set(gca,'position',[0.13 0.2 0.775 0.7])
-for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-end
-xlabel(' ')
-ylabel('Elementary Effects')
-title('Reduced form screening')
-
-saveas(gcf,[dirname,'/',M_.fname,'_redform_screen'])
-eval(['print -depsc2 ' dirname,'/',M_.fname,'_redform_screen']);
-eval(['print -dpdf ' dirname,'/',M_.fname,'_redform_screen']);
-
diff --git a/GSA_distrib/4.1/set_shocks_param.m b/GSA_distrib/4.1/set_shocks_param.m
deleted file mode 100644
index f84247d299917645863b894899ee43c7b53e9391..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/set_shocks_param.m
+++ /dev/null
@@ -1,30 +0,0 @@
-function set_shocks_param(xparam1)
- global estim_params_ M_
-
- nvx = estim_params_.nvx;
- ncx = estim_params_.ncx;
- np = estim_params_.np;
- Sigma_e = M_.Sigma_e;
- offset = 0;
- if nvx
- offset = offset + nvx;
- var_exo = estim_params_.var_exo;
- for i=1:nvx
- k = var_exo(i,1);
- Sigma_e(k,k) = xparam1(i)^2;
- end
- end
-
- if ncx
- offset = offset + estim_params_.nvn;
- corrx = estim_params_.corrx;
- for i=1:ncx
- k1 = corrx(i,1);
- k2 = corrx(i,2);
- Sigma_e(k1,k2) = xparam1(i+offset)*sqrt(Sigma_e_(k1,k1)*Sigma_e_(k2,k2));
- Sigma_e(k2,k1) = Sigma_e_(k1,k2);
- end
- end
-
-
- M_.Sigma_e = Sigma_e;
\ No newline at end of file
diff --git a/GSA_distrib/4.1/skewness.m b/GSA_distrib/4.1/skewness.m
deleted file mode 100644
index 19ce487ab85deb85797680f06fc12f8db20c9d4b..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/skewness.m
+++ /dev/null
@@ -1,7 +0,0 @@
-function s=skewness(y),
-
-% y=stand_(y);
-% s=mean(y.^3);
- m2=mean((y-mean(y)).^2);
- m3=mean((y-mean(y)).^3);
- s=m3/m2^1.5;
\ No newline at end of file
diff --git a/GSA_distrib/4.1/smirnov.m b/GSA_distrib/4.1/smirnov.m
deleted file mode 100644
index bc068aeb1046e90ee8f739deff1c256a5bc0fcba..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/smirnov.m
+++ /dev/null
@@ -1,73 +0,0 @@
-function [H,prob,d] = smirnov(x1 , x2 , alpha, iflag )
-% Smirnov test for 2 distributions
-% [H,prob,d] = smirnov(x1 , x2 , alpha, iflag )
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-
-
-if nargin<3
- alpha = 0.05;
-end
-if nargin<4,
- iflag=0;
-end
-
-% empirical cdfs.
-xmix= [x1;x2];
-bin = [-inf ; sort(xmix) ; inf];
-
-ncount1 = histc (x1 , bin);
-ncount1 = ncount1(:);
-ncount2 = histc (x2 , bin);
-ncount2 = ncount2(:);
-
-cum1 = cumsum(ncount1)./sum(ncount1);
-cum1 = cum1(1:end-1);
-
-cum2 = cumsum(ncount2)./sum(ncount2);
-cum2 = cum2(1:end-1);
-
-n1= length(x1);
-n2= length(x2);
-n = n1*n2 /(n1+n2);
-
-% Compute the d(n1,n2) statistics.
-
-if iflag==0,
- d = max(abs(cum1 - cum2));
-elseif iflag==-1
- d = max(cum2 - cum1);
-elseif iflag==1
- d = max(cum1 - cum2);
-end
-%
-% Compute P-value check H0 hypothesis
-%
-
-lam = max((sqrt(n) + 0.12 + 0.11/sqrt(n)) * d , 0);
-if iflag == 0
- j = [1:101]';
- prob = 2 * sum((-1).^(j-1).*exp(-2*lam*lam*j.^2));
-
- prob=max(prob,0);
- prob=min(1,prob);
-else
- prob = exp(-2*lam*lam);
-end
-
-H = (alpha >= prob);
diff --git a/GSA_distrib/4.1/speed.m b/GSA_distrib/4.1/speed.m
deleted file mode 100644
index faaa1de86ead1e91c71bcbf0f81f09cdc2c3e587..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/speed.m
+++ /dev/null
@@ -1,52 +0,0 @@
-function [tadj, iff] = speed(A,B,mf,p),
-% [tadj, iff] = speed(A,B,mf,p),
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-nvar=length(mf);
-nstate= size(A,1);
-nshock = size(B,2);
-nrun=size(B,3);
-
-iff=zeros(nvar,nshock,nrun);
-tadj=iff;
-disp('Computing speed of adjustement ...')
-h = waitbar(0,'Speed of adjustement...');
-
-for i=1:nrun,
- irf=zeros(nvar,nshock);
- a=squeeze(A(:,:,i));
- b=squeeze(B(:,:,i));
- IFF=inv(eye(nstate)-a)*b;
- iff(:,:,i)=IFF(mf,:);
- IF=IFF-b;
-
- t=0;
- while any(any(irf<0.5))
- t=t+1;
- IFT=((eye(nstate)-a^(t+1))*inv(eye(nstate)-a))*b-b;
- irf=IFT(mf,:)./(IF(mf,:)+eps);
- irf = irf.*(abs(IF(mf,:))>1.e-7)+(abs(IF(mf,:))<=1.e-7);
- %irf=ft(mf,:);
- tt=(irf>0.5).*t;
- tadj(:,:,i)=((tt-tadj(:,:,i))==tt).*tt+tadj(:,:,i);
- end
- waitbar(i/nrun,h)
-end
-disp(' ')
-disp('.. done !')
-close(h)
diff --git a/GSA_distrib/4.1/stab_map_.m b/GSA_distrib/4.1/stab_map_.m
deleted file mode 100644
index f525e01218377d995331e539df5ba4a55e6bbfeb..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/stab_map_.m
+++ /dev/null
@@ -1,556 +0,0 @@
-function x0 = stab_map_(OutputDirectoryName)
-%
-% function x0 = stab_map_(OutputDirectoryName)
-%
-% Mapping of stability regions in the prior ranges applying
-% Monte Carlo filtering techniques.
-%
-% INPUTS (from opt_gsa structure)
-% Nsam = MC sample size
-% fload = 0 to run new MC; 1 to load prevoiusly generated analysis
-% alpha2 = significance level for bivariate sensitivity analysis
-% [abs(corrcoef) > alpha2]
-% prepSA = 1: save transition matrices for mapping reduced form
-% = 0: no transition matrix saved (default)
-% pprior = 1: sample from prior ranges (default): sample saved in
-% _prior.mat file
-% = 0: sample from posterior ranges: sample saved in
-% _mc.mat file
-% OUTPUT:
-% x0: one parameter vector for which the model is stable.
-%
-% GRAPHS
-% 1) Pdf's of marginal distributions under the stability (dotted
-% lines) and unstability (solid lines) regions
-% 2) Cumulative distributions of:
-% - stable subset (dotted lines)
-% - unacceptable subset (solid lines)
-% 3) Bivariate plots of significant correlation patterns
-% ( abs(corrcoef) > alpha2) under the stable and unacceptable subsets
-%
-% USES lptauSEQ,
-% stab_map_1, stab_map_2
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-%global bayestopt_ estim_params_ dr_ options_ ys_ fname_
-global bayestopt_ estim_params_ options_ oo_ M_
-
-opt_gsa=options_.opt_gsa;
-
-Nsam = opt_gsa.Nsam;
-fload = opt_gsa.load_stab;
-ksstat = opt_gsa.ksstat;
-alpha2 = opt_gsa.alpha2_stab;
-prepSA = (opt_gsa.redform | opt_gsa.identification);
-pprior = opt_gsa.pprior;
-ilptau = opt_gsa.ilptau;
-nliv = opt_gsa.morris_nliv;
-ntra = opt_gsa.morris_ntra;
-
-dr_ = oo_.dr;
-%if isfield(dr_,'ghx'),
- ys_ = oo_.dr.ys;
- nspred = dr_.nspred; %size(dr_.ghx,2);
- nboth = dr_.nboth;
- nfwrd = dr_.nfwrd;
-%end
-fname_ = M_.fname;
-
-np = estim_params_.np;
-nshock = estim_params_.nvx;
-nshock = nshock + estim_params_.nvn;
-nshock = nshock + estim_params_.ncx;
-nshock = nshock + estim_params_.ncn;
-lpmat0=[];
-
-pshape = bayestopt_.pshape(nshock+1:end);
-p1 = bayestopt_.p1(nshock+1:end);
-p2 = bayestopt_.p2(nshock+1:end);
-p3 = bayestopt_.p3(nshock+1:end);
-p4 = bayestopt_.p4(nshock+1:end);
-
-if nargin==0,
- OutputDirectoryName='';
-end
-
-opt=options_;
- options_.periods=0;
- options_.nomoments=1;
- options_.irf=0;
- options_.noprint=1;
- options_.simul=0;
-if fload==0,
-% if prepSA
-% T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),Nsam/2);
-% end
-
- if isfield(dr_,'ghx'),
- egg=zeros(length(dr_.eigval),Nsam);
- end
- yys=zeros(length(dr_.ys),Nsam);
-
- if opt_gsa.morris == 1
- [lpmat, OutFact] = Sampling_Function_2(nliv, np+nshock, ntra, ones(np+nshock, 1), zeros(np+nshock,1), []);
- lpmat = lpmat.*(nliv-1)/nliv+1/nliv/2;
- Nsam=size(lpmat,1);
- lpmat0 = lpmat(:,1:nshock);
- lpmat = lpmat(:,nshock+1:end);
- elseif opt_gsa.morris==3,
- lpmat = prep_ide(Nsam,np,5);
- Nsam=size(lpmat,1);
- else
- if np<52 & ilptau>0,
- [lpmat] = lptauSEQ(Nsam,np); % lptau
- if np>30 | ilptau==2, % scrambled lptau
- for j=1:np,
- lpmat(:,j)=lpmat(randperm(Nsam),j);
- end
- end
- else %ilptau==0
- %[lpmat] = rand(Nsam,np);
- for j=1:np,
- lpmat(:,j) = randperm(Nsam)'./(Nsam+1); %latin hypercube
- end
-
- end
- end
-% try
- dummy=prior_draw_gsa(1);
-% catch
-% if pprior,
-% if opt_gsa.prior_range==0;
-% error('Some unknown prior is specified or ML estimation,: use prior_range=1 option!!');
-% end
-% end
-%
-% end
- if pprior,
- for j=1:nshock,
- if opt_gsa.morris~=1,
- lpmat0(:,j) = randperm(Nsam)'./(Nsam+1); %latin hypercube
- end
- if opt_gsa.prior_range
- lpmat0(:,j)=lpmat0(:,j).*(bayestopt_.ub(j)-bayestopt_.lb(j))+bayestopt_.lb(j);
- end
- end
- if opt_gsa.prior_range
-% if opt_gsa.identification,
-% deltx=min(0.001, 1/Nsam/2);
-% for j=1:np,
-% xdelt(:,:,j)=prior_draw_gsa(0,[lpmat0 lpmat]+deltx);
-% end
-% end
- for j=1:np,
- lpmat(:,j)=lpmat(:,j).*(bayestopt_.ub(j+nshock)-bayestopt_.lb(j+nshock))+bayestopt_.lb(j+nshock);
- end
- else
- xx=prior_draw_gsa(0,[lpmat0 lpmat]);
-% if opt_gsa.identification,
-% deltx=min(0.001, 1/Nsam/2);
-% ldum=[lpmat0 lpmat];
-% ldum = prior_draw_gsa(0,ldum+deltx);
-% for j=1:nshock+np,
-% xdelt(:,:,j)=xx;
-% xdelt(:,j,j)=ldum(:,j);
-% end
-% clear ldum
-% end
- lpmat0=xx(:,1:nshock);
- lpmat=xx(:,nshock+1:end);
- clear xx;
- end
- else
- % for j=1:nshock,
- % xparam1(j) = oo_.posterior_mode.shocks_std.(bayestopt_.name{j});
- % sd(j) = oo_.posterior_std.shocks_std.(bayestopt_.name{j});
- % lpmat0(:,j) = randperm(Nsam)'./(Nsam+1); %latin hypercube
- % lb = max(bayestopt_.lb(j), xparam1(j)-2*sd(j));
- % ub1=xparam1(j)+(xparam1(j) - lb); % define symmetric range around the mode!
- % ub = min(bayestopt_.ub(j),ub1);
- % if ub<ub1,
- % lb=xparam1(j)-(ub-xparam1(j)); % define symmetric range around the mode!
- % end
- % lpmat0(:,j) = lpmat0(:,j).*(ub-lb)+lb;
- % end
- % %
- % for j=1:np,
- % xparam1(j+nshock) = oo_.posterior_mode.parameters.(bayestopt_.name{j+nshock});
- % sd(j+nshock) = oo_.posterior_std.parameters.(bayestopt_.name{j+nshock});
- % lb = max(bayestopt_.lb(j+nshock),xparam1(j+nshock)-2*sd(j+nshock));
- % ub1=xparam1(j+nshock)+(xparam1(j+nshock) - lb); % define symmetric range around the mode!
- % ub = min(bayestopt_.ub(j+nshock),ub1);
- % if ub<ub1,
- % lb=xparam1(j+nshock)-(ub-xparam1(j+nshock)); % define symmetric range around the mode!
- % end
- % %ub = min(bayestopt_.ub(j+nshock),xparam1(j+nshock)+2*sd(j+nshock));
- % if np>30 & np<52
- % lpmat(:,j) = lpmat(randperm(Nsam),j).*(ub-lb)+lb;
- % else
- % lpmat(:,j) = lpmat(:,j).*(ub-lb)+lb;
- % end
- % end
- %load([fname_,'_mode'])
- eval(['load ' options_.mode_file ';']');
- d = chol(inv(hh));
- lp=randn(Nsam*2,nshock+np)*d+kron(ones(Nsam*2,1),xparam1');
- for j=1:Nsam*2,
- lnprior(j) = any(lp(j,:)'<=bayestopt_.lb | lp(j,:)'>=bayestopt_.ub);
- end
- ireal=[1:2*Nsam];
- ireal=ireal(find(lnprior==0));
- lp=lp(ireal,:);
- Nsam=min(Nsam, length(ireal));
- lpmat0=lp(1:Nsam,1:nshock);
- lpmat=lp(1:Nsam,nshock+1:end);
- clear lp lnprior ireal;
- end
- %
- h = waitbar(0,'Please wait...');
- istable=[1:Nsam];
- jstab=0;
- iunstable=[1:Nsam];
- iindeterm=zeros(1,Nsam);
- iwrong=zeros(1,Nsam);
- for j=1:Nsam,
- M_.params(estim_params_.param_vals(:,1)) = lpmat(j,:)';
- %try stoch_simul([]);
- try
- [Tt,Rr,SteadyState,infox{j}] = dynare_resolve(bayestopt_.restrict_var_list,...
- bayestopt_.restrict_columns,...
- bayestopt_.restrict_aux);
- if infox{j}==0,
- check1 = max(abs(feval([M_.fname '_static'],...
- SteadyState,...
- [oo_.exo_steady_state; ...
- oo_.exo_det_steady_state], M_.params))) > options_.dynatol ;
- if check1,
- error(['The seadystate values returned by ' M_.fname ...
- '_steadystate.m don''t solve the static model!' ])
- end
- end
-
-
- if ~exist('T')
- dr_=oo_.dr;
- T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),Nsam);
- egg=zeros(length(dr_.eigval),Nsam);
- end
- catch
- if isfield(oo_.dr,'eigval'),
- oo_.dr=rmfield(oo_.dr,'eigval');
- end
- if isfield(oo_.dr,'ghx'),
- oo_.dr=rmfield(oo_.dr,'ghx');
- end
- disp('No solution could be found'),
- end
- dr_ = oo_.dr;
- if isfield(dr_,'ghx'),
- egg(:,j) = sort(dr_.eigval);
- iunstable(j)=0;
- if prepSA
- jstab=jstab+1;
- T(:,:,jstab) = [dr_.ghx dr_.ghu];
-% [A,B] = ghx2transition(squeeze(T(:,:,jstab)), ...
-% bayestopt_.restrict_var_list, ...
-% bayestopt_.restrict_columns, ...
-% bayestopt_.restrict_aux);
- end
- if ~exist('nspred'),
- nspred = dr_.nspred; %size(dr_.ghx,2);
- nboth = dr_.nboth;
- nfwrd = dr_.nfwrd;
- end
- else
- istable(j)=0;
- if isfield(dr_,'eigval')
- egg(:,j) = sort(dr_.eigval);
- if exist('nspred')
- if any(isnan(egg(1:nspred,j)))
- iwrong(j)=j;
- else
- if (nboth | nfwrd) & abs(egg(nspred+1,j))<=options_.qz_criterium,
- iindeterm(j)=j;
- end
- end
- end
- else
- if exist('egg'),
- egg(:,j)=ones(size(egg,1),1).*NaN;
- end
- iwrong(j)=j;
- end
- end
- ys_=real(dr_.ys);
- yys(:,j) = ys_;
- ys_=yys(:,1);
- waitbar(j/Nsam,h,['MC iteration ',int2str(j),'/',int2str(Nsam)])
- end
- close(h)
- if prepSA,
- T=T(:,:,1:jstab);
- end
- istable=istable(find(istable)); % stable params
- iunstable=iunstable(find(iunstable)); % unstable params
- iindeterm=iindeterm(find(iindeterm)); % indeterminacy
- iwrong=iwrong(find(iwrong)); % dynare could not find solution
-
- % % map stable samples
- % istable=[1:Nsam];
- % for j=1:Nsam,
- % if any(isnan(egg(1:nspred,j)))
- % istable(j)=0;
- % else
- % if abs(egg(nspred,j))>=options_.qz_criterium; %(1-(options_.qz_criterium-1)); %1-1.e-5;
- % istable(j)=0;
- % %elseif (dr_.nboth | dr_.nfwrd) & abs(egg(nspred+1,j))<=options_.qz_criterium; %1+1.e-5;
- % elseif (nboth | nfwrd) & abs(egg(nspred+1,j))<=options_.qz_criterium; %1+1.e-5;
- % istable(j)=0;
- % end
- % end
- % end
- % istable=istable(find(istable)); % stable params
- %
- % % map unstable samples
- % iunstable=[1:Nsam];
- % for j=1:Nsam,
- % %if abs(egg(dr_.npred+1,j))>1+1.e-5 & abs(egg(dr_.npred,j))<1-1.e-5;
- % %if (dr_.nboth | dr_.nfwrd),
- % if ~any(isnan(egg(1:5,j)))
- % if (nboth | nfwrd),
- % if abs(egg(nspred+1,j))>options_.qz_criterium & abs(egg(nspred,j))<options_.qz_criterium; %(1-(options_.qz_criterium-1));
- % iunstable(j)=0;
- % end
- % else
- % if abs(egg(nspred,j))<options_.qz_criterium; %(1-(options_.qz_criterium-1));
- % iunstable(j)=0;
- % end
- % end
- % end
- % end
- % iunstable=iunstable(find(iunstable)); % unstable params
- bkpprior.pshape=bayestopt_.pshape;
- bkpprior.p1=bayestopt_.p1;
- bkpprior.p2=bayestopt_.p2;
- bkpprior.p3=bayestopt_.p3;
- bkpprior.p4=bayestopt_.p4;
- if pprior,
- if ~prepSA
- save([OutputDirectoryName '/' fname_ '_prior'], ...
- 'bkpprior','lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
- 'egg','yys','nspred','nboth','nfwrd')
- else
- save([OutputDirectoryName '/' fname_ '_prior'], ...
- 'bkpprior','lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
- 'egg','yys','T','nspred','nboth','nfwrd')
- end
-
- else
- if ~prepSA
- save([OutputDirectoryName '/' fname_ '_mc'], ...
- 'lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
- 'egg','yys','nspred','nboth','nfwrd')
- else
- save([OutputDirectoryName '/' fname_ '_mc'], ...
- 'lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
- 'egg','yys','T','nspred','nboth','nfwrd')
- end
- end
-else
- if pprior,
- filetoload=[OutputDirectoryName '/' fname_ '_prior'];
- else
- filetoload=[OutputDirectoryName '/' fname_ '_mc'];
- end
- load(filetoload,'lpmat','lpmat0','iunstable','istable','iindeterm','iwrong','egg','yys','nspred','nboth','nfwrd')
- Nsam = size(lpmat,1);
-
-
- if prepSA & isempty(strmatch('T',who('-file', filetoload),'exact')),
- h = waitbar(0,'Please wait...');
- options_.periods=0;
- options_.nomoments=1;
- options_.irf=0;
- options_.noprint=1;
- stoch_simul([]);
- %T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),length(istable));
- ntrans=length(istable);
- for j=1:ntrans,
- M_.params(estim_params_.param_vals(:,1)) = lpmat(istable(j),:)';
- %stoch_simul([]);
- [Tt,Rr,SteadyState,info] = dynare_resolve(bayestopt_.restrict_var_list,...
- bayestopt_.restrict_columns,...
- bayestopt_.restrict_aux);
- if ~exist('T')
- T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),ntrans);
- end
- dr_ = oo_.dr;
- T(:,:,j) = [dr_.ghx dr_.ghu];
- if ~exist('nspred')
- nspred = dr_.nspred; %size(dr_.ghx,2);
- nboth = dr_.nboth;
- nfwrd = dr_.nfwrd;
- end
- ys_=real(dr_.ys);
- yys(:,j) = ys_;
- ys_=yys(:,1);
- waitbar(j/ntrans,h,['MC iteration ',int2str(j),'/',int2str(ntrans)])
- end
- close(h)
- save(filetoload,'T','-append')
- elseif prepSA
- load(filetoload,'T')
- end
-end
-
-if pprior
- aname='prior_stab';
- auname='prior_unacceptable';
- aunstname='prior_unstable';
- aindname='prior_indeterm';
- awrongname='prior_wrong';
- asname='prior_stable';
-else
- aname='mc_stab';
- auname='mc_unacceptable';
- aunstname='mc_unstable';
- aindname='mc_indeterm';
- awrongname='mc_wrong';
- asname='mc_stable';
-end
-delete([OutputDirectoryName,'/',fname_,'_',aname,'_*.*']);
-%delete([OutputDirectoryName,'/',fname_,'_',aname,'_SA_*.*']);
-delete([OutputDirectoryName,'/',fname_,'_',asname,'_corr_*.*']);
-delete([OutputDirectoryName,'/',fname_,'_',auname,'_corr_*.*']);
-delete([OutputDirectoryName,'/',fname_,'_',aunstname,'_corr_*.*']);
-delete([OutputDirectoryName,'/',fname_,'_',aindname,'_corr_*.*']);
-
-if length(iunstable)>0 & length(iunstable)<Nsam,
- disp([num2str(length(istable)/Nsam*100,3),'\% of the prior support is stable.'])
- disp([num2str( (length(iunstable)-length(iwrong)-length(iindeterm) )/Nsam*100),'\% of the prior support is unstable.'])
- if ~isempty(iindeterm),
- disp([num2str(length(iindeterm)/Nsam*100,3),'\% of the prior support gives indeterminacy.'])
- end
- if ~isempty(iwrong),
- disp(' ');
- disp(['For ',num2str(length(iwrong)/Nsam*100,3),'\% of the prior support dynare could not find a solution.'])
- end
- disp(' ');
- % Blanchard Kahn
- [proba, dproba] = stab_map_1(lpmat, istable, iunstable, aname,0);
- indstab=find(dproba>ksstat);
- disp('Smirnov statistics in driving acceptable behaviour')
- for j=1:np,
- disp([M_.param_names(estim_params_.param_vals(j,1),:),' d-stat = ', num2str(dproba(j),3)])
- end
- disp(' ');
- if ~isempty(indstab)
- stab_map_1(lpmat, istable, iunstable, aname, 1, indstab, OutputDirectoryName);
- end
- ixun=iunstable(find(~ismember(iunstable,[iindeterm,iwrong])));
- if ~isempty(iindeterm),
- [proba, dproba] = stab_map_1(lpmat, [1:Nsam], iindeterm, [aname, '_indet'],0);
- indindet=find(dproba>ksstat);
- disp('Smirnov statistics in driving indeterminacy')
- for j=1:np,
- disp([M_.param_names(estim_params_.param_vals(j,1),:),' d-stat = ', num2str(dproba(j),3)])
- end
- disp(' ');
- if ~isempty(indindet)
- stab_map_1(lpmat, [1:Nsam], iindeterm, [aname, '_indet'], 1, indindet, OutputDirectoryName);
- end
- end
-
- if ~isempty(ixun),
- [proba, dproba] = stab_map_1(lpmat, [1:Nsam], ixun, [aname, '_unst'],0);
- indunst=find(dproba>ksstat);
- disp('Smirnov statistics in driving instability')
- for j=1:np,
- disp([M_.param_names(estim_params_.param_vals(j,1),:),' d-stat = ', num2str(dproba(j),3)])
- end
- disp(' ');
- if ~isempty(indunst)
- stab_map_1(lpmat, [1:Nsam], ixun, [aname, '_unst'], 1, indunst, OutputDirectoryName);
- end
- end
-
- if ~isempty(iwrong),
- [proba, dproba] = stab_map_1(lpmat, [1:Nsam], iwrong, [aname, '_wrong'],0);
- indwrong=find(dproba>ksstat);
- disp('Smirnov statistics in driving no solution')
- for j=1:np,
- disp([M_.param_names(estim_params_.param_vals(j,1),:),' d-stat = ', num2str(dproba(j),3)])
- end
- disp(' ');
- if ~isempty(indwrong)
- stab_map_1(lpmat, [1:Nsam], iwrong, [aname, '_wrong'], 1, indwrong, OutputDirectoryName);
- end
- end
-
- disp(' ')
- disp('Starting bivariate analysis:')
-
- c0=corrcoef(lpmat(istable,:));
- c00=tril(c0,-1);
-
- stab_map_2(lpmat(istable,:),alpha2, asname, OutputDirectoryName);
- if length(iunstable)>10,
- stab_map_2(lpmat(iunstable,:),alpha2, auname, OutputDirectoryName);
- end
- if length(iindeterm)>10,
- stab_map_2(lpmat(iindeterm,:),alpha2, aindname, OutputDirectoryName);
- end
- if length(ixun)>10,
- stab_map_2(lpmat(ixun,:),alpha2, aunstname, OutputDirectoryName);
- end
- if length(iwrong)>10,
- stab_map_2(lpmat(iwrong,:),alpha2, awrongname, OutputDirectoryName);
- end
-
- x0=0.5.*(bayestopt_.ub(1:nshock)-bayestopt_.lb(1:nshock))+bayestopt_.lb(1:nshock);
- x0 = [x0; lpmat(istable(1),:)'];
- if istable(end)~=Nsam
- M_.params(estim_params_.param_vals(:,1)) = lpmat(istable(1),:)';
- [oo_.dr, info] = resol(oo_.steady_state,0);
-% stoch_simul([]);
- end
-else
- if length(iunstable)==0,
- disp('All parameter values in the specified ranges are stable!')
- x0=0.5.*(bayestopt_.ub(1:nshock)-bayestopt_.lb(1:nshock))+bayestopt_.lb(1:nshock);
- x0 = [x0; lpmat(istable(1),:)'];
- else
- disp('All parameter values in the specified ranges are not acceptable!')
- x0=[];
- end
-
-end
-
-
-options_.periods=opt.periods;
-if isfield(opt,'nomoments'),
- options_.nomoments=opt.nomoments;
-end
-options_.irf=opt.irf;
-options_.noprint=opt.noprint;
-if isfield(opt,'simul'),
- options_.simul=opt.simul;
-end
-
-
-
diff --git a/GSA_distrib/4.1/stab_map_1.m b/GSA_distrib/4.1/stab_map_1.m
deleted file mode 100644
index 8813fa572d19097e74e50f8b1faaf5aa68ff29ce..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/stab_map_1.m
+++ /dev/null
@@ -1,87 +0,0 @@
-function [proba, dproba] = stab_map_1(lpmat, ibehaviour, inonbehaviour, aname, iplot, ipar, dirname)
-%function [proba, dproba] = stab_map_1(lpmat, ibehaviour, inonbehaviour, aname, iplot, ipar, dirname)
-%
-% lpmat = Monte Carlo matrix
-% ibehaviour = index of behavioural runs
-% inonbehaviour = index of non-behavioural runs
-% aname = label of the analysis
-% iplot = 1 plot cumulative distributions (default)
-% iplot = 0 no plots
-% ipar = index array of parameters to plot
-% dirname = (OPTIONAL) path of the directory where to save
-% (default: current directory)
-%
-% Plots: dotted lines for BEHAVIOURAL
-% solid lines for NON BEHAVIOURAL
-% USES smirnov
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global estim_params_ bayestopt_ M_ options_
-
-if nargin<5,
- iplot=1;
-end
-fname_ = M_.fname;
-if nargin<7,
- dirname='';;
-end
-
-nshock = estim_params_.nvx;
-nshock = nshock + estim_params_.nvn;
-nshock = nshock + estim_params_.ncx;
-nshock = nshock + estim_params_.ncn;
-
-npar=size(lpmat,2);
-ishock= npar>estim_params_.np;
-
-if nargin<6 | isempty(ipar),
- ipar=[1:npar];
-end
-nparplot=length(ipar);
-
-% Smirnov test for Blanchard;
-for j=1:npar,
- [H,P,KSSTAT] = smirnov(lpmat(ibehaviour,j),lpmat(inonbehaviour,j));
- proba(j)=P;
- dproba(j)=KSSTAT;
-end
-if iplot
- lpmat=lpmat(:,ipar);
- ftit=bayestopt_.name(ipar+nshock*(1-ishock));
-
-for i=1:ceil(nparplot/12),
- figure('name',aname),
- for j=1+12*(i-1):min(nparplot,12*i),
- subplot(3,4,j-12*(i-1))
- if ~isempty(ibehaviour),
- h=cumplot(lpmat(ibehaviour,j));
- set(h,'color',[0 0 0], 'linestyle',':')
- end
- hold on,
- if ~isempty(inonbehaviour),
- h=cumplot(lpmat(inonbehaviour,j));
- set(h,'color',[0 0 0])
- end
- title([ftit{j},'. D-stat ', num2str(dproba(ipar(j)),2)],'interpreter','none')
- end
- saveas(gcf,[dirname,'/',fname_,'_',aname,'_SA_',int2str(i)])
- eval(['print -depsc2 ' dirname '/' fname_ '_' aname '_SA_' int2str(i)]);
- eval(['print -dpdf ' dirname '/' fname_ '_' aname '_SA_' int2str(i)]);
- if options_.nograph, close(gcf), end
-end
-end
diff --git a/GSA_distrib/4.1/stab_map_2.m b/GSA_distrib/4.1/stab_map_2.m
deleted file mode 100644
index 3d1a8fa9cd39ca5b7668183156e780701ccdff81..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/stab_map_2.m
+++ /dev/null
@@ -1,97 +0,0 @@
-%function stab_map_2(x,alpha2,istab,fnam)
-function stab_map_2(x,alpha2,fnam, dirname)
-% function stab_map_2(x,alpha2,fnam, dirname)
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-%global bayestopt_ estim_params_ dr_ options_ ys_ fname_
-global bayestopt_ estim_params_ options_ oo_ M_
-
-npar=size(x,2);
-ishock= npar>estim_params_.np;
-if nargin<3,
- fnam='';
-end
-if nargin<4,
- dirname='';
-end
-
-ys_ = oo_.dr.ys;
-dr_ = oo_.dr;
-fname_ = M_.fname;
-nshock = estim_params_.nvx;
-nshock = nshock + estim_params_.nvn;
-nshock = nshock + estim_params_.ncx;
-nshock = nshock + estim_params_.ncn;
-
-c0=corrcoef(x);
-c00=tril(c0,-1);
-fig_nam_=[fname_,'_',fnam,'_corr_'];
-
-ifig=0;
-j2=0;
-if ishock==0
- npar=estim_params_.np;
-else
- npar=estim_params_.np+nshock;
-end
-for j=1:npar,
- i2=find(abs(c00(:,j))>alpha2);
- if length(i2)>0,
- for jx=1:length(i2),
- j2=j2+1;
- if mod(j2,12)==1,
- ifig=ifig+1;
- figure('name',['Correlations in the ',fnam,' sample ', num2str(ifig)]),
- end
- subplot(3,4,j2-(ifig-1)*12)
- % bar(c0(i2,j)),
- % set(gca,'xticklabel',bayestopt_.name(i2)),
- % set(gca,'xtick',[1:length(i2)])
- %plot(stock_par(ixx(nfilt+1:end,i),j),stock_par(ixx(nfilt+1:end,i),i2(jx)),'.k')
- %hold on,
- plot(x(:,j),x(:,i2(jx)),'.')
- % xlabel(deblank(estim_params_.param_names(j,:)),'interpreter','none'),
- % ylabel(deblank(estim_params_.param_names(i2(jx),:)),'interpreter','none'),
- if ishock,
- xlabel(bayestopt_.name{j},'interpreter','none'),
- ylabel(bayestopt_.name{i2(jx)},'interpreter','none'),
- else
- xlabel(bayestopt_.name{j+nshock},'interpreter','none'),
- ylabel(bayestopt_.name{i2(jx)+nshock},'interpreter','none'),
- end
- title(['cc = ',num2str(c0(i2(jx),j))])
- if (mod(j2,12)==0) & j2>0,
- saveas(gcf,[dirname,'/',fig_nam_,int2str(ifig)])
- eval(['print -depsc2 ' dirname '/' fig_nam_ int2str(ifig)]);
- eval(['print -dpdf ' dirname '/' fig_nam_ int2str(ifig)]);
- if options_.nograph, close(gcf), end
- end
- end
- end
- if (j==(npar)) & j2>0,
- saveas(gcf,[dirname,'/',fig_nam_,int2str(ifig)])
- eval(['print -depsc2 ' dirname '/' fig_nam_ int2str(ifig)]);
- eval(['print -dpdf ' dirname '/' fig_nam_ int2str(ifig)]);
- if options_.nograph, close(gcf), end
- end
-
-end
-if ifig==0,
- disp(['No correlation term >', num2str(alpha2),' found for ',fnam])
-end
-%close all
diff --git a/GSA_distrib/4.1/stand_.m b/GSA_distrib/4.1/stand_.m
deleted file mode 100644
index fb0b3fda399b0de41d620faf17510a213f653f89..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/stand_.m
+++ /dev/null
@@ -1,25 +0,0 @@
-function [y, meany, stdy] = stand_(x)
-% STAND_ Standardise a matrix by columns
-%
-% [x,my,sy]=stand(y)
-%
-% y: Time series (column matrix)
-%
-% x: standardised equivalent of y
-% my: Vector of mean values for each column of y
-% sy: Vector of standard deviations for each column of y
-%
-% Copyright (c) 2006 by JRC, European Commission, United Kingdom
-% Author : Marco Ratto
-
-
-if nargin==0,
- return;
-end
-
-for j=1:size(x,2);
-meany(j)=mean(x(find(~isnan(x(:,j))),j));
-stdy(j)=std(x(find(~isnan(x(:,j))),j));
- y(:,j)=(x(:,j)-meany(j))./stdy(j);
-end
-% end of m-file
\ No newline at end of file
diff --git a/GSA_distrib/4.1/teff.m b/GSA_distrib/4.1/teff.m
deleted file mode 100644
index 6c33706e53cee1c495bf876b5af289e4b5b35c69..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/teff.m
+++ /dev/null
@@ -1,51 +0,0 @@
-function [yt, j0, ir, ic]=teff(T,Nsam,istable)
-%
-% [yt, j0, ir, ic]=teff(T,Nsam,istable)
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-ndim = (length(size(T)));
-if ndim==3,
-if nargin==1,
- Nsam=size(T,3);
- istable = [1:Nsam]';
-end
-tmax=max(T,[],3);
-tmin=min(T,[],3);
-[ir, ic]=(find( (tmax-tmin)>1.e-8));
-j0 = length(ir);
-yt=zeros(Nsam, j0);
-
-for j=1:j0,
- y0=squeeze(T(ir(j),ic(j),:));
- %y1=ones(size(lpmat,1),1)*NaN;
- y1=ones(Nsam,1)*NaN;
- y1(istable,1)=y0;
- yt(:,j)=y1;
-end
-
-else
-tmax=max(T,[],2);
-tmin=min(T,[],2);
-ir=(find( (tmax-tmin)>1.e-8));
-j0 = length(ir);
-yt=NaN(Nsam, j0);
-yt(istable,:)=T(ir,:)';
-
-
-end
-%clear y0 y1;
diff --git a/GSA_distrib/4.1/th_moments.m b/GSA_distrib/4.1/th_moments.m
deleted file mode 100644
index 41bb18d7865567efefa2f466a988751683601fb1..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/th_moments.m
+++ /dev/null
@@ -1,66 +0,0 @@
-% Copyright (C) 2001 Michel Juillard
-%
-function [vdec, corr, autocorr, z, zz] = th_moments(dr,var_list)
- global M_ oo_ options_
-
- nvar = size(var_list,1);
- if nvar == 0
- nvar = length(dr.order_var);
- ivar = [1:nvar]';
- else
- ivar=zeros(nvar,1);
- for i=1:nvar
- i_tmp = strmatch(var_list(i,:),M_.endo_names,'exact');
- if isempty(i_tmp)
- error (['One of the variable specified does not exist']) ;
- else
- ivar(i) = i_tmp;
- end
- end
- end
-
- [gamma_y,ivar] = th_autocovariances(dr,ivar,M_, options_);
- m = dr.ys(ivar);
-
-
- i1 = find(abs(diag(gamma_y{1})) > 1e-12);
- s2 = diag(gamma_y{1});
- sd = sqrt(s2);
-
-
- z = [ m sd s2 ];
- mean = m;
- var = gamma_y{1};
-
-
-%'THEORETICAL MOMENTS';
-%'MEAN','STD. DEV.','VARIANCE');
-z;
-
-%'VARIANCE DECOMPOSITION (in percent)';
-if M_.exo_nbr>1,
-vdec = 100*gamma_y{options_.ar+2}(i1,:);
-else
-vdec = 100*ones(size(gamma_y{1}(i1,1)));
-end
-%'MATRIX OF CORRELATIONS';
-if options_.opt_gsa.useautocorr,
- corr = gamma_y{1}(i1,i1)./(sd(i1)*sd(i1)');
- corr = corr-diag(diag(corr))+diag(diag(gamma_y{1}(i1,i1)));
-else
- corr = gamma_y{1}(i1,i1);
-end
- if options_.ar > 0
-%'COEFFICIENTS OF AUTOCORRELATION';
- for i=1:options_.ar
- if options_.opt_gsa.useautocorr,
- autocorr{i} = gamma_y{i+1}(i1,i1);
- else
- autocorr{i} = gamma_y{i+1}(i1,i1).*(sd(i1)*sd(i1)');
- end
- zz(:,i) = diag(gamma_y{i+1}(i1,i1));
- end
- end
-
-
-
\ No newline at end of file
diff --git a/GSA_distrib/4.1/thet2tau.m b/GSA_distrib/4.1/thet2tau.m
deleted file mode 100644
index 5cd29f00e46947dcd2b9efe3553a8e8b3d9ec3d3..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/thet2tau.m
+++ /dev/null
@@ -1,45 +0,0 @@
-function tau = thet2tau(params, indx, indexo, flagmoments,mf,nlags,useautocorr)
-global M_ oo_ options_
-
-if nargin==1,
- indx = [1:M_.param_nbr];
- indexo = [];
-end
-
-if nargin<4,
- flagmoments=0;
-end
-if nargin<7 | isempty(useautocorr),
- useautocorr=0;
-end
-
-M_.params(indx) = params(length(indexo)+1:end);
-if ~isempty(indexo)
- M_.Sigma_e(indexo,indexo) = diag(params(1:length(indexo)).^2);
-end
-% [A(oo_.dr.order_var,oo_.dr.order_var),B(oo_.dr.order_var,:)]=dynare_resolve;
-[A,B]=dynare_resolve;
-if flagmoments==0,
-tau = [oo_.dr.ys(oo_.dr.order_var); A(:); vech(B*M_.Sigma_e*B')];
-else
-GAM = lyapunov_symm(A,B*M_.Sigma_e*B',options_.qz_criterium,options_.lyapunov_complex_threshold);
-k = find(abs(GAM) < 1e-12);
-GAM(k) = 0;
-if useautocorr,
- sy = sqrt(diag(GAM));
- sy = sy*sy';
- sy0 = sy-diag(diag(sy))+eye(length(sy));
- dum = GAM./sy0;
- tau = vech(dum(mf,mf));
-else
- tau = vech(GAM(mf,mf));
-end
-for ii = 1:nlags
- dum = A^(ii)*GAM;
- if useautocorr,
- dum = dum./sy;
- end
- tau = [tau;vec(dum(mf,mf))];
-end
-tau = [ oo_.dr.ys(oo_.dr.order_var(mf)); tau];
-end
\ No newline at end of file
diff --git a/GSA_distrib/4.1/trank.m b/GSA_distrib/4.1/trank.m
deleted file mode 100644
index a0c5bda999a6eebdf4d1b1977f1c47240d4c111d..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.1/trank.m
+++ /dev/null
@@ -1,25 +0,0 @@
-function yr = trank(y);
-% yr = trank(y);
-% yr is the rank transformation of y
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-[nr, nc] = size(y);
-for j=1:nc,
- [dum, is]=sort(y(:,j));
- yr(is,j)=[1:nr]'./nr;
-end
diff --git a/GSA_distrib/4.2/LPTAU.m b/GSA_distrib/4.2/LPTAU.m
deleted file mode 100644
index 7427de885c114d4e0cbed949322d62072bb92f34..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/LPTAU.m
+++ /dev/null
@@ -1,512 +0,0 @@
-function VECTOR = LPTAU(I, N)
-%
-% I.M. SOBOL', V.I. TURCHANINOV, Yu.L. LEVITAN, B.V. SHUKHMAN
-% KELDYSH INSTITUTE OF APPLIED MATHEMATICS
-% RUSSIAN ACADEMY OF SCIENCES
-%
-% QUASIRANDOM SEQUENCE GENERATORS
-% -------------------------------
-%
-% 28.11.1991
-%
-% NOTE TO THE USER BY the NEA Data Bank:
-% This quasi random number generator has been made available to
-% you on condition that its identity is preserved when used
-% in computer programs. If its use leads to scientific publication
-% of results you should cite it in the references, in addition
-% no commercial use should be made unless agreed upon with the
-% main author (Prof. I.M. Sobol')
-%
-% ABSTRACT
-% ........
-%
-% POINTS BELONGING TO LP-TAU SEQUENCES UNIFORMLY DISTRIBUTED IN THE
-% N-DIMENSIONAL UNIT CUBE ARE OFTEN USED IN NUMERICAL MATHEMATICS:
-%
-% - AS NODES FOR MULTIDIMENSIONAL INTEGRATION;
-% - AS SEARCHING POINTS IN GLOBAL OPTIMIZATION;
-% - AS TRIAL POINTS IN MULTI-CRITERIA DECISION MAKING;
-% - AS QUASIRANDOM POINTS FOR QUASI-MONTECARLO ALGORITHMS;
-% - ETC.
-%
-% THIS SUBROUTINE CONTAINS THE ALGORITHM FOR FAST GENERATION OF
-% LP-TAU SEQUENCES THAT ARE SUITABLE FOR MULTI-PROCESSOR COMPUTATIONS.
-% THE DIMENSIONS N.LE.51, THE NUMBER OF POINTS N.LT.2**30.
-% THE PROGRAMMING LANGUAGE IS FORTRAN-77. THIS SUBROUTINE IS AVAILABLE
-% ALSO IN %-LANGUAGE.
-% THE REPORT DESCRIBING THE ALGORITHM CONTAINS THE DESCRIPTION OF THE
-% ALGORITHM AND CERTAIN IMPORTANT PROPERTIES OF LP-TAU SEQUENCES AND
-% THEIR GENERALIZATIONS ARE DISCUSSED.
-%
-% REFERENCE:
-% I.M. SOBOL', V.I. TURCHANINOV, Yu.L. LEVITAN, B.V. SHUKHMAN
-% KELDYSH INSTITUTE OF APPLIED MATHEMATICS
-% RUSSIAN ACADEMY OF SCIENCES
-%
-% QUASIRANDOM SEQUENCE GENERATORS
-% MOSCOW 1992, IPM ZAK. NO.30 (100 COPIES)
-%
-% ------------------------------------------------------------------------
-%
-% INPUT PARAMETERS:
-%
-% I - NUMBER OF THE POINT (I=(0,2**30-1)),
-% N - DIMENSION OF THE POINT (0<N<52);
-%
-% OUTPUT PARAMETER:
-%
-% VECTOR(N) - N-VECTOR CONTAINING THE CARTESIAN CO-ORDINATES OF
-% THE I-TH POINT.
-%
-%
-% TO CALL THE SUBROUTINE WRITE:
-%
-% CALL LPTAU(I,N,VECTOR)
-% WHERE I, N: INTEGER CAPABLE OF STORING 2**30 (INTEGER*4 ON IBM
-% OR OTHER 32 BIT/WORD MACHINES)
-% VECTOR: DOUBLE PRECISION ARRAY WHOSE LENGTH < 52.
-%
-% INTEGER QP
-% QP = QUANTITY POWER
-%
-% PARAMETER (MAXDIM=51, QP=30, MAXNUM=2**30-1)
-MAXDIM=51; QP=30; MAXNUM=2^30-1;
-%
-% THE DIMENSION OF THE POINT CANNOT EXCEED MAXDIM
-% THE TOTAL NUMBER OF GENERATED POINTS CANNOT EXCEED 2**QP
-% MAXNUM=2**30-1 // 1073741823
-%
-% DOUBLE PRECISION VECTOR(N)
-% INTEGER I,N
-%
-% INTEGER PRVNUM,PRVDIM
-% INTEGER DIRECT(MAXDIM,QP), MASKV(MAXDIM)
-% DOUBLE PRECISION SCALE
-%
-% Translated into MATLAB by M. Ratto
-VECTOR=zeros(1,N);
-SCALE =9.31322574615478516E-10;
-
-persistent PRVNUM PRVDIM MASKV DIRECT
-if isempty(PRVNUM), PRVNUM=-2; end,
-if isempty(PRVDIM), PRVDIM=0; end,
-
-if isempty(DIRECT), ...
- DIRECT(1:MAXDIM,1)=[
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912, 536870912, 536870912, 536870912, 536870912, ...
- 536870912]';
- DIRECT(1:MAXDIM,2)=[
- 805306368, 268435456, 805306368, 268435456, 805306368, ...
- 268435456, 805306368, 268435456, 268435456, 805306368, ...
- 268435456, 805306368, 268435456, 805306368, 268435456, ...
- 805306368, 805306368, 268435456, 805306368, 268435456, ...
- 805306368, 268435456, 805306368, 268435456, 268435456, ...
- 805306368, 268435456, 805306368, 268435456, 805306368, ...
- 268435456, 805306368, 805306368, 268435456, 805306368, ...
- 268435456, 805306368, 268435456, 805306368, 268435456, ...
- 268435456, 805306368, 268435456, 805306368, 268435456, ...
- 805306368, 268435456, 805306368, 805306368, 268435456, ...
- 805306368]';
- DIRECT(1:MAXDIM,3)=[
- 939524096, 939524096, 134217728, 671088640, 402653184, ...
- 402653184, 671088640, 134217728, 671088640, 402653184, ...
- 939524096, 134217728, 671088640, 939524096, 134217728, ...
- 671088640, 134217728, 939524096, 939524096, 402653184, ...
- 402653184, 134217728, 671088640, 402653184, 671088640, ...
- 402653184, 402653184, 671088640, 134217728, 134217728, ...
- 939524096, 939524096, 939524096, 939524096, 134217728, ...
- 671088640, 402653184, 402653184, 671088640, 134217728, ...
- 671088640, 402653184, 939524096, 134217728, 671088640, ...
- 939524096, 134217728, 671088640, 134217728, 939524096, ...
- 939524096]';
- DIRECT(1:MAXDIM,4)=[
- 1006632960, 67108864, 603979776, 1006632960, 335544320, ...
- 469762048, 872415232, 738197504, 469762048, 872415232, ...
- 1006632960, 67108864, 872415232, 469762048, 469762048, ...
- 469762048, 1006632960, 335544320, 872415232, 603979776, ...
- 201326592, 67108864, 335544320, 67108864, 201326592, ...
- 738197504, 1006632960, 738197504, 603979776, 335544320, ...
- 738197504, 67108864, 1006632960, 67108864, 603979776, ...
- 1006632960, 335544320, 469762048, 872415232, 738197504, ...
- 469762048, 872415232, 1006632960, 67108864, 872415232, ...
- 469762048, 469762048, 469762048, 1006632960, 335544320, ...
- 872415232]';
- DIRECT(1:MAXDIM,5)=[
- 1040187392, 637534208, 1040187392, 838860800, 167772160, ...
- 234881024, 167772160, 1040187392, 436207616, 33554432, ...
- 570425344, 1040187392, 503316480, 838860800, 973078528, ...
- 167772160, 234881024, 436207616, 771751936, 100663296, ...
- 234881024, 905969664, 771751936, 33554432, 838860800, ...
- 973078528, 905969664, 33554432, 301989888, 838860800, ...
- 100663296, 234881024, 1040187392, 637534208, 1040187392, ...
- 838860800, 167772160, 234881024, 167772160, 1040187392, ...
- 436207616, 33554432, 570425344, 1040187392, 503316480, ...
- 838860800, 973078528, 167772160, 234881024, 436207616, ...
- 771751936]';
- DIRECT(1:MAXDIM,6)=[
- 1056964608, 352321536, 50331648, 419430400, 956301312, ...
- 889192448, 620756992, 117440512, 956301312, 922746880, ...
- 822083584, 218103808, 587202560, 385875968, 452984832, ...
- 218103808, 184549376, 285212672, 150994944, 956301312, ...
- 352321536, 654311424, 553648128, 352321536, 788529152, ...
- 956301312, 587202560, 251658240, 218103808, 721420288, ...
- 251658240, 1056964608, 520093696, 889192448, 587202560, ...
- 956301312, 419430400, 352321536, 83886080, 654311424, ...
- 419430400, 385875968, 285212672, 754974720, 50331648, ...
- 922746880, 989855744, 754974720, 721420288, 822083584, ...
- 687865856]';
- DIRECT(1:MAXDIM,7)=[
- 1065353216, 1065353216, 578813952, 25165824, 125829120, ...
- 964689920, 327155712, 310378496, 360710144, 360710144, ...
- 159383552, 444596224, 947912704, 662700032, 444596224, ...
- 528482304, 578813952, 578813952, 75497472, 1065353216, ...
- 92274688, 511705088, 897581056, 847249408, 662700032, ...
- 931135488, 411041792, 713031680, 696254464, 528482304, ...
- 209715200, 578813952, 1065353216, 1065353216, 578813952, ...
- 25165824, 125829120, 964689920, 327155712, 310378496, ...
- 360710144, 360710144, 159383552, 444596224, 947912704, ...
- 662700032, 444596224, 528482304, 578813952, 578813952, ...
- 75497472]';
- DIRECT(1:MAXDIM,8)=[
- 1069547520, 4194304, 826277888, 624951296, 616562688, ...
- 801112064, 952107008, 406847488, 398458880, 331350016, ...
- 356515840, 46137344, 1010827264, 1069547520, 734003200, ...
- 113246208, 490733568, 633339904, 910163968, 801112064, ...
- 893386752, 851443712, 801112064, 918552576, 742391808, ...
- 499122176, 62914560, 264241152, 708837376, 717225984, ...
- 759169024, 499122176, 272629760, 423624704, 155189248, ...
- 239075328, 205520896, 943718400, 373293056, 457179136, ...
- 406847488, 71303168, 473956352, 54525952, 624951296, ...
- 104857600, 1019215872, 901775360, 213909504, 281018368, ...
- 851443712]';
- DIRECT(1:MAXDIM,9)=[
- 1071644672, 543162368, 190840832, 329252864, 853540864, ...
- 132120576, 778043392, 73400320, 178257920, 522190848, ...
- 639631360, 534773760, 991952896, 333447168, 48234496, ...
- 1059061760, 761266176, 673185792, 220200960, 396361728, ...
- 362807296, 815792128, 819986432, 346030080, 39845888, ...
- 752877568, 387973120, 643825664, 291504128, 274726912, ...
- 568328192, 526385152, 673185792, 98566144, 396361728, ...
- 727711744, 1042284544, 106954752, 299892736, 912261120, ...
- 44040192, 895483904, 333447168, 551550976, 467664896, ...
- 618659840, 606076928, 274726912, 245366784, 446693376, ...
- 421527552]';
- DIRECT(1:MAXDIM,10)=[
- 1072693248, 273678336, 644874240, 753926144, 495976448, ...
- 869269504, 355467264, 57671680, 816840704, 961544192, ...
- 804257792, 495976448, 347078656, 426770432, 1066401792, ...
- 372244480, 84934656, 208666624, 313524224, 598736896, ...
- 487587840, 965738496, 1011875840, 296747008, 393216000, ...
- 523239424, 720371712, 823132160, 128974848, 407896064, ...
- 747634688, 850395136, 873463808, 504365056, 481296384, ...
- 686817280, 592445440, 995098624, 498073600, 969932800, ...
- 586153984, 1039138816, 814743552, 523239424, 294649856, ...
- 305135616, 506462208, 11534336, 449839104, 619708416, ...
- 479199232]';
- DIRECT(1:MAXDIM,11)=[
- 1073217536, 947388416, 1070071808, 977797120, 365428736, ...
- 702021632, 461897728, 829947904, 425197568, 634912768, ...
- 437780480, 582483968, 792199168, 315097088, 611844096, ...
- 667418624, 166199296, 513277952, 187170816, 1036517376, ...
- 25690112, 201850880, 443023360, 990380032, 63438848, ...
- 211288064, 983040000, 1069023232, 421003264, 742916096, ...
- 487063552, 363331584, 973602816, 286785536, 171442176, ...
- 669515776, 110624768, 383254528, 289931264, 352845824, ...
- 878182400, 655884288, 836239360, 765984768, 549978112, ...
- 655884288, 85458944, 591921152, 563609600, 277348352, ...
- 919076864]';
- DIRECT(1:MAXDIM,12)=[
- 1073479680, 71565312, 2359296, 891551744, 158597120, ...
- 383516672, 1019478016, 947126272, 621019136, 714866688, ...
- 738459648, 265027584, 468975616, 131858432, 504627200, ...
- 581173248, 266600448, 865861632, 658243584, 546045952, ...
- 521404416, 304873472, 1060896768, 163840000, 305922048, ...
- 257163264, 50069504, 773062656, 59506688, 779354112, ...
- 165937152, 587988992, 486801408, 160694272, 90439680, ...
- 423362560, 536608768, 614203392, 56885248, 999030784, ...
- 10747904, 764674048, 25952256, 989069312, 352583680, ...
- 799801344, 261357568, 873201664, 40108032, 769392640, ...
- 254541824]';
- DIRECT(1:MAXDIM,13)=[
- 1073610752, 644218880, 538836992, 455475200, 1062600704, ...
- 139329536, 205651968, 905052160, 797048832, 452329472, ...
- 973471744, 627703808, 614072320, 803078144, 637403136, ...
- 835059712, 949878784, 662044672, 767950848, 426901504, ...
- 448659456, 23986176, 1016201216, 524943360, 525991936, ...
- 618790912, 781058048, 761659392, 458096640, 226361344, ...
- 950665216, 952500224, 516030464, 337510400, 496107520, ...
- 830865408, 944111616, 636354560, 978452480, 921567232, ...
- 533594112, 7471104, 678035456, 471203840, 1065746432, ...
- 575275008, 996540416, 909246464, 879362048, 637927424, ...
- 25821184]';
- DIRECT(1:MAXDIM,14)=[
- 1073676288, 357892096, 808648704, 2424832, 2555904, ...
- 624230400, 69271552, 456851456, 1052966912, 600637440, ...
- 487260160, 794624000, 386727936, 467599360, 798031872, ...
- 630652928, 340983808, 493944832, 37945344, 264175616, ...
- 263520256, 833421312, 235077632, 464846848, 534839296, ...
- 992411648, 10813440, 367067136, 116457472, 115015680, ...
- 928710656, 619773952, 813760512, 1043398656, 967770112, ...
- 912850944, 72155136, 1009057792, 668532736, 462356480, ...
- 267321344, 795803648, 635764736, 574160896, 1003421696, ...
- 181075968, 56688640, 388562944, 190906368, 657915904, ...
- 474939392]';
- DIRECT(1:MAXDIM,15)=[
- 1073709056, 1073709056, 137003008, 547782656, 545095680, ...
- 26836992, 34701312, 354385920, 925663232, 656965632, ...
- 327581696, 894795776, 110067712, 1038057472, 209354752, ...
- 596541440, 42631168, 471433216, 52527104, 666861568, ...
- 706707456, 674070528, 824410112, 305496064, 136282112, ...
- 847740928, 531464192, 222920704, 379289600, 507740160, ...
- 11894784, 1053392896, 129990656, 557547520, 666468352, ...
- 1061912576, 576684032, 1041334272, 380469248, 114196480, ...
- 133070848, 517046272, 129990656, 790396928, 563773440, ...
- 388333568, 661749760, 446791680, 737378304, 229998592, ...
- 348225536]';
- DIRECT(1:MAXDIM,16)=[
- 1073725440, 16384, 605372416, 275234816, 817971200, ...
- 603963392, 555335680, 721534976, 997801984, 1028767744, ...
- 407060480, 375275520, 256688128, 1021165568, 303349760, ...
- 1022476288, 234143744, 106708992, 732971008, 733954048, ...
- 789889024, 879575040, 764657664, 762658816, 1010843648, ...
- 941080576, 827932672, 98942976, 1051738112, 624934912, ...
- 993280000, 134070272, 201375744, 567558144, 882163712, ...
- 649084928, 356564992, 489439232, 637091840, 60637184, ...
- 199278592, 815677440, 927678464, 94519296, 419184640, ...
- 933838848, 426655744, 911130624, 171393024, 561332224, ...
- 471613440]';
- DIRECT(1:MAXDIM,17)=[
- 1073733632, 536895488, 1043685376, 679944192, 417505280, ...
- 301981696, 832561152, 210542592, 167501824, 1071341568, ...
- 229302272, 970661888, 732176384, 576659456, 402464768, ...
- 451584000, 368467968, 928260096, 933847040, 29319168, ...
- 582934528, 772612096, 330014720, 647323648, 174071808, ...
- 1008689152, 295919616, 353869824, 177774592, 580198400, ...
- 381837312, 638574592, 637558784, 679370752, 504012800, ...
- 747118592, 429973504, 1032609792, 932667392, 583360512, ...
- 969498624, 1056333824, 660955136, 247488512, 153509888, ...
- 242180096, 205840384, 797499392, 824565760, 234348544, ...
- 842326016]';
- DIRECT(1:MAXDIM,18)=[
- 1073737728, 268455936, 52785152, 1020628992, 345018368, ...
- 452972544, 704442368, 255987712, 750759936, 697692160, ...
- 196677632, 764604416, 485625856, 522022912, 680620032, ...
- 362270720, 838103040, 83972096, 629133312, 46108672, ...
- 867561472, 725422080, 184504320, 751112192, 191918080, ...
- 306425856, 507310080, 30453760, 281858048, 604000256, ...
- 208662528, 319557632, 318779392, 476139520, 863719424, ...
- 567062528, 521179136, 712790016, 610299904, 293687296, ...
- 1023086592, 549089280, 1065242624, 707751936, 363024384, ...
- 16674816, 197136384, 1037561856, 195112960, 372707328, ...
- 992751616]';
- DIRECT(1:MAXDIM,19)=[
- 1073739776, 939554816, 580732928, 854333440, 172619776, ...
- 511694848, 936142848, 518199296, 593348608, 225527808, ...
- 900982784, 180279296, 168904704, 62814208, 754485248, ...
- 730691584, 1005996032, 411174912, 249866240, 641669120, ...
- 1008719872, 749066240, 860993536, 94177280, 432564224, ...
- 226355200, 925784064, 995657728, 967731200, 436226048, ...
- 913799168, 549894144, 964696064, 843315200, 445863936, ...
- 1047422976, 548947968, 492066816, 953870336, 1002653696, ...
- 861440000, 385636352, 325253120, 187353088, 653584384, ...
- 1008269312, 748693504, 1013016576, 55814144, 255170560, ...
- 260708352]';
- DIRECT(1:MAXDIM,20)=[
- 1073740800, 67126272, 829514752, 423777280, 968297472, ...
- 205511680, 147076096, 926669824, 202300416, 118395904, ...
- 381332480, 1002738688, 743042048, 292551680, 584567808, ...
- 284339200, 183936000, 616762368, 435221504, 159376384, ...
- 907322368, 595696640, 247497728, 553735168, 826051584, ...
- 564454400, 446024704, 214236160, 33661952, 251685888, ...
- 660327424, 284244992, 859868160, 722502656, 622844928, ...
- 324342784, 682374144, 400579584, 405353472, 605187072, ...
- 840682496, 212956160, 157891584, 193201152, 437990400, ...
- 573578240, 368053248, 580197376, 937905152, 565527552, ...
- 89064448]';
- DIRECT(1:MAXDIM,21)=[
- 1073741312, 637560320, 189496832, 27474432, 129338880, ...
- 908054016, 641870336, 186375680, 302677504, 763663872, ...
- 103878144, 325187072, 858254848, 922041856, 261924352, ...
- 954978816, 292822528, 849512960, 210311680, 933232128, ...
- 691981824, 155417088, 627070464, 416795136, 182081024, ...
- 513433088, 848658944, 515770880, 627273216, 629169664, ...
- 414566912, 147450368, 698353152, 244844032, 226578944, ...
- 1020087808, 886978048, 389697024, 1007004160, 839646720, ...
- 621924864, 549962240, 609583616, 735976960, 87342592, ...
- 1058542080, 163066368, 307997184, 876471808, 794280448, ...
- 675386880]';
- DIRECT(1:MAXDIM,22)=[
- 1073741568, 352343296, 644236032, 636735232, 615860480, ...
- 959444224, 287380736, 1007410432, 890187008, 399480576, ...
- 520092928, 643311360, 816901376, 695310080, 1019229440, ...
- 77034240, 733295872, 1035127552, 986582784, 332381952, ...
- 334852352, 364956416, 596672256, 800381696, 480316672, ...
- 574863104, 647347968, 702910208, 499965184, 364968704, ...
- 120862976, 1023256320, 995114240, 13951232, 32520448, ...
- 702127360, 45176064, 444945664, 237860096, 152839936, ...
- 530633984, 429135616, 267272448, 884808960, 933712640, ...
- 61605632, 174335744, 564911360, 302327552, 650589440, ...
- 450649344]';
- DIRECT(1:MAXDIM,23)=[
- 1073741696, 1065385856, 1073734272, 331949184, 842310784, ...
- 799537536, 965852032, 369351808, 662886016, 86119808, ...
- 865109888, 299633792, 422735488, 181087360, 174252416, ...
- 1041212544, 840196224, 750314368, 391053440, 903306880, ...
- 742365312, 236995200, 42492800, 946000512, 771692416, ...
- 897405824, 613803136, 924258688, 808338304, 1038125440, ...
- 683814272, 177186176, 766008960, 704549248, 194555008, ...
- 306383744, 496592512, 416020864, 655186816, 1032204928, ...
- 694773632, 577910144, 45797760, 910332544, 536014976, ...
- 675946368, 987635840, 788223872, 353993856, 96313472, ...
- 85248640]';
- DIRECT(1:MAXDIM,24)=[
- 1073741760, 4210752, 12608, 744788544, 494377792, ...
- 115601344, 769248448, 990895808, 851706304, 979326784, ...
- 692061120, 429015104, 217132864, 736067008, 55694400, ...
- 456152640, 631601984, 787264192, 898599104, 478383808, ...
- 507774272, 458270272, 392995136, 872482496, 124824768, ...
- 1034161344, 362141632, 1053833280, 943810496, 428920128, ...
- 795835200, 835462848, 961843520, 606198080, 785652672, ...
- 154954432, 491617344, 297351232, 580735552, 634587968, ...
- 185277760, 141505600, 417673280, 106907456, 395575616, ...
- 566958656, 352651200, 415242688, 26635200, 1030317504, ...
- 247212992]';
- DIRECT(1:MAXDIM,25)=[
- 1073741792, 543187040, 536882016, 981766752, 357858144, ...
- 810665952, 369083488, 613015520, 86115232, 845149216, ...
- 606076960, 1018241504, 35245536, 635403744, 236633696, ...
- 407451232, 427671904, 460141792, 116344544, 990246688, ...
- 1024892576, 883429408, 150655392, 173476896, 197666464, ...
- 1016740448, 605376608, 970487008, 1006881248, 598265632, ...
- 1022861728, 489055392, 216680608, 371439072, 53140576, ...
- 965114400, 98534112, 209692256, 264598496, 321437280, ...
- 545303840, 324119904, 876587488, 778239712, 802033120, ...
- 44406496, 665829024, 803213920, 309742112, 735181344, ...
- 1036125600]';
- DIRECT(1:MAXDIM,26)=[
- 1073741808, 273698896, 805312112, 903123536, 153504624, ...
- 689632208, 432848944, 859888752, 510853776, 240805744, ...
- 250610192, 852489168, 139460144, 283082224, 222702928, ...
- 342181488, 922872432, 187528656, 360637424, 814514736, ...
- 301037840, 800872624, 272595184, 158627600, 238839088, ...
- 927181136, 710248688, 788854608, 1048376560, 484709072, ...
- 85709008, 1065469744, 429237328, 490778384, 848024144, ...
- 443114288, 687907504, 474573648, 45706416, 681465296, ...
- 805303216, 14567920, 369839504, 440402480, 797652624, ...
- 115959088, 929784560, 91226544, 205943056, 288358704, ...
- 950217296]';
- DIRECT(1:MAXDIM,27)=[
- 1073741816, 947419256, 134232008, 460100200, 1073685336, ...
- 398354904, 1069834248, 686054696, 108299224, 273898840, ...
- 731382552, 938170664, 86812552, 677346808, 602208712, ...
- 652635752, 209797064, 323968376, 384078968, 561178056, ...
- 923399256, 996597176, 942777416, 885167400, 89791048, ...
- 956122504, 87393464, 987661336, 993412952, 827749496, ...
- 903211272, 33649816, 594875176, 65052056, 822835240, ...
- 625704888, 1065374584, 612232920, 536299720, 1046858504, ...
- 939518840, 160843032, 654656088, 744496936, 872197704, ...
- 219111576, 829112632, 455614152, 1064192952, 313010856, ...
- 820754920]';
- DIRECT(1:MAXDIM,28)=[
- 1073741820, 71582788, 603989028, 37500, 120660, ...
- 182195932, 213921796, 473570692, 41763004, 156352828, ...
- 88343188, 698012780, 666108868, 337608156, 1054329884, ...
- 799472220, 641885244, 392104980, 502284340, 1002405628, ...
- 249907140, 75586228, 206587660, 565275348, 1021426548, ...
- 425987996, 598058580, 401940420, 919427316, 822049324, ...
- 115655868, 759299588, 562394644, 990942164, 1003212268, ...
- 598750292, 675334852, 675293340, 445665316, 903023756, ...
- 872412692, 172640916, 1051615436, 91229620, 94586692, ...
- 344873452, 7029156, 683421900, 434258804, 955002092, ...
- 436424380]';
- DIRECT(1:MAXDIM,29)=[
- 1073741822, 644245094, 1040195102, 537039474, 537089354, ...
- 642656334, 73402402, 664239174, 1014620426, 500917234, ...
- 1042677826, 347788318, 1069154738, 373259762, 362587674, ...
- 239395914, 132283950, 903121466, 445210638, 968851198, ...
- 230153254, 935549622, 308815630, 861891286, 496995094, ...
- 670740382, 657311830, 573565382, 248331478, 1064650798, ...
- 338312798, 669059078, 1065190902, 379125622, 111897166, ...
- 520650422, 740300390, 1046483950, 66254898, 992513134, ...
- 234871606, 610553330, 450553866, 566758134, 787800806, ...
- 1071709866, 971732606, 528102354, 790919122, 917384366, ...
- 656244162]';
- DIRECT(1:MAXDIM,30)=[
- 1073741823, 357913941, 50344755, 268538457, 805540473, ...
- 3487029, 3146769, 592038967, 729591963, 781578389, ...
- 66781679, 113956361, 331153483, 967802327, 935343371, ...
- 324351309, 609305915, 818137857, 131059769, 918519549, ...
- 827341719, 922770101, 456972047, 363883221, 1057014661, ...
- 900956063, 580478293, 520383687, 315470533, 227601711, ...
- 169598765, 909227271, 796983815, 349496709, 393974911, ...
- 378320037, 777004343, 927999269, 616377385, 345930959, ...
- 989849787, 627400495, 892675125, 260314121, 1041964063, ...
- 531367163, 195776757, 237309785, 949187605, 719002587, ...
- 495745187]';
-end
-
-%
-% TRAP FOR A WRONG SUBROUTINE CALL
-%
-if ((I<0) | (N<1) | (I>MAXNUM) | (N>MAXDIM)),
- disp('LP-TAU CALL FAILED')
- disp(' PRESS <ENTER> TO EXIT LPTAU')
- pause
- return
-end
-if ((PRVNUM+1==I) & (N<=PRVDIM)),
- %
- % RECURRENT GENERATION OF THE POINT
- %
- %
- % SEARCH POSITION OF THE RIGHTMOST "1"
- % IN THE BINARY REPRESENTATION OF I
- %
- L=0;
- POS=0;
- while L<QP & POS==0,
- L=L+1;
- POS=bitand(bitshift(I,-(L-1)),1);
- end
- %
- % RIGHTMOST POSITION IS L
- %
- for J=1:N
- MASKV(J)=bitxor(MASKV(J),DIRECT(J,L));
- VECTOR(J)=MASKV(J)*SCALE;
- end
-else
- %
- % GENERATION OF THE POINT FROM "I" AND "N"
- %
- MASKV=zeros(1,N);
- IM=bitxor(I,bitshift(I,-1));
- M=0;
- while IM~=0 & M<QP,
- M=M+1;
- if (bitand(IM,1)==1),
- for J=1:N
- MASKV(J)=bitxor(MASKV(J),DIRECT(J,M));
- end
- end
- IM=bitshift(IM,-1);
- end
- for J=1:N
- VECTOR(J)=MASKV(J)*SCALE;
- end
-end
-%
-PRVNUM=I;
-PRVDIM=N;
-return
-
-
diff --git a/GSA_distrib/4.2/Morris_Measure_Groups.m b/GSA_distrib/4.2/Morris_Measure_Groups.m
deleted file mode 100644
index c5a71b057a3d8029f6abdf621f82816465b7f4be..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/Morris_Measure_Groups.m
+++ /dev/null
@@ -1,130 +0,0 @@
-
-function [SAmeas, OutMatrix] = Morris_Measure_Groups(NumFact, Sample, Output, p, Group)
-
-% [SAmeas, OutMatrix] = Morris_Measure_Groups(NumFact, Sample, Output, p, Group)
-%
-% Given the Morris sample matrix, the output values and the group matrix compute the Morris measures
-% -------------------------------------------------------------------------
-% INPUTS
-% -------------------------------------------------------------------------
-% Group [NumFactor, NumGroups] := Matrix describing the groups.
-% Each column represents one group.
-% The element of each column are zero if the factor is not in the
-% group. Otherwise it is 1.
-
-% Sample := Matrix of the Morris sampled trajectories
-
-% Output := Matrix of the output(s) values in correspondence of each point
-% of each trajectory
-
-% k = Number of factors
-% -------------------------------------------------------------------------
-% OUTPUTS
-% OutMatrix (NumFactor*NumOutputs, 3)= [Mu*, Mu, StDev]
-% for each output it gives the three measures of each factor
-% -------------------------------------------------------------------------
-
-if nargin==0,
- disp(' ')
- disp('[SAmeas, OutMatrix] = Morris_Measure_Groups(NumFact, Sample, Output, p, Group);')
- return
-end
-
-OutMatrix=[];
-if nargin < 5, Group=[]; end
-
-NumGroups = size(Group,2);
-if nargin < 4 | isempty(p),
- p = 4;
-end
-Delt = p/(2*p-2);
-
-if NumGroups ~ 0
- sizea = NumGroups; % Number of groups
- GroupMat=Group;
- GroupMat = GroupMat';
-else
- sizea = NumFact;
-end
-r=size(Sample,1)/(sizea+1); % Number of trajectories
-
-% For Each Output
-for k=1:size(Output,2)
-
- OutValues=Output(:,k);
-
- % For each r trajectory
- for i=1:r
-
- % For each step j in the trajectory
- % Read the orientation matrix fact for the r-th sampling
- % Read the corresponding output values
- Single_Sample = Sample(i+(i-1)*sizea:i+(i-1)*sizea+sizea,:);
- Single_OutValues = OutValues(i+(i-1)*sizea:i+(i-1)*sizea+sizea,:);
- A = (Single_Sample(2:sizea+1,:)-Single_Sample(1:sizea,:))';
- Delta = A(find(A));
-
- % For each point of the fixed trajectory compute the values of the Morris function. The function
- % is partitioned in four parts, from order zero to order 4th.
- for j=1:sizea % For each point in the trajectory i.e for each factor
- % matrix of factor which changes
- if NumGroups ~ 0;
- AuxFind (:,1) = A(:,j);
-% AuxFind(find(A(:,j)),1)=1;
-% Pippo = sum((Group - repmat(AuxFind,1,NumGroups)),1);
-% Change_factor(j,i) = find(Pippo==0);
- Change_factor = find(abs(AuxFind)>1e-010);
- % If we deal with groups we can only estimate the new mu*
- % measure since factors in the same groups can move in
- % opposite direction and the definition of the standard
- % Morris mu cannopt be applied.
- % In the new version the elementary effect is defined with
- % the absolute value.
- %SAmeas(find(GroupMat(Change_factor(j,i),:)),i) = abs((Single_OutValues(j) - Single_OutValues(j+1) )/Delt); %(2/3));
- SAmeas(i,Change_factor') = abs((Single_OutValues(j) - Single_OutValues(j+1) )/Delt);
- else
- Change_factor(j,i) = find(Single_Sample(j+1,:)-Single_Sample(j,:));
- % If no groups --> we compute both the original and
- % modified measure
- if Delta(j) > 0 %=> +Delta
- SAmeas(Change_factor(j,i),i) = (Single_OutValues(j+1) - Single_OutValues(j) )/Delt; %(2/3);
- else %=> -Delta
- SAmeas(Change_factor(j,i),i) = (Single_OutValues(j) - Single_OutValues(j+1) )/Delt; %(2/3);
- end
- end
- end %for j=1:sizea
-
- end %for i=1:r
-
- if NumGroups ~ 0
- SAmeas = SAmeas';
- end
-
- % Compute Mu AbsMu and StDev
- if any(any(isnan(SAmeas)))
- for j=1:NumFact,
- SAm = SAmeas(j,:);
- SAm = SAm(find(~isnan(SAm)));
- rr=length(SAm);
- AbsMu(j,1) = sum(abs(SAm),2)/rr;
- if NumGroups == 0
- Mu(j,1) = sum(SAm,2)/rr;
- StDev(j,1) = sum((SAm - repmat(Mu(j),1,rr)).^2/(rr*(rr-1)),2).^0.5;
- end
- end
- else
- AbsMu = sum(abs(SAmeas),2)/r;
- if NumGroups == 0
- Mu = sum(SAmeas,2)/r;
- StDev = sum((SAmeas - repmat(Mu,1,r)).^2/(r*(r-1)),2).^0.5;
- end
- end
-
- % Define the output Matrix - if we have groups we cannot define the old
- % measure mu, only mu* makes sense
- if NumGroups > 0
- OutMatrix = [OutMatrix; AbsMu];
- else
- OutMatrix = [OutMatrix; AbsMu, Mu, StDev];
- end
-end % For Each Output
diff --git a/GSA_distrib/4.2/Sampling_Function_2.m b/GSA_distrib/4.2/Sampling_Function_2.m
deleted file mode 100644
index ccd3a87f91051686bea0d3a406e751223b076ca6..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/Sampling_Function_2.m
+++ /dev/null
@@ -1,174 +0,0 @@
-function [Outmatrix, OutFact] = Sampling_Function_2(p, k, r, UB, LB, GroupMat)
-%[Outmatrix, OutFact] = Sampling_Function_2(p, k, r, UB, LB, GroupMat)
-% Inputs: k (1,1) := number of factors examined or number of groups examined.
-% In case the groups are chosen the number of factors is stores in NumFact and
-% sizea becomes the number of created groups.
-% NumFact (1,1) := number of factors examined in the case when groups are chosen
-% r (1,1) := sample size
-% p (1,1) := number of intervals considered in [0, 1]
-% UB(sizea,1) := Upper Bound for each factor
-% LB(sizea,1) := Lower Bound for each factor
-% GroupNumber(1,1) := Number of groups (eventually 0)
-% GroupMat(NumFact,GroupNumber):= Matrix which describes the chosen groups. Each column represents a group and its elements
-% are set to 1 in correspondence of the factors that belong to the fixed group. All
-% the other elements are zero.
-% Local Variables:
-% sizeb (1,1) := sizea+1
-% sizec (1,1) := 1
-% randmult (sizea,1) := vector of random +1 and -1
-% perm_e(1,sizea) := vector of sizea random permutated indeces
-% fact(sizea) := vector containing the factor varied within each traj
-% DDo(sizea,sizea) := D* in Morris, 1991
-% A(sizeb,sizea) := Jk+1,k in Morris, 1991
-% B(sizeb,sizea) := B in Morris, 1991
-% Po(sizea,sizea) := P* in Morris, 1991
-% Bo(sizeb,sizea) := B* in Morris, 1991
-% Ao(sizeb,sizec) := Jk+1,1 in Morris, 1991
-% xo(sizec,sizea) := x* in Morris, 1991 (starting point for the trajectory)
-% In(sizeb,sizea) := for each loop orientation matrix. It corresponds to a trajectory
-% of k step in the parameter space and it provides a single elementary
-% effect per factor
-% MyInt()
-% Fact(sizea,1) := for each loop vector indicating which factor or group of factors has been changed
-% in each step of the trajectory
-% AuxMat(sizeb,sizea) := Delta*0.5*((2*B - A) * DD0 + A) in Morris, 1991. The AuxMat is used as in Morris design
-% for single factor analysis, while it constitutes an intermediate step for the group analysis.
-%
-% Output: Outmatrix(sizeb*r, sizea) := for the entire sample size computed In(i,j) matrices
-% OutFact(sizea*r,1) := for the entire sample size computed Fact(i,1) vectors
-%
-% Note: B0 is constructed as in Morris design when groups are not considered. When groups are considered the routine
-% follows the following steps:
-% 1- Creation of P0 and DD0 matrices defined in Morris for the groups. This means that the dimensions of these
-% 2 matrices are (GroupNumber,GroupNumber).
-% 2- Creation of AuxMat matrix with (GroupNumber+1,GroupNumber) elements.
-% 3- Definition of GroupB0 starting from AuxMat, GroupMat and P0.
-% 4- The final B0 for groups is obtained as [ones(sizeb,1)*x0' + GroupB0]. The P0 permutation is present in GroupB0
-% and it's not necessary to permute the matrix (ones(sizeb,1)*x0') because it's already randomly created.
-% Reference:
-% A. Saltelli, K. Chan, E.M. Scott, "Sensitivity Analysis" on page 68 ss
-%
-% F. Campolongo, J. Cariboni, JRC - IPSC Ispra, Varese, IT
-% Last Update: 15 November 2005 by J.Cariboni
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-
-% Parameters and initialisation of the output matrix
-sizea = k;
-Delta = p/(2*p-2);
-%Delta = 1/3
-NumFact = sizea;
-GroupNumber = size(GroupMat,2);
-
-if GroupNumber ~ 0;
- sizea = size(GroupMat,2);
-end
-
-sizeb = sizea + 1;
-sizec = 1;
-Outmatrix = [];
-OutFact = [];
-
-% For each i generate a trajectory
-for i=1:r
-
- % Construct DD0 - OLD VERSION - it does not need communication toolbox
- % RAND(N,M) is an NXM matrix with random entries, chosen from a uniform distribution on the interval (0.0,1.0).
- % Note that DD0 tells if the factor have to be increased or ddecreased
- % by Delta.
- randmult = ones(k,1);
- v = rand(k,1);
- randmult (find(v < 0.5))=-1;
- randmult = repmat(randmult,1,k);
- DD0 = randmult .* eye(k);
-
- % Construct DD0 - NEW VERSION - it needs communication toolbox
- % randsrc(m) generates an m-by-m matrix, each of whose entries independently takes the value -1 with probability 1/2,
- % and 1 with probability 1/2.
- % DD0 = randsrc(NumFact) .* eye(NumFact);
-
- % Construct B (lower triangular)
- B = ones(sizeb,sizea);
- for j = 1:sizea
- B(1:j,j)=0;
- end
-
- % Construct A0, A
- A0 = ones(sizeb,1);
- A = ones(sizeb,NumFact);
-
- % Construct the permutation matrix P0. In each column of P0 one randomly chosen element equals 1
- % while all the others equal zero.
- % P0 tells the order in which order factors are changed in each
- % trajectory. P0 is created as it follows:
- % 1) All the elements of P0 are set equal to zero ==> P0 = zeros (sizea, sizea);
- % 2) The function randperm create a random permutation of integer 1:sizea, without repetitions ==> perm_e;
- % 3) In each column of P0 the element indicated in perm_e is set equal to one.
- % Note that P0 is then used reading it by rows.
- P0 = zeros (sizea, sizea);
- perm_e = randperm(sizea); % RANDPERM(n) is a random permutation of the integers from 1 to n.
- for j = 1:sizea
- P0(perm_e(j),j) = 1;
- end
-
- % When groups are present the random permutation is done only on B. The effect is the same since
- % the added part (A0*x0') is completely random.
- if GroupNumber ~ 0
- B = B * (GroupMat*P0')';
- end
-
- % Compute AuxMat both for single factors and groups analysis. For Single factors analysis
- % AuxMat is added to (A0*X0) and then permutated through P0. When groups are active AuxMat is
- % used to build GroupB0. AuxMat is created considering DD0. If the element on DD0 diagonal
- % is 1 then AuxMat will start with zero and add Delta. If the element on DD0 diagonal is -1
- % then DD0 will start Delta and goes to zero.
- AuxMat = Delta*0.5*((2*B - A) * DD0 + A);
-
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
- % a --> Define the random vector x0 for the factors. Note that x0 takes value in the hypercube
- % [0,...,1-Delta]*[0,...,1-Delta]*[0,...,1-Delta]*[0,...,1-Delta]
- MyInt = repmat([0:(1/(p-1)):(1-Delta)],NumFact,1); % Construct all possible values of the factors
-
- % OLD VERSION - it needs communication toolbox
- % w = randint(NumFact,1,[1,size(MyInt,2)]);
-
- % NEW VERSION - construct a version of random integers
- % 1) create a vector of random integers
- % 2) divide [0,1] into the needed steps
- % 3) check in which interval the random numbers fall
- % 4) generate the corresponding integer
- v = repmat(rand(NumFact,1),1,size(MyInt,2)+1); % 1)
- IntUsed = repmat([0:1/size(MyInt,2):1],NumFact,1); % 2)
- DiffAuxVec = IntUsed - v; % 3)
-
- for ii = 1:size(DiffAuxVec,1)
- w(1,ii) = max(find(DiffAuxVec(ii,:)<0)); % 4)
- end
- x0 = MyInt(1,w)'; % Define x0
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
- % b --> Compute the matrix B*, here indicated as B0. Each row in B0 is a
- % trajectory for Morris Calculations. The dimension of B0 is (Numfactors+1,Numfactors)
- if GroupNumber ~ 0
- B0 = (A0*x0' + AuxMat);
- else
- B0 = (A0*x0' + AuxMat)*P0;
- end
-
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
- % c --> Compute values in the original intervals
- % B0 has values x(i,j) in [0, 1/(p -1), 2/(p -1), ... , 1].
- % To obtain values in the original intervals [LB, UB] we compute
- % LB(j) + x(i,j)*(UB(j)-LB(j))
- In = repmat(LB,1,sizeb)' + B0 .* repmat((UB-LB),1,sizeb)';
-
- % Create the Factor vector. Each component of this vector indicate which factor or group of factor
- % has been changed in each step of the trajectory.
- for j=1:sizea
- Fact(1,j) = find(P0(j,:));
- end
- Fact(1,sizea+1) = 0;
-
- Outmatrix = [Outmatrix; In];
- OutFact = [OutFact; Fact'];
-
-end
\ No newline at end of file
diff --git a/GSA_distrib/4.2/beta_inv.m b/GSA_distrib/4.2/beta_inv.m
deleted file mode 100644
index d3c95836dd060c5dbcdc1f300131576955360dfb..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/beta_inv.m
+++ /dev/null
@@ -1,38 +0,0 @@
-function x = beta_inv(p, a, b)
-% PURPOSE: inverse of the cdf (quantile) of the beta(a,b) distribution
-%--------------------------------------------------------------
-% USAGE: x = beta_inv(p,a,b)
-% where: p = vector of probabilities
-% a = beta distribution parameter, a = scalar
-% b = beta distribution parameter b = scalar
-% NOTE: mean [beta(a,b)] = a/(a+b), variance = ab/((a+b)*(a+b)*(a+b+1))
-%--------------------------------------------------------------
-% RETURNS: x at each element of p for the beta(a,b) distribution
-%--------------------------------------------------------------
-% SEE ALSO: beta_d, beta_pdf, beta_inv, beta_rnd
-%--------------------------------------------------------------
-
-% Anders Holtsberg, 18-11-93
-% Copyright (c) Anders Holtsberg
-% documentation modified by LeSage to
-% match the format of the econometrics toolbox
-
-if (nargin ~= 3)
- error('Wrong # of arguments to beta_inv');
-end
-
-if any(any((a<=0)|(b<=0)))
- error('beta_inv parameter a or b is nonpositive');
-end
-if any(any(abs(2*p-1)>1))
- error('beta_inv: A probability should be 0<=p<=1');
-end
-
-x = a ./ (a+b);
-dx = 1;
-while any(any(abs(dx)>256*eps*max(x,1)))
- dx = (betainc(x,a,b) - p) ./ beta_pdf(x,a,b);
- x = x - dx;
- x = x + (dx - x) / 2 .* (x<0);
-end
-
\ No newline at end of file
diff --git a/GSA_distrib/4.2/beta_pdf.m b/GSA_distrib/4.2/beta_pdf.m
deleted file mode 100644
index 8412fbdce51af35e893bcb501b60230e49e3e1b0..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/beta_pdf.m
+++ /dev/null
@@ -1,32 +0,0 @@
-function pdf = beta_pdf(x, a, b)
-% PURPOSE: pdf of the beta(a,b) distribution
-%--------------------------------------------------------------
-% USAGE: pdf = beta_pdf(x,a,b)
-% where: x = vector of components
-% a = beta distribution parameter, a = scalar
-% b = beta distribution parameter b = scalar
-% NOTE: mean[(beta(a,b)] = a/(a+b), variance = ab/((a+b)*(a+b)*(a+b+1))
-%--------------------------------------------------------------
-% RETURNS: pdf at each element of x of the beta(a,b) distribution
-%--------------------------------------------------------------
-% SEE ALSO: beta_d, beta_pdf, beta_inv, beta_rnd
-%--------------------------------------------------------------
-
-% Anders Holtsberg, 18-11-93
-% Copyright (c) Anders Holtsberg
-% documentation modified by LeSage to
-% match the format of the econometrics toolbox
-
-
-if (nargin ~=3)
- error('Wrong # of arguments to beta_pdf');
-end
-
-if any(any((a<=0)|(b<=0)))
- error('Parameter a or b is nonpositive');
-end
-
-I = find((x<0)|(x>1));
-
-pdf = x.^(a-1) .* (1-x).^(b-1) ./ beta(a,b);
-pdf(I) = 0*I;
diff --git a/GSA_distrib/4.2/cumplot.m b/GSA_distrib/4.2/cumplot.m
deleted file mode 100644
index a700d37842a1c4ddb3a9adb34a4780c90e5b5685..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/cumplot.m
+++ /dev/null
@@ -1,14 +0,0 @@
-function h = cumplot(x);
-%function h =cumplot(x)
-% Copyright (C) 2005 Marco Ratto
-
-
-n=length(x);
-x=[-inf; sort(x); Inf];
-y=[0:n n]./n;
-h0 = stairs(x,y);
-grid on,
-
-if nargout,
- h=h0;
-end
diff --git a/GSA_distrib/4.2/dat_fil_.m b/GSA_distrib/4.2/dat_fil_.m
deleted file mode 100644
index 0b3ac8f8e7499ca8f48b610df9a04c2fdcfe48c1..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/dat_fil_.m
+++ /dev/null
@@ -1,30 +0,0 @@
-function c = dat_fil_(data_file);
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-try
- eval(data_file);
-catch
- load(data_file);
-end
-clear data_file;
-
-a=who;
-
-for j=1:length(a)
- eval(['c.',a{j},'=',a{j},';']);
-end
\ No newline at end of file
diff --git a/GSA_distrib/4.2/dynare_MC.m b/GSA_distrib/4.2/dynare_MC.m
deleted file mode 100644
index 3d13b5b514eef2c82ae2673297b37ae5ec981655..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/dynare_MC.m
+++ /dev/null
@@ -1,133 +0,0 @@
-function dynare_MC(var_list_,OutDir,data,rawdata,data_info)
-%
-% Adapted by M. Ratto from dynare_estimation.m and posteriorsmoother.m
-% (dynare_estimation.m and posteriorsmoother.m are part of DYNARE,
-% copyright M. Juillard)
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global M_ options_ oo_ estim_params_
-global bayestopt_
-
-% if options_.filtered_vars ~= 0 & options_.filter_step_ahead == 0
-% options_.filter_step_ahead = 1;
-% end
-% if options_.filter_step_ahead ~= 0
-% options_.nk = max(options_.filter_step_ahead);
-% else
-% options_.nk = 0;
-% end
-%
-options_.filter_step_ahead=1;
-options_.nk = 1;
-
-
-
-nvx = estim_params_.nvx;
-nvn = estim_params_.nvn;
-ncx = estim_params_.ncx;
-ncn = estim_params_.ncn;
-np = estim_params_.np ;
-npar = nvx+nvn+ncx+ncn+np;
-
-if isempty(options_.datafile)
- error('ESTIMATION: datafile option is missing')
-end
-
-if isempty(options_.varobs)
- error('ESTIMATION: VAROBS is missing')
-end
-
-gend = data_info.gend;
-n_varobs = size(options_.varobs,1);
-
-data_index = data_info.data_index;
-number_of_observations = data_info.number_of_observations;
-no_more_missing_observations = data_info.no_more_missing_observations;
-missing_value = data_info.missing_value;
-
-offset = npar-np;
-fname_=M_.fname;
-
-options_ = set_default_option(options_,'opt_gsa',1);
-options_gsa_ = options_.opt_gsa;
-
-if options_gsa_.pprior,
- namfile=[fname_,'_prior'];
-else
- namfile=[fname_,'_mc'];
-end
-load([OutDir,'/',namfile],'lpmat', 'lpmat0', 'istable')
-% load(options_.mode_file)
-%%
-%%
-%%
-x=[lpmat0(istable,:) lpmat(istable,:)];
-clear lpmat lpmat0 istable %iunstable egg yys T
-B = size(x,1);
-[atT,innov,measurement_error,updated_variables,ys,trend_coeff, aK] = DsgeSmoother(x(1,:)',gend,data,data_index,missing_value);
-n1=size(atT,1);
-
-nfil=B/40;
-stock_smooth = zeros(M_.endo_nbr,gend,40);
-stock_filter = zeros(M_.endo_nbr,gend+1,40);
-stock_ys = zeros(40, M_.endo_nbr);
-logpo2=zeros(B,1);
-%%
-h = waitbar(0,'MC smoother ...');
-delete([OutDir,'/',namfile,'_*.mat'])
-ib=0;
-ifil=0;
-opt_gsa=options_.opt_gsa;
-
-for b=1:B
- ib=ib+1;
- deep = x(b,:)';
- set_all_parameters(deep);
- dr = resol(oo_.steady_state,0);
- %deep(1:offset) = xparam1(1:offset);
- logpo2(b,1) = DsgeLikelihood(deep,gend,data,data_index,number_of_observations,no_more_missing_observations);
- if opt_gsa.lik_only==0,
- [atT,innov,measurement_error,updated_variables,ys,trend_coeff, aK] = DsgeSmoother(deep,gend,data,data_index,missing_value);
- stock_smooth(:,:,ib)=atT(1:M_.endo_nbr,:);
-% stock_filter(:,:,ib)=updated_variables(1:M_.endo_nbr,:);
- stock_filter(:,:,ib)=aK(1,1:M_.endo_nbr,:);
- stock_ys(ib,:)=ys';
- if ib==40,
- ib=0;
- ifil=ifil+1;
- save([OutDir,'/',namfile,'_',num2str(ifil)],'stock_smooth','stock_filter','stock_ys')
- stock_smooth = zeros(M_.endo_nbr,gend,40);
- stock_filter = zeros(M_.endo_nbr,gend+1,40);
- stock_ys = zeros(40, M_.endo_nbr);
- end
- end
- waitbar(b/B,h,['MC smoother ...',num2str(b),'/',num2str(B)]);
-end
-close(h)
-if opt_gsa.lik_only==0,
-if ib>0,
- ifil=ifil+1;
- stock_smooth = stock_smooth(:,:,1:ib);
- stock_filter = stock_filter(:,:,1:ib);
- stock_ys = stock_ys(1:ib,:);
- save([OutDir,'/',namfile,'_',num2str(ifil)],'stock_smooth','stock_filter','stock_ys')
-end
-end
-stock_gend=gend;
-stock_data=data;
-save([OutDir,'/',namfile],'x','logpo2','stock_gend','stock_data','-append')
diff --git a/GSA_distrib/4.2/fdjac.m b/GSA_distrib/4.2/fdjac.m
deleted file mode 100644
index 2ff746531b5393759295f07a94ea67a7a24230bf..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/fdjac.m
+++ /dev/null
@@ -1,37 +0,0 @@
-% FDJAC Computes two-sided finite difference Jacobian
-% USAGE
-% fjac = fdjac(f,x,P1,P2,...)
-% INPUTS
-% f : name of function of form fval = f(x)
-% x : evaluation point
-% P1,P2,... : additional arguments for f (optional)
-% OUTPUT
-% fjac : finite differnce Jacobian
-%
-% USER OPTIONS (SET WITH OPSET)
-% tol : a factor used in setting the step size
-% increase if f is inaccurately computed
-
-% Copyright (c) 1997-2002, Paul L. Fackler & Mario J. Miranda
-% paul_fackler@ncsu.edu, miranda.4@osu.edu
-
-function fjac = fdjac(f,x,varargin)
-
-tol = optget(mfilename,'tol',eps.^(1/3));
-
-h = tol.*max(abs(x),1);
-xh1=x+h; xh0=x-h;
-h=xh1-xh0;
-for j=1:length(x);
- xx = x;
- xx(j) = xh1(j); f1=feval(f,xx,varargin{:});
- xx(j) = xh0(j); f0=feval(f,xx,varargin{:});
- fjac(:,j) = (f1-f0)/h(j);
-% v = (f1-f0);
-% k = find(abs(v) < 1e-8);
-% v(k) = 0;
-%
-% fjac(:,j) = v/h(j);
-end
-
-feval(f,x,varargin{:});
\ No newline at end of file
diff --git a/GSA_distrib/4.2/filt_mc_.m b/GSA_distrib/4.2/filt_mc_.m
deleted file mode 100644
index ba582de371a0f1a2f1e77646e29d09894aaaa976..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/filt_mc_.m
+++ /dev/null
@@ -1,687 +0,0 @@
-function [rmse_MC, ixx] = filt_mc_(OutDir,data_info)
-% function [rmse_MC, ixx] = filt_mc_(OutDir)
-% copyright Marco Ratto 2006
-% inputs (from opt_gsa structure)
-% vvarvecm = options_gsa_.var_rmse;
-% loadSA = options_gsa_.load_rmse;
-% pfilt = options_gsa_.pfilt_rmse;
-% alpha = options_gsa_.alpha_rmse;
-% alpha2 = options_gsa_.alpha2_rmse;
-% istart = options_gsa_.istart_rmse;
-% alphaPC = 0.5;
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global bayestopt_ estim_params_ M_ options_ oo_
-
-options_gsa_=options_.opt_gsa;
-vvarvecm = options_gsa_.var_rmse;
-loadSA = options_gsa_.load_rmse;
-pfilt = options_gsa_.pfilt_rmse;
-alpha = options_gsa_.alpha_rmse;
-alpha2 = options_gsa_.alpha2_rmse;
-istart = options_gsa_.istart_rmse;
-alphaPC = 0.5;
-
-fname_ = M_.fname;
-lgy_ = M_.endo_names;
-dr_ = oo_.dr;
-
-disp(' ')
-disp(' ')
-disp('Starting sensitivity analysis')
-disp('for the fit of EACH observed series ...')
-disp(' ')
-disp('Deleting old SA figures...')
-a=dir([OutDir,'/*.*']);
-tmp1='0';
-if options_.opt_gsa.ppost,
- tmp=['_rmse_post'];
-else
- if options_.opt_gsa.pprior
- tmp=['_rmse_prior'];
- else
- tmp=['_rmse_mc'];
- end
- if options_gsa_.lik_only,
- tmp1 = [tmp,'_post_SA'];
- tmp = [tmp,'_lik_SA'];
- end
-end
-for j=1:length(a),
- if strmatch([fname_,tmp],a(j).name),
- disp(a(j).name)
- delete([OutDir,'/',a(j).name])
- end,
- if strmatch([fname_,tmp1],a(j).name),
- disp(a(j).name)
- delete([OutDir,'/',a(j).name])
- end,
-end
-disp('done !')
-
-
-nshock=estim_params_.nvx + estim_params_.nvn + estim_params_.ncx + estim_params_.ncn;
-npar=estim_params_.np;
-if ~isempty(options_.mode_file),
- load(options_.mode_file,'xparam1'),
-end
-if options_.opt_gsa.ppost,
- c=load([fname_,'_mean'],'xparam1');
- xparam1_mean=c.xparam1;
- clear c
-elseif ~isempty(options_.mode_file) & ~isempty(ls([fname_,'_mean.mat']))
- c=load([fname_,'_mean'],'xparam1');
- xparam1_mean=c.xparam1;
- clear c
-end
-
-if options_.opt_gsa.ppost,
- fnamtmp=[fname_,'_post'];
- DirectoryName = CheckPath('metropolis');
-else
- if options_.opt_gsa.pprior
- fnamtmp=[fname_,'_prior'];
- DirectoryName = CheckPath(['gsa' filesep 'prior']);
- else
- fnamtmp=[fname_,'_mc'];
- DirectoryName = CheckPath(['gsa' filesep 'mc']);
- end
-end
-if ~loadSA,
- if exist('xparam1','var')
- set_all_parameters(xparam1);
- steady_;
- ys_mode=oo_.steady_state;
- end
- if exist('xparam1_mean','var')
- set_all_parameters(xparam1_mean);
- steady_;
- ys_mean=oo_.steady_state;
- end
- % eval(options_.datafile)
- obs = dat_fil_(options_.datafile);
- %stock_gend=data_info.gend;
- %stock_data = data_info.data;
- load([DirectoryName '/' M_.fname '_data.mat']); filfilt = dir([DirectoryName '/' M_.fname '_filter_step_ahead*.mat']);
- filparam = dir([DirectoryName '/' M_.fname '_param*.mat']);
- x=[];
- logpo2=[];
- sto_ys=[];
- for j=1:length(filparam),
- %load([DirectoryName '/' M_.fname '_param',int2str(j),'.mat']);
- if isempty(strmatch([M_.fname '_param_irf'],filparam(j).name))
- load([DirectoryName '/' filparam(j).name]);
- x=[x; stock];
- logpo2=[logpo2; stock_logpo];
- sto_ys=[sto_ys; stock_ys];
- clear stock stock_logpo stock_ys;
- end
- end
- nruns=size(x,1);
- nfilt=floor(pfilt*nruns);
- if options_.opt_gsa.ppost || (options_.opt_gsa.ppost==0 && options_.opt_gsa.lik_only==0)
- disp(' ')
- disp('Computing RMSE''s...')
- fobs = options_.first_obs;
- nobs=options_.nobs;
- for i=1:size(vvarvecm,1),
- vj=deblank(vvarvecm(i,:));
- eval(['vobs =obs.',vj,'(fobs:fobs-1+nobs);'])
- if options_.prefilter == 1
- %eval([vj,'=',vj,'-bayestopt_.mean_varobs(i);'])
- %eval([vj,'=',vj,'-mean(',vj,',1);'])
- vobs = vobs-mean(vobs,1);
- end
-
- jxj = strmatch(vj,lgy_(dr_.order_var,:),'exact');
- js = strmatch(vj,lgy_,'exact');
- if exist('xparam1','var')
- % if isfield(oo_,'FilteredVariables')
- % eval(['rmse_mode(i) = sqrt(mean((vobs(istart:end)-oo_.steady_state(js)-oo_.FilteredVariables.',vj,'(istart:end-1)).^2));'])
- % else
- [alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK] = DsgeSmoother(xparam1,stock_gend,stock_data,{},0);
- y0 = squeeze(aK(1,jxj,:)) + ...
- kron(ys_mode(js,:),ones(size(aK,3),1));
- % y0 = ahat(jxj,:)' + ...
- % kron(ys_mode(js,:),ones(size(ahat,2),1));
- rmse_mode(i) = sqrt(mean((vobs(istart:end)-y0(istart:end-1)).^2));
- % end
- end
- y0=zeros(nobs+1,nruns);
- nbb=0;
- for j=1:length(filfilt),
- load([DirectoryName '/' M_.fname '_filter_step_ahead',num2str(j),'.mat']);
- nb = size(stock,4);
- % y0(:,nbb+1:nbb+nb)=squeeze(stock(1,js,:,:)) + ...
- % kron(sto_ys(nbb+1:nbb+nb,js)',ones(size(stock,3),1));
- y0(:,nbb+1:nbb+nb)=squeeze(stock(1,js,1:nobs+1,:)) + ...
- kron(sto_ys(nbb+1:nbb+nb,js)',ones(nobs+1,1));
- %y0(:,:,size(y0,3):size(y0,3)+size(stock,3))=stock;
- nbb=nbb+nb;
- clear stock;
- end
- y0M=mean(y0,2);
- for j=1:nruns,
- rmse_MC(j,i) = sqrt(mean((vobs(istart:end)-y0(istart:end-1,j)).^2));
- end
- if exist('xparam1_mean','var')
- %eval(['rmse_pmean(i) = sqrt(mean((',vj,'(fobs-1+istart:fobs-1+nobs)-y0M(istart:end-1)).^2));'])
- [alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK] = DsgeSmoother(xparam1_mean,stock_gend,stock_data,{},0);
- y0 = squeeze(aK(1,jxj,:)) + ...
- kron(ys_mean(js,:),ones(size(aK,3),1));
- % y0 = ahat(jxj,:)' + ...
- % kron(ys_mean(js,:),ones(size(ahat,2),1));
- rmse_pmean(i) = sqrt(mean((vobs(istart:end)-y0(istart:end-1)).^2));
- end
- end
- clear stock_filter;
- end
- for j=1:nruns,
- lnprior(j,1) = priordens(x(j,:)',bayestopt_.pshape,bayestopt_.p1,bayestopt_.p2,bayestopt_.p3,bayestopt_.p4);
- end
- likelihood=logpo2(:)-lnprior(:);
- disp('... done!')
-
- if options_.opt_gsa.ppost
- save([OutDir,'/',fnamtmp], 'x', 'logpo2', 'likelihood', 'rmse_MC', 'rmse_mode','rmse_pmean')
- else
- if options_.opt_gsa.lik_only
- save([OutDir,'/',fnamtmp], 'likelihood', '-append')
- else
- save([OutDir,'/',fnamtmp], 'likelihood', 'rmse_MC','-append')
- if exist('xparam1_mean','var')
- save([OutDir,'/',fnamtmp], 'rmse_pmean','-append')
- end
- if exist('xparam1','var')
- save([OutDir,'/',fnamtmp], 'rmse_mode','-append')
- end
- end
- end
-else
- if options_.opt_gsa.lik_only & options_.opt_gsa.ppost==0
- load([OutDir,'/',fnamtmp],'x','logpo2','likelihood');
- else
- load([OutDir,'/',fnamtmp],'x','logpo2','likelihood','rmse_MC','rmse_mode','rmse_pmean');
- end
- lnprior=logpo2(:)-likelihood(:);
- nruns=size(x,1);
- nfilt=floor(pfilt*nruns);
-end
-% smirnov tests
-nfilt0=nfilt*ones(size(vvarvecm,1),1);
-logpo2=logpo2(:);
-if ~options_.opt_gsa.ppost
- [dum, ipost]=sort(-logpo2);
- [dum, ilik]=sort(-likelihood);
-end
-if ~options_.opt_gsa.ppost & options_.opt_gsa.lik_only
- if options_.opt_gsa.pprior
- anam='rmse_prior_post';
- else
- anam='rmse_mc_post';
- end
- stab_map_1(x, ipost(1:nfilt), ipost(nfilt+1:end), anam, 1,[],OutDir);
- stab_map_2(x(ipost(1:nfilt),:),alpha2,anam, OutDir);
- if options_.opt_gsa.pprior
- anam='rmse_prior_lik';
- else
- anam='rmse_mc_lik';
- end
- stab_map_1(x, ilik(1:nfilt), ilik(nfilt+1:end), anam, 1,[],OutDir);
- stab_map_2(x(ilik(1:nfilt),:),alpha2,anam, OutDir);
-else
- for i=1:size(vvarvecm,1),
- [dum, ixx(:,i)]=sort(rmse_MC(:,i));
- if options_.opt_gsa.ppost,
- %nfilt0(i)=length(find(rmse_MC(:,i)<rmse_pmean(i)));
- rmse_txt=rmse_pmean;
- else
- if options_.opt_gsa.pprior | ~exist('rmse_pmean'),
- if exist('rmse_mode'),
- rmse_txt=rmse_mode;
- else
- rmse_txt=NaN(1,size(rmse_MC,2));
- end
- else
- %nfilt0(i)=length(find(rmse_MC(:,i)<rmse_pmean(i)));
- rmse_txt=rmse_pmean;
- end
- end
- for j=1:npar+nshock,
- [H,P,KSSTAT] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j), alpha);
- [H1,P1,KSSTAT1] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j),alpha,1);
- [H2,P2,KSSTAT2] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j),alpha,-1);
- if H1 & H2==0,
- SS(j,i)=1;
- elseif H1==0,
- SS(j,i)=-1;
- else
- SS(j,i)=0;
- end
- PP(j,i)=P;
- end
- end
- ifig=0;
- for i=1:size(vvarvecm,1),
- if mod(i,9)==1,
- ifig=ifig+1;
- figure('name',['Prior ',int2str(ifig)])
- end
- subplot(3,3,i-9*(ifig-1))
- h=cumplot(lnprior(ixx(1:nfilt0(i),i)));
- set(h,'color','red')
- hold on, cumplot(lnprior)
- h=cumplot(lnprior(ixx(nfilt0(i)+1:end,i)));
- set(h,'color','green')
- title(vvarvecm(i,:))
- if mod(i,9)==0 | i==size(vvarvecm,1)
- if options_.opt_gsa.ppost
- saveas(gcf,[OutDir,'/',fname_,'_rmse_post_lnprior',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_post_lnprior',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_post_lnprior',int2str(ifig)]);
- else
- if options_.opt_gsa.pprior
- saveas(gcf,[OutDir,'/',fname_,'_rmse_prior_lnprior',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_prior_lnprior',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_prior_lnprior',int2str(ifig)]);
- else
- saveas(gcf,[OutDir,'/',fname_,'_rmse_mc_lnprior',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_mc_lnprior',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_mc_lnprior',int2str(ifig)]);
- end
- end
- close(gcf)
- end
- end
- ifig=0;
- for i=1:size(vvarvecm,1),
- if mod(i,9)==1,
- ifig=ifig+1;
- figure('name',['Likelihood ',int2str(ifig)])
- end
- subplot(3,3,i-9*(ifig-1))
- h=cumplot(likelihood(ixx(1:nfilt0(i),i)));
- set(h,'color','red')
- hold on, h=cumplot(likelihood);
- h=cumplot(likelihood(ixx(nfilt0(i)+1:end,i)));
- set(h,'color','green')
- title(vvarvecm(i,:))
- if options_.opt_gsa.ppost==0,
- set(gca,'xlim',[min( likelihood(ixx(1:nfilt0(i),i)) ) max( likelihood(ixx(1:nfilt0(i),i)) )])
- end
- if mod(i,9)==0 | i==size(vvarvecm,1)
- if options_.opt_gsa.ppost
- saveas(gcf,[OutDir,'/',fname_,'_rmse_post_lnlik',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_post_lnlik',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_post_lnlik',int2str(ifig)]);
- else
- if options_.opt_gsa.pprior
- saveas(gcf,[OutDir,'/',fname_,'_rmse_prior_lnlik',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_prior_lnlik',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_prior_lnlik',int2str(ifig)]);
- else
- saveas(gcf,[OutDir,'/',fname_,'_rmse_mc_lnlik',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_mc_lnlik',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_mc_lnlik',int2str(ifig)]);
- end
- end
- close(gcf)
- end
- end
- ifig=0;
- for i=1:size(vvarvecm,1),
- if mod(i,9)==1,
- ifig=ifig+1;
- figure('name',['Posterior ',int2str(ifig)])
- end
- subplot(3,3,i-9*(ifig-1))
- h=cumplot(logpo2(ixx(1:nfilt0(i),i)));
- set(h,'color','red')
- hold on, h=cumplot(logpo2);
- h=cumplot(logpo2(ixx(nfilt0(i)+1:end,i)));
- set(h,'color','green')
- title(vvarvecm(i,:))
- if options_.opt_gsa.ppost==0,
- set(gca,'xlim',[min( logpo2(ixx(1:nfilt0(i),i)) ) max( logpo2(ixx(1:nfilt0(i),i)) )])
- end
- if mod(i,9)==0 | i==size(vvarvecm,1)
- if options_.opt_gsa.ppost
- saveas(gcf,[OutDir,'/',fname_,'_rmse_post_lnpost',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_post_lnpost',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_post_lnpost',int2str(ifig)]);
- else
- if options_.opt_gsa.pprior
- saveas(gcf,[OutDir,'/',fname_,'_rmse_prior_lnpost',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_prior_lnpost',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_prior_lnpost',int2str(ifig)]);
- else
- saveas(gcf,[OutDir,'/',fname_,'_rmse_mc_lnpost',int2str(ifig)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_mc_lnpost',int2str(ifig)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_mc_lnpost',int2str(ifig)]);
- end
- end
- close(gcf)
- end
- end
-
- param_names='';
- for j=1:npar+nshock,
- param_names=str2mat(param_names, bayestopt_.name{j});
- end
- param_names=param_names(2:end,:);
-
- disp(' ')
- disp('RMSE over the MC sample:')
- disp(' min yr RMSE max yr RMSE')
- for j=1:size(vvarvecm,1),
- disp([vvarvecm(j,:), sprintf('%15.5g',[(min(rmse_MC(:,j))) [(max(rmse_MC(:,j)))]])])
- end
- invar = find( std(rmse_MC)./mean(rmse_MC)<=0.0001 );
- if ~isempty(invar)
- disp(' ')
- disp(' ')
- disp('RMSE is not varying significantly over the MC sample for the following variables:')
- disp(vvarvecm(invar,:))
- disp('These variables are excluded from SA')
- disp('[Unless you treat these series as exogenous, there is something wrong in your estimation !]')
- end
- ivar = find( std(rmse_MC)./mean(rmse_MC)>0.0001 );
- vvarvecm=vvarvecm(ivar,:);
- rmse_MC=rmse_MC(:,ivar);
-
- disp(' ')
- % if options_.opt_gsa.ppost==0 & options_.opt_gsa.pprior,
- disp(['Sample filtered the ',num2str(pfilt*100),'% best RMSE''s for each observed series ...' ])
- % else
- % disp(['Sample filtered the best RMSE''s smaller than RMSE at the posterior mean ...' ])
- % end
- % figure, boxplot(rmse_MC)
- % set(gca,'xticklabel',vvarvecm)
- % saveas(gcf,[fname_,'_SA_RMSE'])
-
- disp(' ')
- disp(' ')
- disp('RMSE ranges after filtering:')
- if options_.opt_gsa.ppost==0 & options_.opt_gsa.pprior,
- disp([' best ',num2str(pfilt*100),'% filtered remaining 90%'])
- disp([' min max min max posterior mode'])
- else
- disp([' best filtered remaining '])
- disp([' min max min max posterior mean'])
- end
- for j=1:size(vvarvecm,1),
- disp([vvarvecm(j,:), sprintf('%15.5g',[min(rmse_MC(ixx(1:nfilt0(j),j),j)) ...
- max(rmse_MC(ixx(1:nfilt0(j),j),j)) ...
- min(rmse_MC(ixx(nfilt0(j)+1:end,j),j)) ...
- max(rmse_MC(ixx(nfilt0(j)+1:end,j),j)) ...
- rmse_txt(j)])])
- % disp([vvarvecm(j,:), sprintf('%15.5g',[min(logpo2(ixx(1:nfilt,j))) ...
- % max(logpo2(ixx(1:nfilt,j))) ...
- % min(logpo2(ixx(nfilt+1:end,j))) ...
- % max(logpo2(ixx(nfilt+1:end,j)))])])
- end
-
- SP=zeros(npar+nshock,size(vvarvecm,1));
- for j=1:size(vvarvecm,1),
- ns=find(PP(:,j)<alpha);
- SP(ns,j)=ones(size(ns));
- SS(:,j)=SS(:,j).*SP(:,j);
- end
-
- for j=1:npar+nshock, %estim_params_.np,
- nsp(j)=length(find(SP(j,:)));
- end
- snam0=param_names(find(nsp==0),:);
- snam1=param_names(find(nsp==1),:);
- snam2=param_names(find(nsp>1),:);
- snam=param_names(find(nsp>0),:);
- % snam0=bayestopt_.name(find(nsp==0));
- % snam1=bayestopt_.name(find(nsp==1));
- % snam2=bayestopt_.name(find(nsp>1));
- % snam=bayestopt_.name(find(nsp>0));
- nsnam=(find(nsp>1));
-
- disp(' ')
- disp(' ')
- disp('These parameters do not affect significantly the fit of ANY observed series:')
- disp(snam0)
- disp(' ')
- disp('These parameters affect ONE single observed series:')
- disp(snam1)
- disp(' ')
- disp('These parameters affect MORE THAN ONE observed series: trade off exists!')
- disp(snam2)
-
-
- %pnam=bayestopt_.name(end-estim_params_.np+1:end);
- pnam=bayestopt_.name;
-
- % plot trade-offs
- a00=jet(size(vvarvecm,1));
- for ix=1:ceil(length(nsnam)/5),
- figure,
- for j=1+5*(ix-1):min(size(snam2,1),5*ix),
- subplot(2,3,j-5*(ix-1))
- %h0=cumplot(x(:,nsnam(j)+nshock));
- h0=cumplot(x(:,nsnam(j)));
- set(h0,'color',[0 0 0])
- hold on,
- np=find(SP(nsnam(j),:));
- %a0=jet(nsp(nsnam(j)));
- a0=a00(np,:);
- for i=1:nsp(nsnam(j)), %size(vvarvecm,1),
- %h0=cumplot(x(ixx(1:nfilt,np(i)),nsnam(j)+nshock));
- h0=cumplot(x(ixx(1:nfilt0(np(i)),np(i)),nsnam(j)));
- set(h0,'color',a0(i,:))
- end
- ydum=get(gca,'ylim');
- %xdum=xparam1(nshock+nsnam(j));
- if exist('xparam1')
- xdum=xparam1(nsnam(j));
- h1=plot([xdum xdum],ydum);
- set(h1,'color',[0.85 0.85 0.85],'linewidth',2)
- end
- xlabel('')
- title([pnam{nsnam(j)}],'interpreter','none')
- end
- %subplot(3,2,6)
- h0=legend(str2mat('base',vvarvecm(np,:)),0);
- set(h0,'fontsize',6,'position',[0.7 0.1 0.2 0.3],'interpreter','none')
- %h0=legend({'base',vnam{np}}',0);
- %set(findobj(get(h0,'children'),'type','text'),'interpreter','none')
- if options_.opt_gsa.ppost
- saveas(gcf,[OutDir,'/',fname_,'_rmse_post_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_post_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_post_' int2str(ix)]);
- else
- if options_.opt_gsa.pprior
- saveas(gcf,[OutDir,'/',fname_,'_rmse_prior_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_prior_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_prior_' int2str(ix)]);
- else
- saveas(gcf,[OutDir,'/',fname_,'_rmse_mc_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_mc_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_mc_' int2str(ix)]);
- end
- end
- end
- close all
-
- for j=1:size(SP,2),
- nsx(j)=length(find(SP(:,j)));
- end
-
- number_of_grid_points = 2^9; % 2^9 = 512 !... Must be a power of two.
- bandwidth = 0; % Rule of thumb optimal bandwidth parameter.
- kernel_function = 'gaussian'; % Gaussian kernel for Fast Fourrier Transform approximaton.
- %kernel_function = 'uniform'; % Gaussian kernel for Fast Fourrier Transform approximaton.
-
- for ix=1:ceil(length(nsnam)/5),
- figure,
- for j=1+5*(ix-1):min(size(snam2,1),5*ix),
- subplot(2,3,j-5*(ix-1))
- optimal_bandwidth = mh_optimal_bandwidth(x(:,nsnam(j)),size(x,1),bandwidth,kernel_function);
- [x1,f1] = kernel_density_estimate(x(:,nsnam(j)),number_of_grid_points,...
- size(x,1),optimal_bandwidth,kernel_function);
- h0 = plot(x1, f1,'k');
- hold on,
- np=find(SP(nsnam(j),:));
- %a0=jet(nsp(nsnam(j)));
- a0=a00(np,:);
- for i=1:nsp(nsnam(j)), %size(vvarvecm,1),
- optimal_bandwidth = mh_optimal_bandwidth(x(ixx(1:nfilt0(np(i)),np(i)),nsnam(j)),nfilt,bandwidth,kernel_function);
- [x1,f1] = kernel_density_estimate(x(ixx(1:nfilt0(np(i)),np(i)),nsnam(j)),number_of_grid_points,...
- nfilt, optimal_bandwidth,kernel_function);
- h0 = plot(x1, f1);
- set(h0,'color',a0(i,:))
- end
- ydum=get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)]);
- if exist('xparam1')
- %xdum=xparam1(nshock+nsnam(j));
- xdum=xparam1(nsnam(j));
- h1=plot([xdum xdum],[0 ydum(2)]);
- set(h1,'color',[0.85 0.85 0.85],'linewidth',2)
- end
- xlabel('')
- title([pnam{nsnam(j)}],'interpreter','none')
- end
- h0=legend(str2mat('base',vvarvecm(np,:)),0);
- set(h0,'fontsize',6,'position',[0.7 0.1 0.2 0.3],'interpreter','none')
- %h0=legend({'base',vnam{np}}',0);
- %set(findobj(get(h0,'children'),'type','text'),'interpreter','none')
- if options_.opt_gsa.ppost
- saveas(gcf,[OutDir,'/',fname_,'_rmse_post_dens_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_post_dens_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_post_dens_' int2str(ix)]);
- else
- if options_.opt_gsa.pprior
- saveas(gcf,[OutDir,'/',fname_,'_rmse_prior_dens_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_prior_dens_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_prior_dens_' int2str(ix)]);
- else
- saveas(gcf,[OutDir,'/',fname_,'_rmse_mc_dens_',num2str(ix)])
- eval(['print -depsc2 ' OutDir '/' fname_ '_rmse_mc_dens_' int2str(ix)]);
- eval(['print -dpdf ' OutDir '/' fname_ '_rmse_mc_dens_' int2str(ix)]);
- end
- end
- end
- close all
-
- % for j=1:size(SP,2),
- % nfig=0;
- % np=find(SP(:,j));
- % for i=1:nsx(j), %size(vvarvecm,1),
- % if mod(i,12)==1,
- % nfig=nfig+1;
- % %figure('name',['Sensitivity of fit of ',vnam{j}]),
- % figure('name',['Sensitivity of fit of ',deblank(vvarvecm(j,:)),' ',num2str(nfig)]),
- % end
- %
- % subplot(3,4,i-12*(nfig-1))
- % optimal_bandwidth = mh_optimal_bandwidth(x(ixx(1:nfilt,j),np(i)),nfilt,bandwidth,kernel_function);
- % [x1,f1] = kernel_density_estimate(x(ixx(1:nfilt,j),np(i)),number_of_grid_points,...
- % nfilt, optimal_bandwidth,kernel_function);
- % plot(x1, f1,':k','linewidth',2)
- % optimal_bandwidth = mh_optimal_bandwidth(x(ixx(nfilt+1:end,j),np(i)),nruns-nfilt,bandwidth,kernel_function);
- % [x1,f1] = kernel_density_estimate(x(ixx(nfilt+1:end,j),np(i)),number_of_grid_points,...
- % nruns-nfilt,optimal_bandwidth,kernel_function);
- % hold on, plot(x1, f1,'k','linewidth',2)
- % ydum=get(gca,'ylim');
- % %xdum=xparam1(nshock+np(i));
- % xdum=xparam1(np(i));
- % h1=plot([xdum xdum],ydum);
- % set(h1,'color',[0.85 0.85 0.85],'linewidth',2)
- % %xdum1=mean(x(ixx(1:nfilt,j),np(i)+nshock));
- % xdum1=mean(x(ixx(1:nfilt,j),np(i)));
- % h2=plot([xdum1 xdum1],ydum);
- % set(h2,'color',[0 1 0],'linewidth',2)
- % % h0=cumplot(x(nfilt+1:end,np(i)+nshock));
- % % set(h0,'color',[1 1 1])
- % % hold on,
- % % h0=cumplot(x(ixx(1:nfilt,j),np(i)+nshock));
- % % set(h0,'linestyle',':','color',[1 1 1])
- % %title([pnam{np(i)}])
- % title([pnam{np(i)},'. K-S prob ', num2str(PP(np(i),j))],'interpreter','none')
- % xlabel('')
- % if mod(i,12)==0 | i==nsx(j),
- % saveas(gcf,[fname_,'_rmse_',deblank(vvarvecm(j,:)),'_',int2str(nfig)])
- % close(gcf)
- % end
- % end
- % end
-
-
- disp(' ')
- disp(' ')
- disp('Sensitivity table (significance and direction):')
- vav=char(zeros(1, size(param_names,2)+3 ));
- ibl = 12-size(vvarvecm,2);
- for j=1:size(vvarvecm,1),
- vav = [vav, char(zeros(1,ibl)),vvarvecm(j,:)];
- end
- disp(vav)
- for j=1:npar+nshock, %estim_params_.np,
- %disp([param_names(j,:), sprintf('%8.5g',SP(j,:))])
- disp([param_names(j,:),' ', sprintf('%12.3g',PP(j,:))])
- disp([char(zeros(1, size(param_names,2)+3 )),sprintf(' (%6g)',SS(j,:))])
- end
-
-
- disp(' ')
- disp(' ')
- disp('Starting bivariate analysis:')
-
- for i=1:size(vvarvecm,1)
- if options_.opt_gsa.ppost
- fnam = ['rmse_post_',deblank(vvarvecm(i,:))];
- else
- if options_.opt_gsa.pprior
- fnam = ['rmse_prior_',deblank(vvarvecm(i,:))];
- else
- fnam = ['rmse_mc_',deblank(vvarvecm(i,:))];
- end
- end
- stab_map_2(x(ixx(1:nfilt0(i),i),:),alpha2,fnam, OutDir);
-
- % [pc,latent,explained] = pcacov(c0);
- % %figure, bar([explained cumsum(explained)])
- % ifig=0;
- % j2=0;
- % for j=1:npar+nshock,
- % i2=find(abs(pc(:,j))>alphaPC);
- % if ~isempty(i2),
- % j2=j2+1;
- % if mod(j2,12)==1,
- % ifig=ifig+1;
- % figure('name',['PCA of the filtered sample ',deblank(vvarvecm(i,:)),' ',num2str(ifig)]),
- % end
- % subplot(3,4,j2-(ifig-1)*12)
- % bar(pc(i2,j)),
- % set(gca,'xticklabel',bayestopt_.name(i2)),
- % set(gca,'xtick',[1:length(i2)])
- % title(['PC ',num2str(j),'. Explained ',num2str(explained(j)),'%'])
- % end
- % if (mod(j2,12)==0 | j==(npar+nshock)) & j2,
- % saveas(gcf,[fname_,'_SA_PCA_',deblank(vvarvecm(i,:)),'_',int2str(ifig)])
- % end
- % end
- % close all
- end
-
-end
\ No newline at end of file
diff --git a/GSA_distrib/4.2/gamm_cdf.m b/GSA_distrib/4.2/gamm_cdf.m
deleted file mode 100644
index a11d0962a4cd911ae962b4830afdb383572d532f..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/gamm_cdf.m
+++ /dev/null
@@ -1,27 +0,0 @@
-function cdf = gamm_cdf (x, a)
-% PURPOSE: returns the cdf at x of the gamma(a) distribution
-%---------------------------------------------------
-% USAGE: cdf = gamm_cdf(x,a)
-% where: x = a vector
-% a = a scalar gamma(a)
-%---------------------------------------------------
-% RETURNS:
-% a vector of cdf at each element of x of the gamma(a) distribution
-% --------------------------------------------------
-% SEE ALSO: gamm_d, gamm_pdf, gamm_rnd, gamm_inv
-%---------------------------------------------------
-
-% Anders Holtsberg, 18-11-93
-% Copyright (c) Anders Holtsberg
-
-if nargin ~= 2
-error('Wrong # of arguments to gamm_cdf');
-end;
-
-if any(any(a<=0))
- error('gamm_cdf: parameter a is wrong')
-end
-
-cdf = gammainc(x,a);
-I0 = find(x<0);
-cdf(I0) = zeros(size(I0));
diff --git a/GSA_distrib/4.2/gamm_inv.m b/GSA_distrib/4.2/gamm_inv.m
deleted file mode 100644
index 3bede95ba39a4309c86bc5e2c5e347c840dbb23f..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/gamm_inv.m
+++ /dev/null
@@ -1,50 +0,0 @@
-function x = gamm_inv(p,a,b)
-% PURPOSE: returns the inverse of the cdf at p of the gamma(a,b) distribution
-%---------------------------------------------------
-% USAGE: x = gamm_inv(p,a)
-% where: p = a vector of probabilities
-% a = a scalar parameter gamma(a)
-% b = scaling factor for gamma
-%---------------------------------------------------
-% RETURNS:
-% a vector x of the quantile at each element of p of the gamma(a) distribution
-% --------------------------------------------------
-% SEE ALSO: gamm_d, gamm_pdf, gamm_rnd, gamm_cdf
-%---------------------------------------------------
-
-% Anders Holtsberg, 18-11-93
-% Copyright (c) Anders Holtsberg
-% documentation modified by LeSage to fit the format
-% of the econometrics toolbox
-
- if (nargin < 2 | isempty(b))
- b=1;
- end
-
- if (nargin > 3)
- error('Wrong # of arguments to gamm_inv');
- end
-
-
-if any(any(abs(2*p-1)>1))
- error('gamm_inv: a probability should be 0<=p<=1')
-end
-if any(any(a<=0))
- error('gamma_inv: parameter a is wrong')
-end
-
-x = max(a-1,0.1);
-dx = 1;
-while any(any(abs(dx)>256*eps*max(x,1)))
- dx = (gamm_cdf(x,a) - p) ./ gamm_pdf(x,a);
- x = x - dx;
- x = x + (dx - x) / 2 .* (x<0);
-end
-
-I0 = find(p==0);
-x(I0) = zeros(size(I0));
-I1 = find(p==1);
-x(I1) = zeros(size(I0)) + Inf;
-
-
-x=x.*b;
diff --git a/GSA_distrib/4.2/gamm_pdf.m b/GSA_distrib/4.2/gamm_pdf.m
deleted file mode 100644
index 86f4ffb1deb909af6fd7a5fddc4825f9c996ffc2..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/gamm_pdf.m
+++ /dev/null
@@ -1,27 +0,0 @@
-function f = gamm_pdf (x, a)
-% PURPOSE: returns the pdf at x of the gamma(a) distribution
-%---------------------------------------------------
-% USAGE: pdf = gamm_pdf(x,a)
-% where: x = a vector
-% a = a scalar for gamma(a)
-%---------------------------------------------------
-% RETURNS:
-% a vector of pdf at each element of x of the gamma(a) distribution
-% --------------------------------------------------
-% SEE ALSO: gamm_cdf, gamm_rnd, gamm_inv
-%---------------------------------------------------
-
-% Anders Holtsberg, 18-11-93
-% Copyright (c) Anders Holtsberg
-
-if nargin ~= 2
-error('Wrong # of arguments to gamm_cdf');
-end;
-
-if any(any(a<=0))
- error('gamm_pdf: parameter a is wrong')
-end
-
-f = x .^ (a-1) .* exp(-x) ./ gamma(a);
-I0 = find(x<0);
-f(I0) = zeros(size(I0));
diff --git a/GSA_distrib/4.2/ghx2transition.m b/GSA_distrib/4.2/ghx2transition.m
deleted file mode 100644
index ad3cf110ab4b03f155ba28c0e13fbe183f13534d..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/ghx2transition.m
+++ /dev/null
@@ -1,54 +0,0 @@
-function [A,B] = ghx2transition(mm,iv,ic,aux)
-% [A,B] = ghx2transition(mm,iv,ic,aux)
-%
-% Adapted by M. Ratto from kalman_transition_matrix.m
-% (kalman_transition_matrix.m is part of DYNARE, copyright M. Juillard)
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global oo_ M_
-
- [nr1, nc1] = size(mm);
- ghx = mm(:, [1:(nc1-M_.exo_nbr)]);
- ghu = mm(:, [(nc1-M_.exo_nbr+1):end] );
- if nargin == 1
- oo_.dr.ghx = ghx;
- oo_.dr.ghu = ghu;
- endo_nbr = M_.endo_nbr;
- nstatic = oo_.dr.nstatic;
- npred = oo_.dr.npred;
- iv = (1:endo_nbr)';
- ic = [ nstatic+(1:npred) endo_nbr+(1:size(oo_.dr.ghx,2)-npred) ]';
- aux = oo_.dr.transition_auxiliary_variables;
- k = find(aux(:,2) > npred);
- aux(:,2) = aux(:,2) + nstatic;
- aux(k,2) = aux(k,2) + oo_.dr.nfwrd;
- end
- n_iv = length(iv);
- n_ir1 = size(aux,1);
- nr = n_iv + n_ir1;
-
- A = zeros(nr,nr);
- B = zeros(nr,M_.exo_nbr);
-
- i_n_iv = 1:n_iv;
- A(i_n_iv,ic) = ghx(iv,:);
- if n_ir1 > 0
- A(n_iv+1:end,:) = sparse(aux(:,1),aux(:,2),ones(n_ir1,1),n_ir1,nr);
- end
-
- B(i_n_iv,:) = ghu(iv,:);
diff --git a/GSA_distrib/4.2/log_trans_.m b/GSA_distrib/4.2/log_trans_.m
deleted file mode 100644
index b0ff26ddfa8afd10f51f6e8eab91dfa3ca88fcc2..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/log_trans_.m
+++ /dev/null
@@ -1,54 +0,0 @@
-function [yy, xdir, isig, lam]=log_trans_(y0,xdir0)
-
-if nargin==1,
- xdir0='';
-end
-f=inline('skewness(log(y+lam))','lam','y');
-isig=1;
-if ~(max(y0)<0 | min(y0)>0)
- if skewness(y0)<0,
- isig=-1;
- y0=-y0;
- end
- n=hist(y0,10);
- if n(1)>20*n(end),
- try lam=fzero(f,[-min(y0)+10*eps -min(y0)+abs(median(y0))],[],y0);
- catch
- yl(1)=f(-min(y0)+10*eps,y0);
- yl(2)=f(-min(y0)+abs(median(y0)),y0);
- if abs(yl(1))<abs(yl(2))
- lam=-min(y0)+eps;
- else
- lam = -min(y0)+abs(median(y0)); %abs(100*(1+min(y0)));
- end
- end
- yy = log(y0+lam);
- xdir=[xdir0,'_logskew'];
- else
- isig=0;
- lam=0;
- yy = log(y0.^2);
- xdir=[xdir0,'_logsquared'];
- end
-else
- if max(y0)<0
- isig=-1;
- y0=-y0;
- %yy=log(-y0);
- xdir=[xdir0,'_minuslog'];
- elseif min(y0)>0
- %yy=log(y0);
- xdir=[xdir0,'_log'];
- end
- try lam=fzero(f,[-min(y0)+10*eps -min(y0)+median(y0)],[],y0);
- catch
- yl(1)=f(-min(y0)+10*eps,y0);
- yl(2)=f(-min(y0)+abs(median(y0)),y0);
- if abs(yl(1))<abs(yl(2))
- lam=-min(y0)+eps;
- else
- lam = -min(y0)+abs(median(y0)); %abs(100*(1+min(y0)));
- end
- end
- yy = log(y0+lam);
-end
diff --git a/GSA_distrib/4.2/lptauSEQ.m b/GSA_distrib/4.2/lptauSEQ.m
deleted file mode 100644
index 3f34e9ef4a50c90d6d3d6674f84be7544c201f38..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/lptauSEQ.m
+++ /dev/null
@@ -1,25 +0,0 @@
-function [lpmat] = lptauSEQ(Nsam,Nvar)
-
-% [lpmat] = lptauSEQ(Nsam,Nvar)
-%
-% function call LPTAU and generates a sample of dimension Nsam for a
-% number of parameters Nvar
-%
-% Copyright (C) 2005 Marco Ratto
-% THIS PROGRAM WAS WRITTEN FOR MATLAB BY
-% Marco Ratto,
-% Unit of Econometrics and Statistics AF
-% (http://www.jrc.cec.eu.int/uasa/),
-% IPSC, Joint Research Centre
-% The European Commission,
-% TP 361, 21020 ISPRA(VA), ITALY
-% marco.ratto@jrc.it
-%
-
-
-clear lptau
-lpmat = zeros(Nsam, Nvar);
-for j=1:Nsam,
- lpmat(j,:)=LPTAU(j,Nvar);
-end
-return
diff --git a/GSA_distrib/4.2/map_ident_.m b/GSA_distrib/4.2/map_ident_.m
deleted file mode 100644
index 96c28557440c8b04b5a89d15b15b9bc0731318fd..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/map_ident_.m
+++ /dev/null
@@ -1,1531 +0,0 @@
-function map_ident_(OutputDirectoryName)
-global bayestopt_ M_ options_ estim_params_ oo_
-
-opt_gsa = options_.opt_gsa;
-fname_ = M_.fname;
-nliv = opt_gsa.morris_nliv;
-ntra = opt_gsa.morris_ntra;
-itrans = opt_gsa.trans_ident;
-
-np = estim_params_.np;
-if opt_gsa.load_ident_files,
- gsa_flag=0;
-else
- gsa_flag=-2;
-end
-
-pnames = M_.param_names(estim_params_.param_vals(:,1),:);
-
-filetoload=[OutputDirectoryName '/' fname_ '_prior'];
-load(filetoload,'lpmat','lpmat0','istable','T','yys','nspred','nboth','nfwrd')
-if ~isempty(lpmat0),
- lpmatx=lpmat0(istable,:);
-else
- lpmatx=[];
-end
-Nsam = size(lpmat,1);
-nshock = size(lpmat0,2);
-npT = np+nshock;
-
-fname_ = M_.fname;
-
-if opt_gsa.load_ident_files==0,
- % th moments
-% options_.ar = min(3,options_.ar);
-
- mss = yys(bayestopt_.mfys,:);
- mss = teff(mss(:,istable),Nsam,istable);
- yys = teff(yys(oo_.dr.order_var,istable),Nsam,istable);
- [vdec, cc, ac] = mc_moments(T, lpmatx, oo_.dr);
-
-
- if opt_gsa.morris==2,
- [pdraws, TAU, GAM] = dynare_identification(options_.options_ident,[lpmatx lpmat(istable,:)]);
- if max(max(abs(pdraws-[lpmatx lpmat(istable,:)])))==0,
- disp(['Sample check OK ', num2str(max(max(abs(pdraws-[lpmatx lpmat(istable,:)]))))]),
- clear pdraws;
- end
-% for j=1:length(istable), gas(:,j)=[vech(cc(:,:,j)); vec(ac(:,:,j))]; end
-% if ~isempty(mss),
-% gas = [mss(istable,:)'; gas];
-% end
-% if max(max(abs(GAM-gas)))<=1.e-8,
-% disp(['Moments check OK ',num2str(max(max(abs(GAM-gas))))]),
- clear GAM gas
-% end
- end
- if opt_gsa.morris~=1 & M_.exo_nbr>1,
- ifig=0;
- for j=1:M_.exo_nbr,
- if mod(j,6)==1
- figure('name',['Variance decomposition shocks']);
- ifig=ifig+1;
- iplo=0;
- end
- iplo=iplo+1;
- subplot(2,3,iplo)
- myboxplot(squeeze(vdec(:,j,:))',[],'.',[],10)
- % boxplot(squeeze(vdec(:,j,:))','whis',10,'symbol','.r')
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:size(options_.varobs,1)])
- set(gca,'xlim',[0.5 size(options_.varobs,1)+0.5])
- set(gca,'ylim',[-2 102])
- for ip=1:size(options_.varobs,1),
- text(ip,-4,deblank(options_.varobs(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- ylabel(' ')
- title(M_.exo_names(j,:),'interpreter','none')
- if mod(j,6)==0 | j==M_.exo_nbr,
- saveas(gcf,[OutputDirectoryName,'/',fname_,'_vdec_exo_',int2str(ifig)])
- eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_vdec_exo_',int2str(ifig)]);
- eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_vdec_exo_',int2str(ifig)]);
- close(gcf),
- end
- end
- end
- for j=1:size(cc,1)
- cc(j,j,:)=stand_(squeeze(log(cc(j,j,:))))./2;
- end
- [vdec, j0, ir_vdec, ic_vdec] = teff(vdec,Nsam,istable);
- [cc, j0, ir_cc, ic_cc] = teff(cc,Nsam,istable);
- [ac, j0, ir_ac, ic_ac] = teff(ac,Nsam,istable);
-
- [nr1, nc1, nnn] = size(T);
- endo_nbr = M_.endo_nbr;
- nstatic = oo_.dr.nstatic;
- npred = oo_.dr.npred;
- iv = (1:endo_nbr)';
- ic = [ nstatic+(1:npred) endo_nbr+(1:size(oo_.dr.ghx,2)-npred) ]';
- aux = oo_.dr.transition_auxiliary_variables;
- k = find(aux(:,2) > npred);
- aux(:,2) = aux(:,2) + nstatic;
- aux(k,2) = aux(k,2) + oo_.dr.nfwrd;
-
- dr.ghx = T(:, [1:(nc1-M_.exo_nbr)],1);
- dr.ghu = T(:, [(nc1-M_.exo_nbr+1):end], 1);
- [Aa,Bb] = kalman_transition_matrix(dr, ...
- iv, ic, aux, M_.exo_nbr);
-% bayestopt_.restrict_var_list, ...
-% bayestopt_.restrict_columns, ...
-% bayestopt_.restrict_aux, M_.exo_nbr);
- A = zeros(size(Aa,1),size(Aa,2)+size(Aa,1),length(istable));
- % Sig(estim_params_.var_exo(:,1))=lpmatx(1,:).^2;
- set_shocks_param(lpmatx(1,:));
- A(:,:,1)=[Aa, triu(Bb*M_.Sigma_e*Bb')];
- for j=2:length(istable),
- dr.ghx = T(:, [1:(nc1-M_.exo_nbr)],j);
- dr.ghu = T(:, [(nc1-M_.exo_nbr+1):end], j);
- [Aa,Bb] = kalman_transition_matrix(dr, ...
- iv, ic, aux, M_.exo_nbr);
-% bayestopt_.restrict_var_list, ...
-% bayestopt_.restrict_columns, ...
-% bayestopt_.restrict_aux, M_.exo_nbr);
- set_shocks_param(lpmatx(j,:));
- A(:,:,j)=[Aa, triu(Bb*M_.Sigma_e*Bb')];
- end
- clear T;
- clear lpmatx;
-
- [nr,nc,nn]=size(A);
- io=bayestopt_.mf2;
- % T1=A(io,1:nr,:);
- % ino=find(~ismember([1:nr],io));
- % T2=A(ino,1:nr,:);
- R=A(:,nr+1:nc,:);
-% [tadj, iff] = speed(A(1:nr,1:nr,:),R,io,0.5);
-% [tadj, j0, ir_tadj, ic_tadj] = teff(tadj,Nsam,istable);
-% [iff, j0, ir_if, ic_if] = teff(iff,Nsam,istable);
-
-
- [yt, j0]=teff(A,Nsam,istable);
- yt = [yys yt];
- if opt_gsa.morris==2,
-% iii=find(std(yt(istable,:))>1.e-8);
-% if max(max(abs(TAU-yt(istable,iii)')))<= 1.e-8,
-% err = max(max(abs(TAU-yt(istable,iii)')));
-% disp(['Model check OK ',num2str(err)]),
- clear TAU A
-% end
- else
- clear A,
- end
- % [yt1, j01]=teff(T1,Nsam,istable);
- % [yt2, j02]=teff(T2,Nsam,istable);
- % [ytr, j0r]=teff(R,Nsam,istable);
- %
- % yt=[yt1 yt2 ytr];
- save([OutputDirectoryName,'/',fname_,'_main_eff'],'ac','cc','vdec','yt','mss')
-else
- if opt_gsa.morris==2,
-% [pdraws, TAU, GAM] = dynare_identification([1:npT]); %,[lpmatx lpmat(istable,:)]);
- [pdraws, TAU, GAM] = dynare_identification(options_.options_ident);
- end
- load([OutputDirectoryName,'/',fname_,'_main_eff'],'ac','cc','vdec','yt','mss')
-end
-
-% for j=1:nr,
-% for i=1:nc,
-% y0=squeeze(A(j,i,:));
-% if max(y0)-min(y0)>1.e-10,
-% j0=j0+1;
-% y1=ones(size(lpmat,1),1)*NaN;
-% y1(istable,1)=y0;
-% yt(:,j0)=y1;
-% end
-% end
-% end
-% yt = yt(:,j0);
-
-if opt_gsa.morris==1,
- %OutputDir = CheckPath('GSA/SCREEN');
- if ~isempty(vdec),
- if opt_gsa.load_ident_files==0,
- SAMorris = [];
- for i=1:size(vdec,2),
- [SAmeas, SAMorris(:,:,i)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], vdec(:,i),nliv);
- end
- SAvdec = squeeze(SAMorris(:,1,:))';
- save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAvdec','vdec','ir_vdec','ic_vdec')
- else
- load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAvdec','vdec','ir_vdec','ic_vdec')
- end
-
- figure,
-% boxplot(SAvdec,'whis',10,'symbol','r.')
- myboxplot(SAvdec,[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:npT,
- text(ip,-2,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('All variance decomposition')
- saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_vdec'])
- eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_vdec']);
- eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_vdec']);
- close(gcf)
- else
- save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'vdec')
-
- end
-
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['EET variance decomposition observed variables']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_vdec==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAvdec(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAvdec(iv,:),[],'.',[],3)
-% else
-% plot(SAvdec(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-2,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_vdec_varobs_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_vdec_varobs_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_vdec_varobs_',int2str(ifig)]);
-% close(gcf)
-% end
-% end
-%
-% ifig = 0;
-% for j=1:M_.exo_nbr,
-% if mod(j,6)==1
-% figure('name',['EET variance decomposition shocks']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ic_vdec==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAvdec(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAvdec(iv,:),[],'.',[],3)
-% else
-% plot(SAvdec(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-2,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(M_.exo_names(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==M_.exo_nbr,
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_vdec_exo_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_vdec_exo_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_vdec_exo_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
-
- if opt_gsa.load_ident_files==0,
- SAMorris = [];
- ccac = [mss cc ac];
- for i=1:size(ccac,2),
- [SAmeas, SAMorris(:,:,i)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], [ccac(:,i)],nliv);
- end
- SAcc = squeeze(SAMorris(:,1,:))';
- SAcc = SAcc./(max(SAcc')'*ones(1,npT));
- save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAcc','cc','ir_cc','ic_cc','-append')
- save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'ac','ir_ac','ic_ac','-append')
- else
- load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAcc','cc','ir_cc','ic_cc')
- load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'ac','ir_ac','ic_ac')
- end
-
- figure,
-% boxplot(SAcc,'whis',10,'symbol','r.')
- myboxplot(SAcc,[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 1])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('EET All moments')
- saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_moments'])
- eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_moments']);
- eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_moments']);
-% close(gcf),
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% MORRIS FOR DERIVATIVES
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-% if opt_gsa.load_ident_files==0,
-% for j=1:npT,
-% SAMorris = [];
-% ddd=NaN(size(lpmat,1),size(JJ,1));
-% ddd(istable,:) = squeeze(JJ(:,j,:))';
-% for i=1:size(ddd,2),
-% [SAmeas, SAMorris(:,:,i)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], [ddd(:,i)],nliv);
-% end
-% SAddd(:,:,j) = squeeze(SAMorris(:,1,:))';
-% SAddd(:,:,j) = SAddd(:,:,j)./(max(SAddd(:,:,j)')'*ones(1,npT));
-% sad(:,j) = median(SAddd(find(~isnan(squeeze(SAddd(:,1,j)))),:,j))';
-% end
-% save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAddd','sad','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAddd','sad')
-% end
-% figure,
-% contourf(sad,10), colorbar
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
-% set(gca,'yticklabel',' ','fontsize',10,'ytick',[1:npT])
-% for ip=1:npT,
-% text(ip,0.9,['D(',bayestopt_.name{ip},')'],'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% text(0.9,ip,[bayestopt_.name{ip}],'rotation',0,'HorizontalAlignment','right','interpreter','none')
-% end
-% [m,im]=max(sad);
-% iii = find((im-[1:npT])==0);
-% disp('Most identified params')
-% disp(bayestopt_.name(iii))
-
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% END OF MORRIS FOR DERIVATIVES
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['EET cross-correlations']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_cc==j);
-% iv = [iv; find(ic_cc==j)];
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAcc(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAcc(iv,:),[],'.',[],3)
-% else
-% plot(SAcc(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_cc_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_cc_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_cc_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
-
-% if opt_gsa.load_ident_files==0,
-% SAMorris = [];
-% for i=1:size(ac,2),
-% [SAmeas, SAMorris(:,:,i)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], ac(:,i),nliv);
-% end
-% %end
-% SAac = squeeze(SAMorris(:,1,:))';
-% save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAac','ac','ir_ac','ic_ac','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAac','ac','ir_ac','ic_ac')
-% end
-% figure,
-% % boxplot(SAac,'whis',10,'symbol','r.')
-% myboxplot(SAac,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title('EET All auto-correlations')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_ac'])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_ac']);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_ac']);
-% close(gcf),
-
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['EET auto-correlations']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_ac==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAac(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAac(iv,:),[],'.',[],3)
-% else
-% plot(SAac(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_ac_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_ac_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_ac_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
-% if opt_gsa.load_ident_files==0,
-% js=0;
-% %for j=1:size(tadj,1),
-% SAMorris = [];
-% for i=1:size(tadj,2),
-% js=js+1;
-% [SAmeas, SAMorris(:,:,js)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], tadj(:,i),nliv);
-% end
-% %end
-% SAM = squeeze(SAMorris(nshock+1:end,1,:));
-% for j=1:js,
-% SAtadj(:,j)=SAM(:,j)./(max(SAM(:,j))+eps);
-% end
-% SAtadj = SAtadj';
-% save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAtadj','tadj','ir_tadj','ic_tadj','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAtadj','tadj','ir_tadj','ic_tadj')
-% end
-% if opt_gsa.load_ident_files==0,
-% js=0;
-% SAMorris = [];
-% for i=1:size(iff,2),
-% js=js+1;
-% [SAmeas, SAMorriss(:,:,js)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], iff(:,i),nliv);
-% end
-% SAM = squeeze(SAMorriss(nshock+1:end,1,:));
-% for j=1:js,
-% SAIF(:,j)=SAM(:,j)./(max(SAM(:,j))+eps);
-% end
-% SAIF = SAIF';
-% save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAIF','iff','ir_if','ic_if','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAIF','iff','ir_if','ic_if')
-% end
-% figure,
-% %bar(SAtadj),
-% % boxplot(SAtadj,'whis',10,'symbol','r.')
-% myboxplot(SAtadj,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% set(gca,'ylim',[0 1])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title('All half-life')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_tadj'])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_tadj']);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_tadj']);
-% close(gcf),
-
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['EET speed of adjustment observed variables']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_tadj==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAtadj(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAtadj(iv,:),[],'.',[],3)
-% else
-% plot(SAtadj(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_tadj_varobs_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_tadj_varobs_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_tadj_varobs_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
-% ifig = 0;
-% for j=1:M_.exo_nbr,
-% if mod(j,6)==1
-% figure('name',['EET speed of adjustment shocks']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ic_tadj==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAtadj(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAtadj(iv,:),[],'.',[],3)
-% else
-% plot(SAtadj(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(M_.exo_names(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==M_.exo_nbr,
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_tadj_exo_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_tadj_exo_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_tadj_exo_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
-% figure,
-% %bar(SAIF),
-% % boxplot(SAIF,'whis',10,'symbol','r.')
-% myboxplot(SAIF,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% set(gca,'ylim',[0 1])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% ylabel('Elementary Effects')
-% title('Steady state gains (impact factors)')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_gain'])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_gain']);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_gain']);
-% close(gcf),
- %figure, bar(SAIF'), title('All Gain Relationships')
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['EET steady state gain observed series']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_if==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAIF(iv,:),'whis',10,'symbol','r.');
-% myboxplot(SAIF(iv,:),[],'.',[],10)
-% else
-% plot(SAIF(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_gain_varobs_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_gain_varobs_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_gain_varobs_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-%
-% ifig = 0;
-% for j=1:M_.exo_nbr,
-% if mod(j,6)==1
-% figure('name',['EET steady state gain shocks']);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ic_if==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAIF(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAIF(iv,:),[],'.',[],3)
-% else
-% plot(SAIF(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(M_.exo_names(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==M_.exo_nbr,
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_gain_exo_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_gain_exo_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_gain_exo_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
-
- if opt_gsa.load_ident_files==0,
- SAMorris = [];
- for j=1:j0,
- [SAmeas, SAMorris(:,:,j)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], yt(:,j),nliv);
- end
-
-% SAM = squeeze(SAMorris(nshock+1:end,1,:));
- SAM = squeeze(SAMorris(1:end,1,:));
- for j=1:j0
- SAnorm(:,j)=SAM(:,j)./max(SAM(:,j));
- irex(j)=length(find(SAnorm(:,j)>0.01));
- end
- [dum, irel]=sort(irex);
-
-% SAMmu = squeeze(SAMorris(nshock+1:end,2,:));
- SAMmu = squeeze(SAMorris(1:end,2,:));
- for j=1:j0
- SAmunorm(:,j)=SAMmu(:,j)./max(SAM(:,j)); % normalised w.r.t. mu*
- end
-% SAMsig = squeeze(SAMorris(nshock+1:end,3,:));
- SAMsig = squeeze(SAMorris(1:end,3,:));
- for j=1:j0
- SAsignorm(:,j)=SAMsig(:,j)./max(SAMsig(:,j));
- end
- save([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAnorm','SAmunorm','SAsignorm','-append')
- else
- load([OutputDirectoryName,'/',fname_,'_morris_IDE'],'SAnorm','SAmunorm','SAsignorm')
- end
- figure, %bar(SAnorm(:,irel))
-% boxplot(SAnorm','whis',10,'symbol','r.')
- myboxplot(SAnorm',[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- set(gca,'ylim',[0 1])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- xlabel(' ')
- for ip=1:npT,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('Elementary effects in the model')
- saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_par'])
- eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_par']);
- eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_par']);
-
- figure, %bar(SAmunorm(:,irel))
-% boxplot(SAmunorm','whis',10,'symbol','r.')
- myboxplot(SAmunorm',[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- set(gca,'ylim',[-1 1])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- xlabel(' ')
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('\mu in the model')
- saveas(gcf,[OutputDirectoryName,'/',fname_,'_morrismu_par'])
- eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morrismu_par']);
- eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morrismu_par']);
- close(gcf),
-
- figure, %bar(SAsignorm(:,irel))
-% boxplot(SAsignorm','whis',10,'symbol','r.')
- myboxplot(SAsignorm',[],'.',[],10)
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- set(gca,'ylim',[0 1])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- xlabel(' ')
- for ip=1:npT,
- text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title('\sigma in the model')
- saveas(gcf,[OutputDirectoryName,'/',fname_,'_morrissig_par'])
- eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morrissig_par']);
- eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morrissig_par']);
- close(gcf),
-
- % figure, bar(SAnorm(:,irel)')
- % set(gca,'xtick',[1:j0])
- % set(gca,'xlim',[0.5 j0+0.5])
- % title('Elementary effects relationships')
- % saveas(gcf,[OutputDirectoryName,'/',fname_,'_morris_redform'])
- % eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_redform']);
- % eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_redform']);
-
-elseif opt_gsa.morris==3,
- np=estim_params_.np;
- na=(4*np+1)*opt_gsa.Nsam;
- for j=1:j0,
- [idex(j,:), yd(j,:)] = spop_ide(lpmat, yt(:,j), opt_gsa.Nsam, 5-1);
- end
- iok=find(~isnan(yt(1:opt_gsa.Nsam,1)));
- yr=NaN*ones(size(lpmat,1),j0);
- for j=1:j0,
- ys(j,:)=yd(j,:)./max(yd(j,:));
- [dum, is]=sort(yt(iok,j));
- yr(iok(is),j)=[1:length(iok)]'./length(iok);
- yr(istable(length(iok)+1:end),j) = interp1(yt(iok,j),yr(iok,j),yt(istable(length(iok)+1:end),j),'','extrap');
- ineg=find(yr(:,j)<0);
- if any(ineg),
- [dum, is]=sort(yr(ineg,j));
- yr(ineg(is),j)=-[length(ineg):-1:1]./length(iok);
-
- end
- [idex_r(j,:), yd_r(j,:)] = spop_ide(lpmat, yr(:,j), opt_gsa.Nsam, 5-1);
- ys_r(j,:)=yd_r(j,:)./max(yd_r(j,:));
-
- end,
- figure, bar((idex.*ys)./opt_gsa.Nsam), title('Relationships')
- figure, bar((idex.*ys)'./opt_gsa.Nsam), title('Parameters')
- figure, bar((idex_r.*ys_r)./opt_gsa.Nsam), title('Relationships rank')
- figure, bar((idex_r.*ys_r)'./opt_gsa.Nsam), title('Parameters rank')
- [v0,d0]=eig(corrcoef(yt(iok,:)));
- ee=diag(d0);
- ee=ee([end:-1:1])./j0;
- i0=length(find(ee>0.01));
- v0=v0(:,[end:-1:1]);
- for j=1:i0,
- [idex_pc(j,:), yd_pc(j,:)] = spop_ide(lpmat, yt*v0(:,j), opt_gsa.Nsam, 5-1);
- end
- for j=1:i0,
- ys_pc(j,:)=yd_pc(j,:)./max(yd_pc(j,:));
- end,
- figure, bar((idex_pc.*ys_pc)./opt_gsa.Nsam), title('Relationships PCA')
- figure, bar((idex_pc.*ys_pc)'./opt_gsa.Nsam), title('Parameters PCA')
-
- [vr,dr]=eig(corrcoef(yr(iok,:)));
- er=diag(dr);
- er=er([end:-1:1])./j0;
- ir0=length(find(er>0.01));
- vr=vr(:,[end:-1:1]);
- for j=1:ir0,
- [idex_pcr(j,:), yd_pcr(j,:)] = spop_ide(lpmat, yr*vr(:,j), opt_gsa.Nsam, 5-1);
- end
- for j=1:ir0,
- ys_pcr(j,:)=yd_pcr(j,:)./max(yd_pcr(j,:));
- end,
- figure, bar((idex_pcr.*ys_pcr)./opt_gsa.Nsam), title('Relationships rank PCA')
- figure, bar((idex_pcr.*ys_pcr)'./opt_gsa.Nsam), title('Parameters rank PCA')
-
-elseif opt_gsa.morris==2, % ISKREV staff
- return,
-
-
-else, % main effects analysis
-
- if itrans==0,
- fsuffix = '';
- elseif itrans==1,
- fsuffix = '_log';
- else
- fsuffix = '_rank';
- end
-
- imap=[1:npT];
-
- x0=[lpmat0(istable,:), lpmat(istable,:)];
- nrun=length(istable);
- nest=min(250,nrun);
- nfit=min(1000,nrun);
-
-% opt_gsa.load_ident_files=0;
-
-% if opt_gsa.load_ident_files==0,
-% try
-% EET=load([OutputDirectoryName,'/SCREEN/',fname_,'_morris_IDE'],'SAvdec','vdec','ir_vdec','ic_vdec');
-% catch
-% EET=[];
-% end
-% SAvdec=zeros(size(vdec,2),npT);
-%
-% for j=1:size(vdec,2),
-% if itrans==0,
-% y0 = vdec(istable,j);
-% elseif itrans==1,
-% y0 = log_trans_(vdec(istable,j));
-% else
-% y0 = trank(vdec(istable,j));
-% end
-% if ~isempty(EET),
-% % imap=find(EET.SAvdec(j,:));
-% % [dum, isort]=sort(-EET.SAvdec(j,:));
-% imap=find(EET.SAvdec(j,:) >= (0.1.*max(EET.SAvdec(j,:))) );
-% end
-% gsa_(j) = gsa_sdp(y0(1:nest), x0(1:nest,imap), ...
-% 2, [],[],[],0,[OutputDirectoryName,'/map_vdec',fsuffix,int2str(j)], pnames);
-% if nfit>nest,
-% gsa_(j) = gsa_sdp(y0(1:nfit), x0(1:nfit,imap), ...
-% -2, gsa_(j).nvr*nest^3/nfit^3,[],[],0,[OutputDirectoryName,'/map_vdec',fsuffix,int2str(j)], pnames);
-% end
-%
-% SAvdec(j,imap)=gsa_(j).si;
-% imap_vdec{j}=imap;
-% end
-% save([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_vdec','SAvdec','vdec','ir_vdec','ic_vdec','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_vdec','SAvdec','vdec','ir_vdec','ic_vdec')
-% end
-% figure,
-% % boxplot(SAvdec,'whis',10,'symbol','r.')
-% myboxplot(SAvdec,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Main effects variance decomposition ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_vdec',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_vdec',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_vdec',fsuffix]);
-% close(gcf),
-%
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['Main effects observed variance decomposition ',fsuffix]);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_vdec==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAvdec(iv,:),'whis',10,'symbol','r.');
-% myboxplot(SAvdec(iv,:),[],'.',[],10)
-% else
-% plot(SAvdec(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_vdec',fsuffix,'_varobs_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_vdec',fsuffix,'_varobs_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_vdec',fsuffix,'_varobs_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-%
-% ifig = 0;
-% for j=1:M_.exo_nbr,
-% if mod(j,6)==1
-% figure('name',['Main effects shocks variance decomposition ',fsuffix]);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ic_vdec==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAvdec(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAvdec(iv,:),[],'.',[],10)
-% else
-% plot(SAvdec(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',3,'xtick',[1:np])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% set(gca,'fontsize',10)
-% end
-% title(M_.exo_names(j,:),'interpreter','none','fontsize',10)
-% if mod(j,6)==0 | j==M_.exo_nbr
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_vdec',fsuffix,'_exo_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_vdec',fsuffix,'_exo_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_vdec',fsuffix,'_exo_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
- if opt_gsa.load_ident_files==0,
- try
- EET=load([OutputDirectoryName,'/SCREEN/',fname_,'_morris_IDE'],'SAcc','ir_cc','ic_cc');
- catch
- EET=[];
- end
- ccac = stand_([mss cc ac]);
- [pcc, dd] = eig(cov(ccac(istable,:)));
- [latent, isort] = sort(-diag(dd));
- latent = -latent;
- figure, bar(latent)
- title('Eigenvalues in PCA')
- pcc=pcc(:,isort);
- ccac = ccac*pcc;
-% npca = min(40, max(find(cumsum(latent)./length(latent)<0.99))+1);
- npca = max(find(cumsum(latent)./length(latent)<0.99))+1;
- siPCA = (EET.SAcc'*abs(pcc'))';
-% siPCA = siPCA./(max(siPCA')'*ones(1,npT)).*(latent*ones(1,npT));
- siPCA = siPCA./(max(siPCA')'*ones(1,npT));
-% siPCA = sum(siPCA,1);
-% siPCA = siPCA./max(siPCA);
- SAcc=zeros(size(ccac,2),npT);
- for j=1:npca, %size(ccac,2),
- if itrans==0,
- y0 = ccac(istable,j);
- elseif itrans==1,
- y0 = log_trans_(ccac(istable,j));
- else
- y0 = trank(ccac(istable,j));
- end
- if ~isempty(EET),
-% imap=find(EET.SAvdec(j,:));
-% [dum, isort]=sort(-EET.SAvdec(j,:));
- imap=find(siPCA(j,:) >= (0.1.*max(siPCA(j,:))) );
-% imap=find(EET.SAcc(j,:) >= (0.1.*max(EET.SAcc(j,:))) );
- end
- gsa_(j) = gsa_sdp(y0(1:nest), x0(1:nest,imap), ...
- 2, [],[],[],0,[OutputDirectoryName,'/map_cc',fsuffix,int2str(j)], pnames);
-% if nfit>nest,
-% gsa_(j) = gsa_sdp(y0(1:nfit), x0(1:nfit,imap), ...
-% -2, gsa_(j).nvr*nest^3/nfit^3,[],[],0,[OutputDirectoryName,'/map_cc',fsuffix,int2str(j)], pnames);
-% end
- SAcc(j,imap)=gsa_(j).si;
- imap_cc{j}=imap;
-
- end
- save([OutputDirectoryName,'/map_cc',fsuffix],'gsa_')
- save([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_cc','SAcc','ccac','-append')
- else
- load([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_cc','SAcc','ccac')
-
- end
-% figure,
-% % boxplot(SAcc,'whis',10,'symbol','r.')
-% myboxplot(SAcc,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% ylabel(' ')
-% title(['Main effects moments''s PCA ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_cc',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_moments',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_moments',fsuffix]);
-% close(gcf),
-
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['Main effects cross-covariances ',fsuffix]);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_cc==j);
-% iv = [iv; find(ic_cc==j)];
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAcc(iv,:),'whis',10,'symbol','r.');
-% myboxplot(SAcc(iv,:),[],'.',[],10)
-% else
-% plot(SAcc(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% set(gca,'fontsize',10)
-% end
-% title(options_.varobs(j,:),'interpreter','none','fontsize',10)
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_cc',fsuffix,'_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_cc',fsuffix,'_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_cc',fsuffix,'_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-%
-% if opt_gsa.load_ident_files==0,
-% try
-% EET=load([OutputDirectoryName,'/SCREEN/',fname_,'_morris_IDE'],'SAac','ir_ac','ic_ac');
-% catch
-% EET=[];
-% end
-% SAac=zeros(size(ac,2),npT);
-% for j=1:size(ac,2),
-% if itrans==0,
-% y0 = ac(istable,j);
-% elseif itrans==1,
-% y0 = log_trans_(ac(istable,j));
-% else
-% y0 = trank(ac(istable,j));
-% end
-% if ~isempty(EET),
-% imap=find(EET.SAac(j,:) >= (0.1.*max(EET.SAac(j,:))) );
-% end
-% % gsa_(j) = gsa_sdp_dyn( y0, lpmat(istable,:), ...
-% % gsa_flag, [],[],[],0,[OutputDirectoryName,'/map_ac',fsuffix,int2str(j)], pnames);
-% gsa_(j) = gsa_sdp(y0(1:nest), x0(1:nest,imap), ...
-% 2, [],[],[],0,[OutputDirectoryName,'/map_ac',fsuffix,int2str(j)], pnames);
-% if nfit>nest,
-% gsa_(j) = gsa_sdp(y0(1:nfit), x0(1:nfit,imap), ...
-% -2, gsa_(j).nvr*nest^3/nfit^3,[],[],0,[OutputDirectoryName,'/map_ac',fsuffix,int2str(j)], pnames);
-% end
-% SAac(j,imap)=gsa_(j).si;
-% imap_ac{j}=imap;
-%
-% end
-% save([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_ac','SAac','ac','ir_ac','ic_ac','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_ac','SAac','ac','ir_ac','ic_ac')
-% end
-%
-% figure,
-% % boxplot(SAac,'whis',10,'symbol','r.')
-% myboxplot(SAac,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Main effects 1 lag auto-covariances ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_ac',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_ac',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_ac',fsuffix]);
-% close(gcf),
-%
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['Main effects auto-covariances ',fsuffix]);
-% ifig=ifig+1;
-% iplo = 0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_ac==j);
-% %iv = [iv; find(ic_ac==j)];
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAac(iv,:),'whis',10,'symbol','r.');
-% myboxplot(SAac(iv,:),[],'.',[],10)
-% else
-% plot(SAac(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:npT,
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% set(gca,'fontsize',10)
-% end
-% title(options_.varobs(j,:),'interpreter','none','fontsize',10)
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_ac',fsuffix,'_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_ac',fsuffix,'_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_ac',fsuffix,'_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-
-% x0=x0(:,nshock+1:end);
- imap=[1:npT];
-
-% if opt_gsa.load_ident_files==0,
-% try
-% EET=load([OutputDirectoryName,'/SCREEN/',fname_,'_morris_IDE'],'SAtadj','ir_tadj','ic_tadj');
-% ny=size(EET.SAtadj,1);
-% catch
-% EET=[];
-% end
-% SAtadj=zeros(size(tadj,2),np);
-% for j=1:size(tadj,2),
-% if itrans==0,
-% y0 = tadj(istable,j);
-% elseif itrans==1,
-% y0 = log_trans_(tadj(istable,j));
-% else
-% y0 = trank(tadj(istable,j));
-% end
-% if ~isempty(EET),
-% if size(tadj,2)~=ny,
-% jj=find(EET.ir_tadj==ir_tadj(j));
-% jj=jj(find(EET.ic_tadj(jj)==ic_tadj(j)));
-% if ~isempty(jj),
-% imap=find(EET.SAtadj(jj,:) >= (0.1.*max(EET.SAtadj(jj,:))) );
-% else
-% imap=[1:np];
-% end
-% else
-% imap=find(EET.SAtadj(j,:) >= (0.1.*max(EET.SAtadj(j,:))) );
-% end
-% end
-% % gsa_(j) = gsa_sdp_dyn( y0, lpmat(istable,:), ...
-% % gsa_flag, [],[],[],0,[OutputDirectoryName,'/map_tadj',fsuffix,int2str(j)], pnames);
-% gsa_(j) = gsa_sdp(y0(1:nest), x0(1:nest,imap), ...
-% 2, [],[],[],0,[OutputDirectoryName,'/map_tadj',fsuffix,int2str(j)], pnames);
-% if nfit>nest,
-% gsa_(j) = gsa_sdp(y0(1:nfit), x0(1:nfit,imap), ...
-% -2, gsa_(j).nvr*nest^3/nfit^3,[],[],0,[OutputDirectoryName,'/map_tadj',fsuffix,int2str(j)], pnames);
-% end
-% SAtadj(j,imap)=gsa_(j).si;
-% imap_tadj{j}=imap;
-%
-% end
-% save([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_tadj','SAtadj','tadj','ir_tadj','ic_tadj','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_tadj','SAtadj','tadj','ir_tadj','ic_tadj')
-% end
-%
-% figure,
-% % boxplot(SAtadj,'whis',10,'symbol','r.')
-% myboxplot(SAtadj,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Main effects speed of adjustment ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_tadj',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_tadj',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_tadj',fsuffix]);
-% close(gcf),
-%
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['Main effects observed speed adjustment ',fsuffix]);
-% ifig=ifig+1;
-% iplo = 0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_tadj==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAtadj(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAtadj(iv,:),[],'.',[],10)
-% else
-% plot(SAtadj(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_tadj',fsuffix,'_varobs_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_tadj',fsuffix,'_varobs_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_tadj',fsuffix,'_varobs_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-%
-% ifig = 0;
-% for j=1:M_.exo_nbr,
-% if mod(j,6)==1
-% figure('name',['Main effects shocks speed of adjustment ',fsuffix]);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ic_tadj==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAtadj(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAtadj(iv,:),[],'.',[],10)
-% else
-% plot(SAtadj(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(M_.exo_names(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==M_.exo_nbr,
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_tadj',fsuffix,'_exo_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_tadj',fsuffix,'_exo_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_tadj',fsuffix,'_exo_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-%
-%
-% if opt_gsa.load_ident_files==0,
-% try
-% EET=load([OutputDirectoryName,'/SCREEN/',fname_,'_morris_IDE'],'SAIF','ir_if','ic_if');
-% catch
-% EET=[];
-% end
-% SAif=zeros(size(iff,2),np);
-% for j=1:size(iff,2),
-% if itrans==0,
-% y0 = iff(istable,j);
-% elseif itrans==1,
-% y0 = log_trans_(iff(istable,j));
-% else
-% y0 = trank(iff(istable,j));
-% end
-% if ~isempty(EET),
-% imap=find(EET.SAIF(j,:) >= (0.1.*max(EET.SAIF(j,:))) );
-% end
-% % gsa_(j) = gsa_sdp_dyn( y0, lpmat(istable,:), ...
-% % gsa_flag, [],[],[],0,[OutputDirectoryName,'/map_if',fsuffix,int2str(j)], pnames);
-% gsa_(j) = gsa_sdp(y0(1:nest), x0(1:nest,imap), ...
-% 2, [],[],[],0,[OutputDirectoryName,'/map_if',fsuffix,int2str(j)], pnames);
-% if nfit>nest,
-% gsa_(j) = gsa_sdp(y0(1:nfit), x0(1:nfit,imap), ...
-% -2, gsa_(j).nvr*nest^3/nfit^3,[],[],0,[OutputDirectoryName,'/map_if',fsuffix,int2str(j)], pnames);
-% end
-% SAif(j,imap)=gsa_(j).si;
-% imap_if{j}=imap;
-%
-% end
-% save([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_if','SAif','iff','ir_if','ic_if','-append')
-% else
-% load([OutputDirectoryName,'/',fname_,'_main_eff'],'imap_if','SAif','iff','ir_if','ic_if')
-% end
-%
-% figure,
-% % boxplot(SAif,'whis',10,'symbol','r.')
-% myboxplot(SAif,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Main effects impact factors ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_if',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_if',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_if',fsuffix]);
-% close(gcf),
-%
-% ifig = 0;
-% for j=1:size(options_.varobs,1)
-% if mod(j,6)==1
-% figure('name',['Main effects observed impact factors ',fsuffix]);
-% ifig=ifig+1;
-% iplo = 0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ir_if==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAif(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAif(iv,:),[],'.',[],10)
-% else
-% plot(SAif(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(options_.varobs(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==size(options_.varobs,1)
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_if',fsuffix,'_varobs_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_if',fsuffix,'_varobs_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_if',fsuffix,'_varobs_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-%
-% ifig = 0;
-% for j=1:M_.exo_nbr,
-% if mod(j,6)==1
-% figure('name',['Main effects shocks impact factors ',fsuffix]);
-% ifig=ifig+1;
-% iplo=0;
-% end
-% iplo=iplo+1;
-% subplot(3,2,iplo)
-% iv = find(ic_if==j);
-% if ~isempty(iv)
-% if length(iv)>1
-% % boxplot(SAif(iv,:),'whis',3,'symbol','r.');
-% myboxplot(SAif(iv,:),[],'.',[],10)
-% else
-% plot(SAif(iv,:),'r.');
-% end
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% end
-% title(M_.exo_names(j,:),'interpreter','none')
-% if mod(j,6)==0 | j==M_.exo_nbr
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_if',fsuffix,'_exo_',int2str(ifig)])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_if',fsuffix,'_exo_',int2str(ifig)]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_if',fsuffix,'_exo_',int2str(ifig)]);
-% close(gcf),
-% end
-% end
-% SAmom = [SAvdec' SAcc' SAac']';
-% SAdyn = [SAtadj' SAif']';
-% SAall = [SAmom(:,nshock+1:end)' SAdyn']';
-%
-% figure,
-% % boxplot(SAtadj,'whis',10,'symbol','r.')
-% myboxplot(SAmom,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
-% set(gca,'xlim',[0.5 npT+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:npT,
-% % text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Main effects theoretical moments ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_moments',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_moments',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_moments',fsuffix]);
-% % close(gcf),
-%
-% figure,
-% % boxplot(SAtadj,'whis',10,'symbol','r.')
-% myboxplot(SAdyn,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Main effects short-long term dynamics ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_dynamics',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_dynamics',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_dynamics',fsuffix]);
-% % close(gcf),
-%
-% figure,
-% % boxplot(SAtadj,'whis',10,'symbol','r.')
-% myboxplot(SAall,[],'.',[],10)
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-% set(gca,'xlim',[0.5 np+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:np,
-% text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% % text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Main effects all ',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_map_ALL',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_map_ALL',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_map_ALL',fsuffix]);
-% % close(gcf),
-
-% for j=1:size(SAall,1),
-% SAallN(j,:)=SAall(j,:)./max(SAall(j,:));
-% end
-% SAmean=mean(SAallN);
-% for j=1:size(SAmom,1),
-% SAmomN(j,:)=SAmom(j,1:nshock)./max(SAmom(j,1:nshock));
-% end
-% SAmomN(find(isnan(SAmomN)))=0;
-% SAmeanexo=mean(SAmomN(:,1:nshock));
-
-% figure, bar(latent'*SAcc),
- figure, bar(sum(SAcc)),
- set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:npT])
- set(gca,'xlim',[0.5 npT+0.5])
- ydum = get(gca,'ylim');
- set(gca,'ylim',[0 ydum(2)])
- set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:npT,
- text(ip,-0.02*(ydum(2)),bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- % text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- xlabel(' ')
- title(['Identifiability indices in the ',fsuffix,' moments.'],'interpreter','none')
- saveas(gcf,[OutputDirectoryName,'/',fname_,'_ident_ALL',fsuffix])
- eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_ident_ALL',fsuffix]);
- eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_ident_ALL',fsuffix]);
-
-% figure, bar(SAmeanexo),
-% set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:nshock])
-% set(gca,'xlim',[0.5 nshock+0.5])
-% ydum = get(gca,'ylim');
-% set(gca,'ylim',[0 ydum(2)])
-% set(gca,'position',[0.13 0.2 0.775 0.7])
-% for ip=1:nshock,
-% % text(ip,-0.02*(ydum(2)),deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% text(ip,-0.02*(ydum(2)),bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
-% end
-% xlabel(' ')
-% title(['Identifiability indices for shocks',fsuffix],'interpreter','none')
-% saveas(gcf,[OutputDirectoryName,'/',fname_,'_ident_SHOCKS',fsuffix])
-% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_ident_SHOCKS',fsuffix]);
-% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_ident_SHOCKS',fsuffix]);
-end
-
-return
diff --git a/GSA_distrib/4.2/mc_moments.m b/GSA_distrib/4.2/mc_moments.m
deleted file mode 100644
index 0f38ff6a66ed59781ecfe2ed45cef930103abf7f..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/mc_moments.m
+++ /dev/null
@@ -1,25 +0,0 @@
-function [vdec, cc, ac] = mc_moments(mm, ss, dr)
-global options_ M_
-
- [nr1, nc1, nsam] = size(mm);
- disp('Computing theoretical moments ...')
- h = waitbar(0,'Theoretical moments ...');
-
- for j=1:nsam,
- dr.ghx = mm(:, [1:(nc1-M_.exo_nbr)],j);
- dr.ghu = mm(:, [(nc1-M_.exo_nbr+1):end], j);
- if ~isempty(ss),
- set_shocks_param(ss(j,:));
- end
- [vdec(:,:,j), corr, autocorr, z, zz] = th_moments(dr,options_.varobs);
- cc(:,:,j)=triu(corr);
- dum=[];
- for i=1:options_.ar
- dum=[dum, autocorr{i}];
- end
- ac(:,:,j)=dum;
- waitbar(j/nsam,h)
- end
- close(h)
- disp(' ')
- disp('... done !')
diff --git a/GSA_distrib/4.2/myboxplot.m b/GSA_distrib/4.2/myboxplot.m
deleted file mode 100644
index 096d1a854a7cf11e29ad0124d1daa226122c186b..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/myboxplot.m
+++ /dev/null
@@ -1,158 +0,0 @@
-
-function sout = myboxplot (data,notched,symbol,vertical,maxwhisker)
-
-% sout = myboxplot (data,notched,symbol,vertical,maxwhisker)
-
-% % % % endif
-if nargin < 5 | isempty(maxwhisker), maxwhisker = 1.5; end
-if nargin < 4 | isempty(vertical), vertical = 1; end
-if nargin < 3 | isempty(symbol), symbol = ['+','o']; end
-if nargin < 2 | isempty(notched), notched = 0; end
-
-if length(symbol)==1, symbol(2)=symbol(1); end
-
-if notched==1, notched=0.25; end
-a=1-notched;
-
-% ## figure out how many data sets we have
-if iscell(data),
- nc = length(data);
-else
-% if isvector(data), data = data(:); end
- nc = size(data,2);
-end
-
-% ## compute statistics
-% ## s will contain
-% ## 1,5 min and max
-% ## 2,3,4 1st, 2nd and 3rd quartile
-% ## 6,7 lower and upper confidence intervals for median
-s = zeros(7,nc);
-box = zeros(1,nc);
-whisker_x = ones(2,1)*[1:nc,1:nc];
-whisker_y = zeros(2,2*nc);
-outliers_x = [];
-outliers_y = [];
-outliers2_x = [];
-outliers2_y = [];
-
-for i=1:nc
- % ## Get the next data set from the array or cell array
- if iscell(data)
- col = data{i}(:);
- else
- col = data(:,i);
- end
-% ## Skip missing data
-% % % % % % % col(isnan(col) | isna (col)) = [];
- col(isnan(col)) = [];
-
- % ## Remember the data length
- nd = length(col);
- box(i) = nd;
- if (nd > 1)
-% ## min,max and quartiles
-% s(1:5,i) = statistics(col)(1:5);
-s(1,i)=min(col);
-s(5,i)=max(col);
-s(2,i)=myprctilecol(col,25);
-s(3,i)=myprctilecol(col,50);
-s(4,i)=myprctilecol(col,75);
-
-
-
-
-
-
-
-
-% ## confidence interval for the median
- est = 1.57*(s(4,i)-s(2,i))/sqrt(nd);
- s(6,i) = max([s(3,i)-est, s(2,i)]);
- s(7,i) = min([s(3,i)+est, s(4,i)]);
-% ## whiskers out to the last point within the desired inter-quartile range
- IQR = maxwhisker*(s(4,i)-s(2,i));
- whisker_y(:,i) = [min(col(col >= s(2,i)-IQR)); s(2,i)];
- whisker_y(:,nc+i) = [max(col(col <= s(4,i)+IQR)); s(4,i)];
-% ## outliers beyond 1 and 2 inter-quartile ranges
- outliers = col((col < s(2,i)-IQR & col >= s(2,i)-2*IQR) | (col > s(4,i)+IQR & col <= s(4,i)+2*IQR));
- outliers2 = col(col < s(2,i)-2*IQR | col > s(4,i)+2*IQR);
- outliers_x = [outliers_x; i*ones(size(outliers))];
- outliers_y = [outliers_y; outliers];
- outliers2_x = [outliers2_x; i*ones(size(outliers2))];
- outliers2_y = [outliers2_y; outliers2];
- elseif (nd == 1)
-% ## all statistics collapse to the value of the point
- s(:,i) = col;
-% ## single point data sets are plotted as outliers.
- outliers_x = [outliers_x; i];
- outliers_y = [outliers_y; col];
- else
-% ## no statistics if no points
- s(:,i) = NaN;
- end
-end
-% % % % if isempty(outliers2_y)
-% % % % outliers2_y=
-% ## Note which boxes don't have enough stats
-chop = find(box <= 1);
-
-% ## Draw a box around the quartiles, with width proportional to the number of
-% ## items in the box. Draw notches if desired.
-box = box*0.23/max(box);
-quartile_x = ones(11,1)*[1:nc] + [-a;-1;-1;1;1;a;1;1;-1;-1;-a]*box;
-quartile_y = s([3,7,4,4,7,3,6,2,2,6,3],:);
-
-% ## Draw a line through the median
-median_x = ones(2,1)*[1:nc] + [-a;+a]*box;
-% median_x=median(col);
-median_y = s([3,3],:);
-
-% ## Chop all boxes which don't have enough stats
-quartile_x(:,chop) = [];
-quartile_y(:,chop) = [];
-whisker_x(:,[chop,chop+nc]) = [];
-whisker_y(:,[chop,chop+nc]) = [];
-median_x(:,chop) = [];
-median_y(:,chop) = [];
-% % % %
-% ## Add caps to the remaining whiskers
-cap_x = whisker_x;
-cap_x(1,:) =cap_x(1,:)- 0.05;
-cap_x(2,:) =cap_x(2,:)+ 0.05;
-cap_y = whisker_y([1,1],:);
-
-% #quartile_x,quartile_y
-% #whisker_x,whisker_y
-% #median_x,median_y
-% #cap_x,cap_y
-%
-% ## Do the plot
-
-mm=min(min(data));
-MM=max(max(data));
-
-if vertical
- plot (quartile_x, quartile_y, 'b', ...
- whisker_x, whisker_y, 'b--', ...
- cap_x, cap_y, 'k', ...
- median_x, median_y, 'r', ...
- outliers_x, outliers_y, [symbol(1),'r'], ...
- outliers2_x, outliers2_y, [symbol(2),'r']);
- set(gca,'XTick',1:nc);
- set(gca, 'XLim', [0.5, nc+0.5]);
- set(gca, 'YLim', [mm-(MM-mm)*0.05-eps, MM+(MM-mm)*0.05+eps]);
-
-else
-% % % % % plot (quartile_y, quartile_x, "b;;",
-% % % % % whisker_y, whisker_x, "b;;",
-% % % % % cap_y, cap_x, "b;;",
-% % % % % median_y, median_x, "r;;",
-% % % % % outliers_y, outliers_x, [symbol(1),"r;;"],
-% % % % % outliers2_y, outliers2_x, [symbol(2),"r;;"]);
-end
-
-if nargout,
- sout=s;
-end
-% % % endfunction
\ No newline at end of file
diff --git a/GSA_distrib/4.2/myprctilecol.m b/GSA_distrib/4.2/myprctilecol.m
deleted file mode 100644
index d99d5ad5009d0081ba192acfc1595b2e054f8536..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/myprctilecol.m
+++ /dev/null
@@ -1,20 +0,0 @@
-function y = myprctilecol(x,p);
-xx = sort(x);
-[m,n] = size(x);
-
-if m==1 | n==1
- m = max(m,n);
- if m == 1,
- y = x*ones(length(p),1);
- return;
- end
- n = 1;
- q = 100*(0.5:m - 0.5)./m;
- xx = [min(x); xx(:); max(x)];
-else
- q = 100*(0.5:m - 0.5)./m;
- xx = [min(x); xx; max(x)];
-end
-
-q = [0 q 100];
-y = interp1(q,xx,p);
\ No newline at end of file
diff --git a/GSA_distrib/4.2/norm_inv.m b/GSA_distrib/4.2/norm_inv.m
deleted file mode 100644
index e676be94edb12acb24a3719eb97af6b80e02d517..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/norm_inv.m
+++ /dev/null
@@ -1,49 +0,0 @@
-function invp = norm_inv(x, m, sd)
-% PURPOSE: computes the quantile (inverse of the CDF)
-% for each component of x with mean m, standard deviation sd
-%---------------------------------------------------
-% USAGE: invp = norm_inv(x,m,v)
-% where: x = variable vector (nx1)
-% m = mean vector (default=0)
-% sd = standard deviation vector (default=1)
-%---------------------------------------------------
-% RETURNS: invp (nx1) vector
-%---------------------------------------------------
-% SEE ALSO: norm_d, norm_rnd, norm_inv, norm_cdf
-%---------------------------------------------------
-
-% Written by KH (Kurt.Hornik@ci.tuwien.ac.at) on Oct 26, 1994
-% Copyright Dept of Probability Theory and Statistics TU Wien
-% Converted to MATLAB by JP LeSage, jpl@jpl.econ.utoledo.edu
-
- if nargin > 3
- error ('Wrong # of arguments to norm_inv');
- end
-
- [r, c] = size (x);
- s = r * c;
-
- if (nargin == 1)
- m = zeros(1,s);
- sd = ones(1,s);
- end
-
-
- if length(m)==1,
- m = repmat(m,1,s);
- end
- if length(sd)==1,
- sd = repmat(sd,1,s);
- end
- x = reshape(x,1,s);
- m = reshape(m,1,s);
- sd = reshape(sd,1,s);
-
- invp = zeros (1,s);
-
- invp = m + sd .* (sqrt(2) * erfinv(2 * x - 1));
-
-
-
- invp = reshape (invp, r, c);
-
diff --git a/GSA_distrib/4.2/optget.m b/GSA_distrib/4.2/optget.m
deleted file mode 100644
index b2893e2ceece29d6d08e7b9657ab54d2632502e8..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/optget.m
+++ /dev/null
@@ -1,39 +0,0 @@
-% OPTGET Utility to get previously set function default values
-% USAGE
-% optvalue=optget(funcname,optname,optvalue);
-% INPUTS
-% funcname : name of function
-% optname : name of option
-% optval : option value
-% OUTPUT
-% optval : the current value of the option
-%
-% If the named field is not already defined, it will be set to
-% optvalue, but optvalue has no effect if the field has already
-% been set. Use OPTSET to change a previously set field.
-%
-% optget(funcname) returns the current values of the options structure.
-
-% Copyright (c) 1997-2000, Paul L. Fackler & Mario J. Miranda
-% paul_fackler@ncsu.edu, miranda.4@osu.edu
-
-function optvalue = optget(funcname,optname,optvalue)
-
-funcname = lower(funcname);
-optvar=[funcname '_options'];
-eval(['global ' optvar]) % declare a global variable
-
-if nargin==1 % return the whole option structure
- optvalue=(eval(optvar));
- return
-end
-
-optname = lower(optname);
-% if structure is empty or the named field does not exist
-% set to the value passed
-if isempty(eval(optvar)) | ~isfield(eval(optvar),optname)
- eval([optvar '.' optname '=optvalue;']);
-% otherwise return the value in the field
-else
- optvalue = eval([optvar '.' optname]);
-end
diff --git a/GSA_distrib/4.2/prior_draw_gsa.m b/GSA_distrib/4.2/prior_draw_gsa.m
deleted file mode 100644
index 278e1e23775e008e7cc37cc7865efe6e441fb67c..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/prior_draw_gsa.m
+++ /dev/null
@@ -1,105 +0,0 @@
-function pdraw = prior_draw_gsa(init,rdraw)
-% Draws from the prior distributions
-% Adapted by M. Ratto from prior_draw (of DYNARE, copyright M. Juillard),
-% for use with Sensitivity Toolbox for DYNARE
-%
-%
-% INPUTS
-% o init [integer] scalar equal to 1 (first call) or 0.
-% o rdraw
-%
-% OUTPUTS
-% o pdraw [double] draw from the joint prior density.
-%
-% ALGORITHM
-% ...
-%
-% SPECIAL REQUIREMENTS
-% MATLAB Statistics Toolbox
-%
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-% global M_ options_ estim_params_ bayestopt_
-global bayestopt_
-persistent npar pshape p6 p7 p3 p4 lbcum ubcum
-
-if init
- pshape = bayestopt_.pshape;
- p6 = bayestopt_.p6;
- p7 = bayestopt_.p7;
- p3 = bayestopt_.p3;
- p4 = bayestopt_.p4;
- npar = length(p6);
- pdraw = zeros(npar,1);
- lbcum = zeros(npar,1);
- ubcum = ones(npar,1);
-
- % set bounds for cumulative probabilities
- for i = 1:npar
- switch pshape(i)
- case 5% Uniform prior.
- p4(i) = min(p4(i),bayestopt_.ub(i));
- p3(i) = max(p3(i),bayestopt_.lb(i));
- case 3% Gaussian prior.
- lbcum(i) = 0.5 * erfc(-(bayestopt_.lb(i)-p6(i))/p7(i) ./ sqrt(2));;
- ubcum(i) = 0.5 * erfc(-(bayestopt_.ub(i)-p6(i))/p7(i) ./ sqrt(2));;
- case 2% Gamma prior.
- lbcum(i) = gamm_cdf((bayestopt_.lb(i)-p3(i))/p7(i),p6(i));
- ubcum(i) = gamm_cdf((bayestopt_.ub(i)-p3(i))/p7(i),p6(i));
- case 1% Beta distribution (TODO: generalized beta distribution)
- lbcum(i) = betainc((bayestopt_.lb(i)-p3(i))./(p4(i)-p3(i)),p6(i),p7(i));
- ubcum(i) = betainc((bayestopt_.ub(i)-p3(i))./(p4(i)-p3(i)),p6(i),p7(i));
- case 4% INV-GAMMA1 distribution
- % TO BE CHECKED
- lbcum(i) = gamm_cdf((1/(bayestopt_.ub(i)-p3(i))^2)/(2/p6(i)),p7(i)/2);
- ubcum(i) = gamm_cdf((1/(bayestopt_.lb(i)-p3(i))^2)/(2/p6(i)),p7(i)/2);
- case 6% INV-GAMMA2 distribution
- % TO BE CHECKED
- lbcum(i) = gamm_cdf((1/(bayestopt_.ub(i)-p3(i)))/(2/p6(i)),p7(i)/2);
- ubcum(i) = gamm_cdf((1/(bayestopt_.lb(i)-p3(i)))/(2/p6(i)),p7(i)/2);
- otherwise
- % Nothing to do here.
- end
- end
- return
-end
-
-
-for i = 1:npar
- rdraw(:,i) = rdraw(:,i).*(ubcum(i)-lbcum(i))+lbcum(i);
- switch pshape(i)
- case 5% Uniform prior.
- pdraw(:,i) = rdraw(:,i)*(p4(i)-p3(i)) + p3(i);
- case 3% Gaussian prior.
- pdraw(:,i) = norm_inv(rdraw(:,i),p6(i),p7(i));
- case 2% Gamma prior.
- pdraw(:,i) = gamm_inv(rdraw(:,i),p6(i),p7(i))+p3(i);
- case 1% Beta distribution (TODO: generalized beta distribution)
- pdraw(:,i) = beta_inv(rdraw(:,i),p6(i),p7(i))*(p4(i)-p3(i))+p3(i);
- case 4% INV-GAMMA1 distribution
- % TO BE CHECKED
- pdraw(:,i) = sqrt(1./gamm_inv(rdraw(:,i),p7(i)/2,2/p6(i)))+p3(i);
- case 6% INV-GAMMA2 distribution
- % TO BE CHECKED
- pdraw(:,i) = 1./gamm_inv(rdraw(:,i),p7(i)/2,2/p6(i))+p3(i);
- otherwise
- % Nothing to do here.
- end
-end
-
-
diff --git a/GSA_distrib/4.2/priorcdf.m b/GSA_distrib/4.2/priorcdf.m
deleted file mode 100644
index 53d8ec34d39523151df6b3d9f9909d024f7de7a3..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/priorcdf.m
+++ /dev/null
@@ -1,50 +0,0 @@
-function [xcum] = priorcdf(para, pshape, p6, p7, p3, p4)
-% This procedure transforms x vectors into cumulative values
-% pshape: 0 is point mass, both para and p2 are ignored
-% 1 is BETA(mean,stdd)
-% 2 is GAMMA(mean,stdd)
-% 3 is NORMAL(mean,stdd)
-% 4 is INVGAMMA(s^2,nu)
-% 5 is UNIFORM [p1,p2]
-% Adapted by M. Ratto from MJ priordens.m
-
-nprio = length(pshape);
-
-i = 1;
-while i <= nprio;
- a = 0;
- b = 0;
- if pshape(i) == 1; % (generalized) BETA Prior
-% mu = (p1(i)-p3(i))/(p4(i)-p3(i));
-% stdd = p2(i)/(p4(i)-p3(i));
-% a = (1-mu)*mu^2/stdd^2 - mu;
-% b = a*(1/mu - 1);
- %lnprior = lnprior + lpdfgbeta(para(i),a,b,p3(i),p4(i)) ;
- para(:,i) = (para(:,i)-p3(i))./(p4(i)-p3(i));
-% xcum(:,i) = betacdf(para(:,i),a,b) ;
- xcum(:,i) = betainc(para(:,i),p6(i),p7(i));
- elseif pshape(i) == 2; % GAMMA PRIOR
-% b = p2(i)^2/(p1(i)-p3(i));
-% a = (p1(i)-p3(i))/b;
- %lnprior = lnprior + lpdfgam(para(i)-p3(i),a,b);
-% xcum(:,i) = gamcdf(para(:,i)-p3(i),a,b);
- xcum(:,i) = gamm_cdf((para(:,i)-p3(i))./p7(i),p6(i));
- elseif pshape(i) == 3; % GAUSSIAN PRIOR
- %lnprior = lnprior + lpdfnorm(para(i),p1(i),p2(i));
-% xcum(:,i) = normcdf(para(:,i),p1(i),p2(i));
- xcum(:,i) = 0.5 * erfc(-(para(:,i)-p6(i))/p7(i) ./ sqrt(2));
- elseif pshape(i) == 4; % INVGAMMA1 PRIOR
- %lnprior = lnprior + lpdfig1(para(i),p1(i),p2(i));
-% xcum(:,i) = gamcdf(1/para(:,i).^2,p2(i)/2,2/p1(i));
- xcum(:,i) = gamm_cdf((1./(para(:,i)-p3(i)).^2)/(2/p6(i)),p7(i)/2);
- elseif pshape(i) == 5; % UNIFORM PRIOR
- %lnprior = lnprior + log(1/(p2(i)-p1(i)));
- xcum(:,i) = (para(:,i)-p3(i))./(p4(i)-p3(i));
- elseif pshape(i) == 6; % INVGAMMA2 PRIOR
-% lnprior = lnprior + lpdfig2(para(i),p1(i),p2(i));
-% xcum(:,i) = gamcdf(1/para(:,i),p2(i)/2,2/p1(i));
- xcum(:,i) = gamm_cdf((1./(para(:,i)-p3(i)))./(2/p6(i)),p7(i)/2);
- end;
- i = i+1;
-end;
-
diff --git a/GSA_distrib/4.2/read_data.m b/GSA_distrib/4.2/read_data.m
deleted file mode 100644
index f54f66cb67269238108c8d93383d5e0cdf66a458..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/read_data.m
+++ /dev/null
@@ -1,39 +0,0 @@
-function [gend, data] = read_data
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global options_ bayestopt_
-
-rawdata = read_variables(options_.datafile,options_.varobs,[],options_.xls_sheet,options_.xls_range);
-
-options_ = set_default_option(options_,'nobs',size(rawdata,1)-options_.first_obs+1);
-gend = options_.nobs;
-
-rawdata = rawdata(options_.first_obs:options_.first_obs+gend-1,:);
-if options_.loglinear == 1 & ~options_.logdata
- rawdata = log(rawdata);
-end
-if options_.prefilter == 1
- bayestopt_.mean_varobs = mean(rawdata,1);
- data = transpose(rawdata-ones(gend,1)*bayestopt_.mean_varobs);
-else
- data = transpose(rawdata);
-end
-
-if ~isreal(rawdata)
- error(['There are complex values in the data. Probably a wrong' ...
- ' transformation'])
-end
diff --git a/GSA_distrib/4.2/redform_map.m b/GSA_distrib/4.2/redform_map.m
deleted file mode 100644
index 2350c599356326ea0f25014ff44899f4fece0e81..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/redform_map.m
+++ /dev/null
@@ -1,351 +0,0 @@
-function redform_map(dirname)
-%function redform_map(dirname)
-% inputs (from opt_gsa structure
-% anamendo = options_gsa_.namendo;
-% anamlagendo = options_gsa_.namlagendo;
-% anamexo = options_gsa_.namexo;
-% iload = options_gsa_.load_redform;
-% pprior = options_gsa_.pprior;
-% ilog = options_gsa_.logtrans_redform;
-% threshold = options_gsa_.threshold_redform;
-% ksstat = options_gsa_.ksstat_redform;
-% alpha2 = options_gsa_.alpha2_redform;
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global M_ oo_ estim_params_ options_ bayestopt_
-
-options_gsa_ = options_.opt_gsa;
-
-anamendo = options_gsa_.namendo;
-anamlagendo = options_gsa_.namlagendo;
-anamexo = options_gsa_.namexo;
-iload = options_gsa_.load_redform;
-pprior = options_gsa_.pprior;
-ilog = options_gsa_.logtrans_redform;
-threshold = options_gsa_.threshold_redform;
-ksstat = options_gsa_.ksstat_redform;
-alpha2 = options_gsa_.alpha2_redform;
-
-pnames = M_.param_names(estim_params_.param_vals(:,1),:);
-if nargin==0,
- dirname='';
-end
-
-if pprior
- load([dirname,'/',M_.fname,'_prior']);
- adir=[dirname '/redform_stab'];
-else
- load([dirname,'/',M_.fname,'_mc']);
- adir=[dirname '/redform_mc'];
-end
-if ~exist('T')
- stab_map_(dirname);
-if pprior
- load([dirname,'/',M_.fname,'_prior'],'T');
-else
- load([dirname,'/',M_.fname,'_mc'],'T');
-end
-end
-if isempty(dir(adir))
- mkdir(adir)
-end
-adir0=pwd;
-%cd(adir)
-
-nspred=size(T,2)-M_.exo_nbr;
-x0=lpmat(istable,:);
-[kn, np]=size(x0);
-offset = length(bayestopt_.pshape)-np;
-if options_gsa_.prior_range,
- pshape=5*(ones(np,1));
- pd = [NaN(np,1) NaN(np,1) bayestopt_.lb(offset+1:end) bayestopt_.ub(offset+1:end)];
-else
- pshape = bayestopt_.pshape(offset+1:end);
- pd = [bayestopt_.p6(offset+1:end) bayestopt_.p7(offset+1:end) bayestopt_.p3(offset+1:end) bayestopt_.p4(offset+1:end)];
-end
-
-nsok = length(find(M_.lead_lag_incidence(M_.maximum_lag,:)));
-clear lpmat lpmat0 egg iunstable yys
-js=0;
-for j=1:size(anamendo,1)
- namendo=deblank(anamendo(j,:));
- iendo=strmatch(namendo,M_.endo_names(oo_.dr.order_var,:),'exact');
- ifig=0;
- iplo=0;
- for jx=1:size(anamexo,1)
- namexo=deblank(anamexo(jx,:));
- iexo=strmatch(namexo,M_.exo_names,'exact');
-
- if ~isempty(iexo),
- %y0=squeeze(T(iendo,iexo+nspred,istable));
- y0=squeeze(T(iendo,iexo+nspred,:));
- if (max(y0)-min(y0))>1.e-10,
- if mod(iplo,9)==0,
- ifig=ifig+1;
- hfig = figure('name',[namendo,' vs. shocks ',int2str(ifig)]);
- iplo=0;
- end
- iplo=iplo+1;
- js=js+1;
- xdir0 = [adir,'/',namendo,'_vs_', namexo];
- if ilog==0,
- if isempty(threshold)
- si(:,js) = redform_private(x0, y0, pshape, pd, iload, pnames, namendo, namexo, xdir0);
- else
- iy=find( (y0>threshold(1)) & (y0<threshold(2)));
- iyc=find( (y0<=threshold(1)) | (y0>=threshold(2)));
- xdir = [xdir0,'_cut'];
- if ~isempty(iy),
- si(:,js) = redform_private(x0(iy,:), y0(iy), pshape, pd, iload, pnames, namendo, namexo, xdir);
- end
- if ~isempty(iy) & ~isempty(iyc)
- delete([xdir, '/*cut*.*'])
- [proba, dproba] = stab_map_1(x0, iy, iyc, 'cut',0);
- indsmirnov = find(dproba>ksstat);
- stab_map_1(x0, iy, iyc, 'cut',1,indsmirnov,xdir);
- stab_map_2(x0(iy,:),alpha2,'cut',xdir)
- stab_map_2(x0(iyc,:),alpha2,'trim',xdir)
- end
- end
- else
- [yy, xdir] = log_trans_(y0,xdir0);
- silog(:,js) = redform_private(x0, yy, pshape, pd, iload, pnames, namendo, namexo, xdir);
- end
-
- figure(hfig)
- subplot(3,3,iplo),
- if ilog,
- [saso, iso] = sort(-silog(:,js));
- bar([silog(iso(1:min(np,10)),js)])
- logflag='log';
- else
- [saso, iso] = sort(-si(:,js));
- bar(si(iso(1:min(np,10)),js))
- logflag='';
- end
- %set(gca,'xticklabel',pnames(iso(1:min(np,10)),:),'fontsize',8)
- set(gca,'xticklabel',' ','fontsize',10)
- set(gca,'xlim',[0.5 10.5])
- for ip=1:min(np,10),
- text(ip,-0.02,deblank(pnames(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- title([logflag,' ',namendo,' vs. ',namexo],'interpreter','none')
- if iplo==9,
- saveas(gcf,[dirname,'/',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)]);
- close(gcf)
- end
-
- end
- end
- end
- if iplo<9 & iplo>0 & ifig,
- saveas(gcf,[dirname,'/',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)]);
- close(gcf)
- end
- ifig=0;
- iplo=0;
- for je=1:size(anamlagendo,1)
- namlagendo=deblank(anamlagendo(je,:));
- ilagendo=strmatch(namlagendo,M_.endo_names(oo_.dr.order_var(oo_.dr.nstatic+1:oo_.dr.nstatic+nsok),:),'exact');
-
- if ~isempty(ilagendo),
- %y0=squeeze(T(iendo,ilagendo,istable));
- y0=squeeze(T(iendo,ilagendo,:));
- if (max(y0)-min(y0))>1.e-10,
- if mod(iplo,9)==0,
- ifig=ifig+1;
- hfig = figure('name',[namendo,' vs. lags ',int2str(ifig)]);
- iplo=0;
- end
- iplo=iplo+1;
- js=js+1;
- xdir0 = [adir,'/',namendo,'_vs_', namlagendo];
- if ilog==0,
- if isempty(threshold)
- si(:,js) = redform_private(x0, y0, pshape, pd, iload, pnames, namendo, namlagendo, xdir0);
- else
- iy=find( (y0>threshold(1)) & (y0<threshold(2)));
- iyc=find( (y0<=threshold(1)) | (y0>=threshold(2)));
- xdir = [xdir0,'_cut'];
- if ~isempty(iy)
- si(:,js) = redform_private(x0(iy,:), y0(iy), pshape, pd, iload, pnames, namendo, namlagendo, xdir);
- end
- if ~isempty(iy) & ~isempty(iyc),
- delete([xdir, '/*cut*.*'])
- [proba, dproba] = stab_map_1(x0, iy, iyc, 'cut',0);
- indsmirnov = find(dproba>ksstat);
- stab_map_1(x0, iy, iyc, 'cut',1,indsmirnov,xdir);
- stab_map_2(x0(iy,:),alpha2,'cut',xdir)
- stab_map_2(x0(iyc,:),alpha2,'trim',xdir)
- end
- end
- else
- [yy, xdir] = log_trans_(y0,xdir0);
- silog(:,js) = redform_private(x0, yy, pshape, pd, iload, pnames, namendo, namlagendo, xdir);
- end
-
- figure(hfig),
- subplot(3,3,iplo),
- if ilog,
- [saso, iso] = sort(-silog(:,js));
- bar([silog(iso(1:min(np,10)),js)])
- logflag='log';
- else
- [saso, iso] = sort(-si(:,js));
- bar(si(iso(1:min(np,10)),js))
- logflag='';
- end
- %set(gca,'xticklabel',pnames(iso(1:min(np,10)),:),'fontsize',8)
- set(gca,'xticklabel',' ','fontsize',10)
- set(gca,'xlim',[0.5 10.5])
- for ip=1:min(np,10),
- text(ip,-0.02,deblank(pnames(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- title([logflag,' ',namendo,' vs. ',namlagendo,'(-1)'],'interpreter','none')
- if iplo==9,
- saveas(gcf,[dirname,'/',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)]);
- close(gcf)
- end
-
- end
- end
- end
- if iplo<9 & iplo>0 & ifig,
- saveas(gcf,[dirname,'/',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)]);
- close(gcf)
- end
-end
-
-if ilog==0,
-figure, %bar(si)
-% boxplot(si','whis',10,'symbol','r.')
-myboxplot(si',[],'.',[],10)
-xlabel(' ')
-set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-set(gca,'xlim',[0.5 np+0.5])
-set(gca,'ylim',[0 1])
-set(gca,'position',[0.13 0.2 0.775 0.7])
-for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-end
-title('Reduced form GSA')
-
-saveas(gcf,[dirname,'/',M_.fname,'_redform_gsa'])
-eval(['print -depsc2 ' dirname,'/',M_.fname,'_redform_gsa']);
-eval(['print -dpdf ' dirname,'/',M_.fname,'_redform_gsa']);
-
-else
-figure, %bar(silog)
-% boxplot(silog','whis',10,'symbol','r.')
-myboxplot(silog',[],'.',[],10)
-set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-xlabel(' ')
-set(gca,'xlim',[0.5 np+0.5])
-set(gca,'ylim',[0 1])
-set(gca,'position',[0.13 0.2 0.775 0.7])
-for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-end
-title('Reduced form GSA - Log-transformed elements')
-
-saveas(gcf,[dirname,'/',M_.fname,'_redform_gsa_log'])
-eval(['print -depsc2 ' dirname,'/',M_.fname,'_redform_gsa_log']);
-eval(['print -dpdf ' dirname,'/',M_.fname,'_redform_gsa_log']);
-
-end
-function si = redform_private(x0, y0, pshape, pd, iload, pnames, namy, namx, xdir)
-global bayestopt_ options_
-
-opt_gsa=options_.opt_gsa;
-np=size(x0,2);
-x00=x0;
- if opt_gsa.prior_range,
- for j=1:np,
- x0(:,j)=(x0(:,j)-pd(j,3))./(pd(j,4)-pd(j,3));
- end
- else
- x0=priorcdf(x0,pshape, pd(:,1), pd(:,2), pd(:,3), pd(:,4));
- end
-
-fname=[xdir,'/map'];
-if iload==0,
- figure, hist(y0,30), title([namy,' vs. ', namx])
- if isempty(dir(xdir))
- mkdir(xdir)
- end
- saveas(gcf,[xdir,'/', namy,'_vs_', namx])
- eval(['print -depsc2 ' xdir,'/', namy,'_vs_', namx]);
- eval(['print -dpdf ' xdir,'/', namy,'_vs_', namx]);
- close(gcf)
-% gsa_ = gsa_sdp_dyn(y0, x0, -2, [],[],[],1,fname, pnames);
- nrun=length(y0);
- nest=min(250,nrun);
- nfit=min(1000,nrun);
-% dotheplots = (nfit<=nest);
- gsa_ = gsa_sdp(y0(1:nest), x0(1:nest,:), 2, [],[-1 -1 -1 -1 -1 0],[],0,[fname,'_est'], pnames);
- if nfit>nest,
- gsa_ = gsa_sdp(y0(1:nfit), x0(1:nfit,:), -2, gsa_.nvr*nest^3/nfit^3,[-1 -1 -1 -1 -1 0],[],0,fname, pnames);
- end
- save([fname,'.mat'],'gsa_')
- [sidum, iii]=sort(-gsa_.si);
- gsa_.x0=x00(1:nfit,:);
- hfig=gsa_sdp_plot(gsa_,fname,pnames,iii(1:min(12,np)));
- close(hfig);
- gsa_.x0=x0(1:nfit,:);
-% copyfile([fname,'_est.mat'],[fname,'.mat'])
- figure,
- plot(y0(1:nfit),[gsa_.fit y0(1:nfit)],'.'),
- title([namy,' vs. ', namx,' fit'])
- saveas(gcf,[xdir,'/', namy,'_vs_', namx,'_fit'])
- eval(['print -depsc2 ' xdir,'/', namy,'_vs_', namx,'_fit']);
- eval(['print -dpdf ' xdir,'/', namy,'_vs_', namx,'_fit']);
- close(gcf)
- if nfit<nrun,
- npred=[nfit+1:nrun];
- yf = ss_anova_fcast(x0(npred,:), gsa_);
- figure,
- plot(y0(npred),[yf y0(npred)],'.'),
- title([namy,' vs. ', namx,' pred'])
- saveas(gcf,[xdir,'/', namy,'_vs_', namx,'_pred'])
- eval(['print -depsc2 ' xdir,'/', namy,'_vs_', namx,'_pred']);
- eval(['print -dpdf ' xdir,'/', namy,'_vs_', namx,'_pred']);
- close(gcf)
- end
-else
-% gsa_ = gsa_sdp_dyn(y0, x0, 0, [],[],[],0,fname, pnames);
- gsa_ = gsa_sdp(y0, x0, 0, [],[],[],0,fname, pnames);
- yf = ss_anova_fcast(x0, gsa_);
- figure,
- plot(y0,[yf y0],'.'),
- title([namy,' vs. ', namx,' pred'])
- saveas(gcf,[xdir,'/', namy,'_vs_', namx,'_pred'])
- eval(['print -depsc2 ' xdir,'/', namy,'_vs_', namx,'_pred']);
- eval(['print -dpdf ' xdir,'/', namy,'_vs_', namx,'_pred']);
- close(gcf)
-end
-% si = gsa_.multivariate.si;
-si = gsa_.si;
-
diff --git a/GSA_distrib/4.2/redform_screen.m b/GSA_distrib/4.2/redform_screen.m
deleted file mode 100644
index 56aae7c39e29c28f982d970f7fa4c6233accf3e9..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/redform_screen.m
+++ /dev/null
@@ -1,165 +0,0 @@
-function redform_screen(dirname)
-%function redform_map(dirname)
-% inputs (from opt_gsa structure
-% anamendo = options_gsa_.namendo;
-% anamlagendo = options_gsa_.namlagendo;
-% anamexo = options_gsa_.namexo;
-% iload = options_gsa_.load_redform;
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global M_ oo_ estim_params_ options_ bayestopt_
-
-options_gsa_ = options_.opt_gsa;
-
-anamendo = options_gsa_.namendo;
-anamlagendo = options_gsa_.namlagendo;
-anamexo = options_gsa_.namexo;
-iload = options_gsa_.load_redform;
-nliv = options_gsa_.morris_nliv;
-
-pnames = M_.param_names(estim_params_.param_vals(:,1),:);
-if nargin==0,
- dirname='';
-end
-
-load([dirname,'/',M_.fname,'_prior'],'lpmat','lpmat0','istable','T');
-
-nspred=oo_.dr.nspred;
-
-[kn, np]=size(lpmat);
-nshock = length(bayestopt_.pshape)-np;
-
-nsok = length(find(M_.lead_lag_incidence(M_.maximum_lag,:)));
-
-js=0;
-for j=1:size(anamendo,1),
- namendo=deblank(anamendo(j,:));
- iendo=strmatch(namendo,M_.endo_names(oo_.dr.order_var,:),'exact');
-
- iplo=0;
- ifig=0;
- for jx=1:size(anamexo,1)
- namexo=deblank(anamexo(jx,:));
- iexo=strmatch(namexo,M_.exo_names,'exact');
-
- if ~isempty(iexo),
- y0=teff(T(iendo,iexo+nspred,:),kn,istable);
- if ~isempty(y0),
- if mod(iplo,9)==0,
- ifig=ifig+1;
- figure('name',[namendo,' vs. shocks ',int2str(ifig)]),
- iplo=0;
- end
- iplo=iplo+1;
- js=js+1;
- subplot(3,3,iplo),
- [SAmeas, SAMorris] = Morris_Measure_Groups(np+nshock, [lpmat0 lpmat], y0,nliv);
- SAM = squeeze(SAMorris(nshock+1:end,1));
- SA(:,js)=SAM./(max(SAM)+eps);
- [saso, iso] = sort(-SA(:,js));
- bar(SA(iso(1:min(np,10)),js))
- %set(gca,'xticklabel',pnames(iso(1:min(np,10)),:),'fontsize',8)
- set(gca,'xticklabel',' ','fontsize',10)
- set(gca,'xlim',[0.5 10.5])
- for ip=1:min(np,10),
- text(ip,-0.02,deblank(pnames(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
- title([namendo,' vs. ',namexo],'interpreter','none')
- if iplo==9,
- saveas(gcf,[dirname,'/',M_.fname,'_', namendo,'_vs_shock_',num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_', namendo,'_vs_shock_',num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_', namendo,'_vs_shock_',num2str(ifig)]);
- close(gcf)
- end
-
- end
- end
- end
- if iplo<9 & iplo>0 & ifig,
- saveas(gcf,[dirname,'/',M_.fname,'_', namendo,'_vs_shocks_',num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_', namendo,'_vs_shocks_',num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_', namendo,'_vs_shocks_',num2str(ifig)]);
- close(gcf)
- end
-
- iplo=0;
- ifig=0;
- for je=1:size(anamlagendo,1)
- namlagendo=deblank(anamlagendo(je,:));
- ilagendo=strmatch(namlagendo,M_.endo_names(oo_.dr.order_var(oo_.dr.nstatic+1:oo_.dr.nstatic+nsok),:),'exact');
-
- if ~isempty(ilagendo),
- y0=teff(T(iendo,ilagendo,:),kn,istable);
- if ~isempty(y0),
- if mod(iplo,9)==0,
- ifig=ifig+1;
- figure('name',[namendo,' vs. lagged endogenous ',int2str(ifig)]),
- iplo=0;
- end
- iplo=iplo+1;
- js=js+1;
- subplot(3,3,iplo),
- [SAmeas, SAMorris] = Morris_Measure_Groups(np+nshock, [lpmat0 lpmat], y0,nliv);
- SAM = squeeze(SAMorris(nshock+1:end,1));
- SA(:,js)=SAM./(max(SAM)+eps);
- [saso, iso] = sort(-SA(:,js));
- bar(SA(iso(1:min(np,10)),js))
- %set(gca,'xticklabel',pnames(iso(1:min(np,10)),:),'fontsize',8)
- set(gca,'xticklabel',' ','fontsize',10)
- set(gca,'xlim',[0.5 10.5])
- for ip=1:min(np,10),
- text(ip,-0.02,deblank(pnames(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
- end
-
- title([namendo,' vs. ',namlagendo,'(-1)'],'interpreter','none')
- if iplo==9,
- saveas(gcf,[dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)]);
- close(gcf)
- end
- end
- end
- end
- if iplo<9 & iplo>0 & ifig,
- saveas(gcf,[dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)])
- eval(['print -depsc2 ' dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)]);
- eval(['print -dpdf ' dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)]);
- close(gcf)
- end
-end
-
-figure,
-%bar(SA)
-% boxplot(SA','whis',10,'symbol','r.')
-myboxplot(SA',[],'.',[],10)
-set(gca,'xticklabel',' ','fontsize',10,'xtick',[1:np])
-set(gca,'xlim',[0.5 np+0.5])
-set(gca,'ylim',[0 1])
-set(gca,'position',[0.13 0.2 0.775 0.7])
-for ip=1:np,
- text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
-end
-xlabel(' ')
-ylabel('Elementary Effects')
-title('Reduced form screening')
-
-saveas(gcf,[dirname,'/',M_.fname,'_redform_screen'])
-eval(['print -depsc2 ' dirname,'/',M_.fname,'_redform_screen']);
-eval(['print -dpdf ' dirname,'/',M_.fname,'_redform_screen']);
-
diff --git a/GSA_distrib/4.2/set_shocks_param.m b/GSA_distrib/4.2/set_shocks_param.m
deleted file mode 100644
index f84247d299917645863b894899ee43c7b53e9391..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/set_shocks_param.m
+++ /dev/null
@@ -1,30 +0,0 @@
-function set_shocks_param(xparam1)
- global estim_params_ M_
-
- nvx = estim_params_.nvx;
- ncx = estim_params_.ncx;
- np = estim_params_.np;
- Sigma_e = M_.Sigma_e;
- offset = 0;
- if nvx
- offset = offset + nvx;
- var_exo = estim_params_.var_exo;
- for i=1:nvx
- k = var_exo(i,1);
- Sigma_e(k,k) = xparam1(i)^2;
- end
- end
-
- if ncx
- offset = offset + estim_params_.nvn;
- corrx = estim_params_.corrx;
- for i=1:ncx
- k1 = corrx(i,1);
- k2 = corrx(i,2);
- Sigma_e(k1,k2) = xparam1(i+offset)*sqrt(Sigma_e_(k1,k1)*Sigma_e_(k2,k2));
- Sigma_e(k2,k1) = Sigma_e_(k1,k2);
- end
- end
-
-
- M_.Sigma_e = Sigma_e;
\ No newline at end of file
diff --git a/GSA_distrib/4.2/skewness.m b/GSA_distrib/4.2/skewness.m
deleted file mode 100644
index 19ce487ab85deb85797680f06fc12f8db20c9d4b..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/skewness.m
+++ /dev/null
@@ -1,7 +0,0 @@
-function s=skewness(y),
-
-% y=stand_(y);
-% s=mean(y.^3);
- m2=mean((y-mean(y)).^2);
- m3=mean((y-mean(y)).^3);
- s=m3/m2^1.5;
\ No newline at end of file
diff --git a/GSA_distrib/4.2/smirnov.m b/GSA_distrib/4.2/smirnov.m
deleted file mode 100644
index bc068aeb1046e90ee8f739deff1c256a5bc0fcba..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/smirnov.m
+++ /dev/null
@@ -1,73 +0,0 @@
-function [H,prob,d] = smirnov(x1 , x2 , alpha, iflag )
-% Smirnov test for 2 distributions
-% [H,prob,d] = smirnov(x1 , x2 , alpha, iflag )
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-
-
-if nargin<3
- alpha = 0.05;
-end
-if nargin<4,
- iflag=0;
-end
-
-% empirical cdfs.
-xmix= [x1;x2];
-bin = [-inf ; sort(xmix) ; inf];
-
-ncount1 = histc (x1 , bin);
-ncount1 = ncount1(:);
-ncount2 = histc (x2 , bin);
-ncount2 = ncount2(:);
-
-cum1 = cumsum(ncount1)./sum(ncount1);
-cum1 = cum1(1:end-1);
-
-cum2 = cumsum(ncount2)./sum(ncount2);
-cum2 = cum2(1:end-1);
-
-n1= length(x1);
-n2= length(x2);
-n = n1*n2 /(n1+n2);
-
-% Compute the d(n1,n2) statistics.
-
-if iflag==0,
- d = max(abs(cum1 - cum2));
-elseif iflag==-1
- d = max(cum2 - cum1);
-elseif iflag==1
- d = max(cum1 - cum2);
-end
-%
-% Compute P-value check H0 hypothesis
-%
-
-lam = max((sqrt(n) + 0.12 + 0.11/sqrt(n)) * d , 0);
-if iflag == 0
- j = [1:101]';
- prob = 2 * sum((-1).^(j-1).*exp(-2*lam*lam*j.^2));
-
- prob=max(prob,0);
- prob=min(1,prob);
-else
- prob = exp(-2*lam*lam);
-end
-
-H = (alpha >= prob);
diff --git a/GSA_distrib/4.2/speed.m b/GSA_distrib/4.2/speed.m
deleted file mode 100644
index faaa1de86ead1e91c71bcbf0f81f09cdc2c3e587..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/speed.m
+++ /dev/null
@@ -1,52 +0,0 @@
-function [tadj, iff] = speed(A,B,mf,p),
-% [tadj, iff] = speed(A,B,mf,p),
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-nvar=length(mf);
-nstate= size(A,1);
-nshock = size(B,2);
-nrun=size(B,3);
-
-iff=zeros(nvar,nshock,nrun);
-tadj=iff;
-disp('Computing speed of adjustement ...')
-h = waitbar(0,'Speed of adjustement...');
-
-for i=1:nrun,
- irf=zeros(nvar,nshock);
- a=squeeze(A(:,:,i));
- b=squeeze(B(:,:,i));
- IFF=inv(eye(nstate)-a)*b;
- iff(:,:,i)=IFF(mf,:);
- IF=IFF-b;
-
- t=0;
- while any(any(irf<0.5))
- t=t+1;
- IFT=((eye(nstate)-a^(t+1))*inv(eye(nstate)-a))*b-b;
- irf=IFT(mf,:)./(IF(mf,:)+eps);
- irf = irf.*(abs(IF(mf,:))>1.e-7)+(abs(IF(mf,:))<=1.e-7);
- %irf=ft(mf,:);
- tt=(irf>0.5).*t;
- tadj(:,:,i)=((tt-tadj(:,:,i))==tt).*tt+tadj(:,:,i);
- end
- waitbar(i/nrun,h)
-end
-disp(' ')
-disp('.. done !')
-close(h)
diff --git a/GSA_distrib/4.2/stab_map_.m b/GSA_distrib/4.2/stab_map_.m
deleted file mode 100644
index 2142ec23414d9e24f2e962debff8fb24d39dcf7e..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/stab_map_.m
+++ /dev/null
@@ -1,548 +0,0 @@
-function x0 = stab_map_(OutputDirectoryName)
-%
-% function x0 = stab_map_(OutputDirectoryName)
-%
-% Mapping of stability regions in the prior ranges applying
-% Monte Carlo filtering techniques.
-%
-% INPUTS (from opt_gsa structure)
-% Nsam = MC sample size
-% fload = 0 to run new MC; 1 to load prevoiusly generated analysis
-% alpha2 = significance level for bivariate sensitivity analysis
-% [abs(corrcoef) > alpha2]
-% prepSA = 1: save transition matrices for mapping reduced form
-% = 0: no transition matrix saved (default)
-% pprior = 1: sample from prior ranges (default): sample saved in
-% _prior.mat file
-% = 0: sample from posterior ranges: sample saved in
-% _mc.mat file
-% OUTPUT:
-% x0: one parameter vector for which the model is stable.
-%
-% GRAPHS
-% 1) Pdf's of marginal distributions under the stability (dotted
-% lines) and unstability (solid lines) regions
-% 2) Cumulative distributions of:
-% - stable subset (dotted lines)
-% - unacceptable subset (solid lines)
-% 3) Bivariate plots of significant correlation patterns
-% ( abs(corrcoef) > alpha2) under the stable and unacceptable subsets
-%
-% USES lptauSEQ,
-% stab_map_1, stab_map_2
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-%global bayestopt_ estim_params_ dr_ options_ ys_ fname_
-global bayestopt_ estim_params_ options_ oo_ M_
-
-opt_gsa=options_.opt_gsa;
-
-Nsam = opt_gsa.Nsam;
-fload = opt_gsa.load_stab;
-ksstat = opt_gsa.ksstat;
-alpha2 = opt_gsa.alpha2_stab;
-prepSA = (opt_gsa.redform | opt_gsa.identification);
-pprior = opt_gsa.pprior;
-ilptau = opt_gsa.ilptau;
-nliv = opt_gsa.morris_nliv;
-ntra = opt_gsa.morris_ntra;
-
-dr_ = oo_.dr;
-%if isfield(dr_,'ghx'),
-ys_ = oo_.dr.ys;
-nspred = dr_.nspred; %size(dr_.ghx,2);
-nboth = dr_.nboth;
-nfwrd = dr_.nfwrd;
-%end
-fname_ = M_.fname;
-
-np = estim_params_.np;
-nshock = estim_params_.nvx;
-nshock = nshock + estim_params_.nvn;
-nshock = nshock + estim_params_.ncx;
-nshock = nshock + estim_params_.ncn;
-lpmat0=[];
-
-pshape = bayestopt_.pshape(nshock+1:end);
-p1 = bayestopt_.p1(nshock+1:end);
-p2 = bayestopt_.p2(nshock+1:end);
-p3 = bayestopt_.p3(nshock+1:end);
-p4 = bayestopt_.p4(nshock+1:end);
-
-if nargin==0,
- OutputDirectoryName='';
-end
-
-opt=options_;
-options_.periods=0;
-options_.nomoments=1;
-options_.irf=0;
-options_.noprint=1;
-options_.simul=0;
-if fload==0,
- % if prepSA
- % T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),Nsam/2);
- % end
-
- if isfield(dr_,'ghx'),
- egg=zeros(length(dr_.eigval),Nsam);
- end
- yys=zeros(length(dr_.ys),Nsam);
-
- if opt_gsa.morris == 1
- [lpmat, OutFact] = Sampling_Function_2(nliv, np+nshock, ntra, ones(np+nshock, 1), zeros(np+nshock,1), []);
- lpmat = lpmat.*(nliv-1)/nliv+1/nliv/2;
- Nsam=size(lpmat,1);
- lpmat0 = lpmat(:,1:nshock);
- lpmat = lpmat(:,nshock+1:end);
- elseif opt_gsa.morris==3,
- lpmat = prep_ide(Nsam,np,5);
- Nsam=size(lpmat,1);
- else
- if np<52 & ilptau>0,
- [lpmat] = lptauSEQ(Nsam,np); % lptau
- if np>30 | ilptau==2, % scrambled lptau
- for j=1:np,
- lpmat(:,j)=lpmat(randperm(Nsam),j);
- end
- end
- else %ilptau==0
- %[lpmat] = rand(Nsam,np);
- for j=1:np,
- lpmat(:,j) = randperm(Nsam)'./(Nsam+1); %latin hypercube
- end
-
- end
- end
- % try
- dummy=prior_draw_gsa(1);
- % catch
- % if pprior,
- % if opt_gsa.prior_range==0;
- % error('Some unknown prior is specified or ML estimation,: use prior_range=1 option!!');
- % end
- % end
- %
- % end
- if pprior,
- for j=1:nshock,
- if opt_gsa.morris~=1,
- lpmat0(:,j) = randperm(Nsam)'./(Nsam+1); %latin hypercube
- end
- if opt_gsa.prior_range
- lpmat0(:,j)=lpmat0(:,j).*(bayestopt_.ub(j)-bayestopt_.lb(j))+bayestopt_.lb(j);
- end
- end
- if opt_gsa.prior_range
- % if opt_gsa.identification,
- % deltx=min(0.001, 1/Nsam/2);
- % for j=1:np,
- % xdelt(:,:,j)=prior_draw_gsa(0,[lpmat0 lpmat]+deltx);
- % end
- % end
- for j=1:np,
- lpmat(:,j)=lpmat(:,j).*(bayestopt_.ub(j+nshock)-bayestopt_.lb(j+nshock))+bayestopt_.lb(j+nshock);
- end
- else
- xx=prior_draw_gsa(0,[lpmat0 lpmat]);
- % if opt_gsa.identification,
- % deltx=min(0.001, 1/Nsam/2);
- % ldum=[lpmat0 lpmat];
- % ldum = prior_draw_gsa(0,ldum+deltx);
- % for j=1:nshock+np,
- % xdelt(:,:,j)=xx;
- % xdelt(:,j,j)=ldum(:,j);
- % end
- % clear ldum
- % end
- lpmat0=xx(:,1:nshock);
- lpmat=xx(:,nshock+1:end);
- clear xx;
- end
- else
- % for j=1:nshock,
- % xparam1(j) = oo_.posterior_mode.shocks_std.(bayestopt_.name{j});
- % sd(j) = oo_.posterior_std.shocks_std.(bayestopt_.name{j});
- % lpmat0(:,j) = randperm(Nsam)'./(Nsam+1); %latin hypercube
- % lb = max(bayestopt_.lb(j), xparam1(j)-2*sd(j));
- % ub1=xparam1(j)+(xparam1(j) - lb); % define symmetric range around the mode!
- % ub = min(bayestopt_.ub(j),ub1);
- % if ub<ub1,
- % lb=xparam1(j)-(ub-xparam1(j)); % define symmetric range around the mode!
- % end
- % lpmat0(:,j) = lpmat0(:,j).*(ub-lb)+lb;
- % end
- % %
- % for j=1:np,
- % xparam1(j+nshock) = oo_.posterior_mode.parameters.(bayestopt_.name{j+nshock});
- % sd(j+nshock) = oo_.posterior_std.parameters.(bayestopt_.name{j+nshock});
- % lb = max(bayestopt_.lb(j+nshock),xparam1(j+nshock)-2*sd(j+nshock));
- % ub1=xparam1(j+nshock)+(xparam1(j+nshock) - lb); % define symmetric range around the mode!
- % ub = min(bayestopt_.ub(j+nshock),ub1);
- % if ub<ub1,
- % lb=xparam1(j+nshock)-(ub-xparam1(j+nshock)); % define symmetric range around the mode!
- % end
- % %ub = min(bayestopt_.ub(j+nshock),xparam1(j+nshock)+2*sd(j+nshock));
- % if np>30 & np<52
- % lpmat(:,j) = lpmat(randperm(Nsam),j).*(ub-lb)+lb;
- % else
- % lpmat(:,j) = lpmat(:,j).*(ub-lb)+lb;
- % end
- % end
- %load([fname_,'_mode'])
- eval(['load ' options_.mode_file ';']');
- d = chol(inv(hh));
- lp=randn(Nsam*2,nshock+np)*d+kron(ones(Nsam*2,1),xparam1');
- for j=1:Nsam*2,
- lnprior(j) = any(lp(j,:)'<=bayestopt_.lb | lp(j,:)'>=bayestopt_.ub);
- end
- ireal=[1:2*Nsam];
- ireal=ireal(find(lnprior==0));
- lp=lp(ireal,:);
- Nsam=min(Nsam, length(ireal));
- lpmat0=lp(1:Nsam,1:nshock);
- lpmat=lp(1:Nsam,nshock+1:end);
- clear lp lnprior ireal;
- end
- %
- h = waitbar(0,'Please wait...');
- istable=[1:Nsam];
- jstab=0;
- iunstable=[1:Nsam];
- iindeterm=zeros(1,Nsam);
- iwrong=zeros(1,Nsam);
- for j=1:Nsam,
- M_.params(estim_params_.param_vals(:,1)) = lpmat(j,:)';
- %try stoch_simul([]);
- try
- [Tt,Rr,SteadyState,infox{j}] = dynare_resolve('restrict');
- if infox{j}(1)==0 && ~exist('T'),
- dr_=oo_.dr;
- T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),Nsam);
- egg=zeros(length(dr_.eigval),Nsam);
- end
- if infox{j},
- disp('no solution'),
- if isfield(oo_.dr,'ghx'),
- oo_.dr=rmfield(oo_.dr,'ghx');
- end
- end
- catch
- if isfield(oo_.dr,'eigval'),
- oo_.dr=rmfield(oo_.dr,'eigval');
- end
- if isfield(oo_.dr,'ghx'),
- oo_.dr=rmfield(oo_.dr,'ghx');
- end
- disp('No solution could be found'),
- end
- dr_ = oo_.dr;
- if isfield(dr_,'ghx'),
- egg(:,j) = sort(dr_.eigval);
- iunstable(j)=0;
- if prepSA
- jstab=jstab+1;
- T(:,:,jstab) = [dr_.ghx dr_.ghu];
- % [A,B] = ghx2transition(squeeze(T(:,:,jstab)), ...
- % bayestopt_.restrict_var_list, ...
- % bayestopt_.restrict_columns, ...
- % bayestopt_.restrict_aux);
- end
- if ~exist('nspred'),
- nspred = dr_.nspred; %size(dr_.ghx,2);
- nboth = dr_.nboth;
- nfwrd = dr_.nfwrd;
- end
- else
- istable(j)=0;
- if isfield(dr_,'eigval')
- egg(:,j) = sort(dr_.eigval);
- if exist('nspred')
- if any(isnan(egg(1:nspred,j)))
- iwrong(j)=j;
- else
- if (nboth | nfwrd) & abs(egg(nspred+1,j))<=options_.qz_criterium,
- iindeterm(j)=j;
- end
- end
- end
- else
- if exist('egg'),
- egg(:,j)=ones(size(egg,1),1).*NaN;
- end
- iwrong(j)=j;
- end
- end
- ys_=real(dr_.ys);
- yys(:,j) = ys_;
- ys_=yys(:,1);
- waitbar(j/Nsam,h,['MC iteration ',int2str(j),'/',int2str(Nsam)])
- end
- close(h)
- if prepSA,
- T=T(:,:,1:jstab);
- end
- istable=istable(find(istable)); % stable params
- iunstable=iunstable(find(iunstable)); % unstable params
- iindeterm=iindeterm(find(iindeterm)); % indeterminacy
- iwrong=iwrong(find(iwrong)); % dynare could not find solution
-
- % % map stable samples
- % istable=[1:Nsam];
- % for j=1:Nsam,
- % if any(isnan(egg(1:nspred,j)))
- % istable(j)=0;
- % else
- % if abs(egg(nspred,j))>=options_.qz_criterium; %(1-(options_.qz_criterium-1)); %1-1.e-5;
- % istable(j)=0;
- % %elseif (dr_.nboth | dr_.nfwrd) & abs(egg(nspred+1,j))<=options_.qz_criterium; %1+1.e-5;
- % elseif (nboth | nfwrd) & abs(egg(nspred+1,j))<=options_.qz_criterium; %1+1.e-5;
- % istable(j)=0;
- % end
- % end
- % end
- % istable=istable(find(istable)); % stable params
- %
- % % map unstable samples
- % iunstable=[1:Nsam];
- % for j=1:Nsam,
- % %if abs(egg(dr_.npred+1,j))>1+1.e-5 & abs(egg(dr_.npred,j))<1-1.e-5;
- % %if (dr_.nboth | dr_.nfwrd),
- % if ~any(isnan(egg(1:5,j)))
- % if (nboth | nfwrd),
- % if abs(egg(nspred+1,j))>options_.qz_criterium & abs(egg(nspred,j))<options_.qz_criterium; %(1-(options_.qz_criterium-1));
- % iunstable(j)=0;
- % end
- % else
- % if abs(egg(nspred,j))<options_.qz_criterium; %(1-(options_.qz_criterium-1));
- % iunstable(j)=0;
- % end
- % end
- % end
- % end
- % iunstable=iunstable(find(iunstable)); % unstable params
- bkpprior.pshape=bayestopt_.pshape;
- bkpprior.p1=bayestopt_.p1;
- bkpprior.p2=bayestopt_.p2;
- bkpprior.p3=bayestopt_.p3;
- bkpprior.p4=bayestopt_.p4;
- if pprior,
- if ~prepSA
- save([OutputDirectoryName '/' fname_ '_prior'], ...
- 'bkpprior','lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
- 'egg','yys','nspred','nboth','nfwrd')
- else
- save([OutputDirectoryName '/' fname_ '_prior'], ...
- 'bkpprior','lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
- 'egg','yys','T','nspred','nboth','nfwrd')
- end
-
- else
- if ~prepSA
- save([OutputDirectoryName '/' fname_ '_mc'], ...
- 'lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
- 'egg','yys','nspred','nboth','nfwrd')
- else
- save([OutputDirectoryName '/' fname_ '_mc'], ...
- 'lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
- 'egg','yys','T','nspred','nboth','nfwrd')
- end
- end
-else
- if pprior,
- filetoload=[OutputDirectoryName '/' fname_ '_prior'];
- else
- filetoload=[OutputDirectoryName '/' fname_ '_mc'];
- end
- load(filetoload,'lpmat','lpmat0','iunstable','istable','iindeterm','iwrong','egg','yys','nspred','nboth','nfwrd')
- Nsam = size(lpmat,1);
-
-
- if prepSA & isempty(strmatch('T',who('-file', filetoload),'exact')),
- h = waitbar(0,'Please wait...');
- options_.periods=0;
- options_.nomoments=1;
- options_.irf=0;
- options_.noprint=1;
- stoch_simul([]);
- %T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),length(istable));
- ntrans=length(istable);
- for j=1:ntrans,
- M_.params(estim_params_.param_vals(:,1)) = lpmat(istable(j),:)';
- %stoch_simul([]);
- [Tt,Rr,SteadyState,info] = dynare_resolve(bayestopt_.restrict_var_list,...
- bayestopt_.restrict_columns,...
- bayestopt_.restrict_aux);
- if ~exist('T')
- T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),ntrans);
- end
- dr_ = oo_.dr;
- T(:,:,j) = [dr_.ghx dr_.ghu];
- if ~exist('nspred')
- nspred = dr_.nspred; %size(dr_.ghx,2);
- nboth = dr_.nboth;
- nfwrd = dr_.nfwrd;
- end
- ys_=real(dr_.ys);
- yys(:,j) = ys_;
- ys_=yys(:,1);
- waitbar(j/ntrans,h,['MC iteration ',int2str(j),'/',int2str(ntrans)])
- end
- close(h)
- save(filetoload,'T','-append')
- elseif prepSA
- load(filetoload,'T')
- end
-end
-
-if pprior
- aname='prior_stab';
- auname='prior_unacceptable';
- aunstname='prior_unstable';
- aindname='prior_indeterm';
- awrongname='prior_wrong';
- asname='prior_stable';
-else
- aname='mc_stab';
- auname='mc_unacceptable';
- aunstname='mc_unstable';
- aindname='mc_indeterm';
- awrongname='mc_wrong';
- asname='mc_stable';
-end
-delete([OutputDirectoryName,'/',fname_,'_',aname,'_*.*']);
-%delete([OutputDirectoryName,'/',fname_,'_',aname,'_SA_*.*']);
-delete([OutputDirectoryName,'/',fname_,'_',asname,'_corr_*.*']);
-delete([OutputDirectoryName,'/',fname_,'_',auname,'_corr_*.*']);
-delete([OutputDirectoryName,'/',fname_,'_',aunstname,'_corr_*.*']);
-delete([OutputDirectoryName,'/',fname_,'_',aindname,'_corr_*.*']);
-
-if length(iunstable)>0 & length(iunstable)<Nsam,
- disp([num2str(length(istable)/Nsam*100,3),'\% of the prior support is stable.'])
- disp([num2str( (length(iunstable)-length(iwrong)-length(iindeterm) )/Nsam*100),'\% of the prior support is unstable.'])
- if ~isempty(iindeterm),
- disp([num2str(length(iindeterm)/Nsam*100,3),'\% of the prior support gives indeterminacy.'])
- end
- if ~isempty(iwrong),
- disp(' ');
- disp(['For ',num2str(length(iwrong)/Nsam*100,3),'\% of the prior support dynare could not find a solution.'])
- end
- disp(' ');
- % Blanchard Kahn
- [proba, dproba] = stab_map_1(lpmat, istable, iunstable, aname,0);
- indstab=find(dproba>ksstat);
- disp('Smirnov statistics in driving acceptable behaviour')
- for j=1:np,
- disp([M_.param_names(estim_params_.param_vals(j,1),:),' d-stat = ', num2str(dproba(j),3)])
- end
- disp(' ');
- if ~isempty(indstab)
- stab_map_1(lpmat, istable, iunstable, aname, 1, indstab, OutputDirectoryName);
- end
- ixun=iunstable(find(~ismember(iunstable,[iindeterm,iwrong])));
- if ~isempty(iindeterm),
- [proba, dproba] = stab_map_1(lpmat, [1:Nsam], iindeterm, [aname, '_indet'],0);
- indindet=find(dproba>ksstat);
- disp('Smirnov statistics in driving indeterminacy')
- for j=1:np,
- disp([M_.param_names(estim_params_.param_vals(j,1),:),' d-stat = ', num2str(dproba(j),3)])
- end
- disp(' ');
- if ~isempty(indindet)
- stab_map_1(lpmat, [1:Nsam], iindeterm, [aname, '_indet'], 1, indindet, OutputDirectoryName);
- end
- end
-
- if ~isempty(ixun),
- [proba, dproba] = stab_map_1(lpmat, [1:Nsam], ixun, [aname, '_unst'],0);
- indunst=find(dproba>ksstat);
- disp('Smirnov statistics in driving instability')
- for j=1:np,
- disp([M_.param_names(estim_params_.param_vals(j,1),:),' d-stat = ', num2str(dproba(j),3)])
- end
- disp(' ');
- if ~isempty(indunst)
- stab_map_1(lpmat, [1:Nsam], ixun, [aname, '_unst'], 1, indunst, OutputDirectoryName);
- end
- end
-
- if ~isempty(iwrong),
- [proba, dproba] = stab_map_1(lpmat, [1:Nsam], iwrong, [aname, '_wrong'],0);
- indwrong=find(dproba>ksstat);
- disp('Smirnov statistics in driving no solution')
- for j=1:np,
- disp([M_.param_names(estim_params_.param_vals(j,1),:),' d-stat = ', num2str(dproba(j),3)])
- end
- disp(' ');
- if ~isempty(indwrong)
- stab_map_1(lpmat, [1:Nsam], iwrong, [aname, '_wrong'], 1, indwrong, OutputDirectoryName);
- end
- end
-
- disp(' ')
- disp('Starting bivariate analysis:')
-
- c0=corrcoef(lpmat(istable,:));
- c00=tril(c0,-1);
-
- stab_map_2(lpmat(istable,:),alpha2, asname, OutputDirectoryName);
- if length(iunstable)>10,
- stab_map_2(lpmat(iunstable,:),alpha2, auname, OutputDirectoryName);
- end
- if length(iindeterm)>10,
- stab_map_2(lpmat(iindeterm,:),alpha2, aindname, OutputDirectoryName);
- end
- if length(ixun)>10,
- stab_map_2(lpmat(ixun,:),alpha2, aunstname, OutputDirectoryName);
- end
- if length(iwrong)>10,
- stab_map_2(lpmat(iwrong,:),alpha2, awrongname, OutputDirectoryName);
- end
-
- x0=0.5.*(bayestopt_.ub(1:nshock)-bayestopt_.lb(1:nshock))+bayestopt_.lb(1:nshock);
- x0 = [x0; lpmat(istable(1),:)'];
- if istable(end)~=Nsam
- M_.params(estim_params_.param_vals(:,1)) = lpmat(istable(1),:)';
- [oo_.dr, info] = resol(oo_.steady_state,0);
- % stoch_simul([]);
- end
-else
- if length(iunstable)==0,
- disp('All parameter values in the specified ranges are stable!')
- x0=0.5.*(bayestopt_.ub(1:nshock)-bayestopt_.lb(1:nshock))+bayestopt_.lb(1:nshock);
- x0 = [x0; lpmat(istable(1),:)'];
- else
- disp('All parameter values in the specified ranges are not acceptable!')
- x0=[];
- end
-
-end
-
-
-options_.periods=opt.periods;
-if isfield(opt,'nomoments'),
- options_.nomoments=opt.nomoments;
-end
-options_.irf=opt.irf;
-options_.noprint=opt.noprint;
-if isfield(opt,'simul'),
- options_.simul=opt.simul;
-end
-
-
-
diff --git a/GSA_distrib/4.2/stab_map_1.m b/GSA_distrib/4.2/stab_map_1.m
deleted file mode 100644
index 8813fa572d19097e74e50f8b1faaf5aa68ff29ce..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/stab_map_1.m
+++ /dev/null
@@ -1,87 +0,0 @@
-function [proba, dproba] = stab_map_1(lpmat, ibehaviour, inonbehaviour, aname, iplot, ipar, dirname)
-%function [proba, dproba] = stab_map_1(lpmat, ibehaviour, inonbehaviour, aname, iplot, ipar, dirname)
-%
-% lpmat = Monte Carlo matrix
-% ibehaviour = index of behavioural runs
-% inonbehaviour = index of non-behavioural runs
-% aname = label of the analysis
-% iplot = 1 plot cumulative distributions (default)
-% iplot = 0 no plots
-% ipar = index array of parameters to plot
-% dirname = (OPTIONAL) path of the directory where to save
-% (default: current directory)
-%
-% Plots: dotted lines for BEHAVIOURAL
-% solid lines for NON BEHAVIOURAL
-% USES smirnov
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-global estim_params_ bayestopt_ M_ options_
-
-if nargin<5,
- iplot=1;
-end
-fname_ = M_.fname;
-if nargin<7,
- dirname='';;
-end
-
-nshock = estim_params_.nvx;
-nshock = nshock + estim_params_.nvn;
-nshock = nshock + estim_params_.ncx;
-nshock = nshock + estim_params_.ncn;
-
-npar=size(lpmat,2);
-ishock= npar>estim_params_.np;
-
-if nargin<6 | isempty(ipar),
- ipar=[1:npar];
-end
-nparplot=length(ipar);
-
-% Smirnov test for Blanchard;
-for j=1:npar,
- [H,P,KSSTAT] = smirnov(lpmat(ibehaviour,j),lpmat(inonbehaviour,j));
- proba(j)=P;
- dproba(j)=KSSTAT;
-end
-if iplot
- lpmat=lpmat(:,ipar);
- ftit=bayestopt_.name(ipar+nshock*(1-ishock));
-
-for i=1:ceil(nparplot/12),
- figure('name',aname),
- for j=1+12*(i-1):min(nparplot,12*i),
- subplot(3,4,j-12*(i-1))
- if ~isempty(ibehaviour),
- h=cumplot(lpmat(ibehaviour,j));
- set(h,'color',[0 0 0], 'linestyle',':')
- end
- hold on,
- if ~isempty(inonbehaviour),
- h=cumplot(lpmat(inonbehaviour,j));
- set(h,'color',[0 0 0])
- end
- title([ftit{j},'. D-stat ', num2str(dproba(ipar(j)),2)],'interpreter','none')
- end
- saveas(gcf,[dirname,'/',fname_,'_',aname,'_SA_',int2str(i)])
- eval(['print -depsc2 ' dirname '/' fname_ '_' aname '_SA_' int2str(i)]);
- eval(['print -dpdf ' dirname '/' fname_ '_' aname '_SA_' int2str(i)]);
- if options_.nograph, close(gcf), end
-end
-end
diff --git a/GSA_distrib/4.2/stab_map_2.m b/GSA_distrib/4.2/stab_map_2.m
deleted file mode 100644
index 3d1a8fa9cd39ca5b7668183156e780701ccdff81..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/stab_map_2.m
+++ /dev/null
@@ -1,97 +0,0 @@
-%function stab_map_2(x,alpha2,istab,fnam)
-function stab_map_2(x,alpha2,fnam, dirname)
-% function stab_map_2(x,alpha2,fnam, dirname)
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-%global bayestopt_ estim_params_ dr_ options_ ys_ fname_
-global bayestopt_ estim_params_ options_ oo_ M_
-
-npar=size(x,2);
-ishock= npar>estim_params_.np;
-if nargin<3,
- fnam='';
-end
-if nargin<4,
- dirname='';
-end
-
-ys_ = oo_.dr.ys;
-dr_ = oo_.dr;
-fname_ = M_.fname;
-nshock = estim_params_.nvx;
-nshock = nshock + estim_params_.nvn;
-nshock = nshock + estim_params_.ncx;
-nshock = nshock + estim_params_.ncn;
-
-c0=corrcoef(x);
-c00=tril(c0,-1);
-fig_nam_=[fname_,'_',fnam,'_corr_'];
-
-ifig=0;
-j2=0;
-if ishock==0
- npar=estim_params_.np;
-else
- npar=estim_params_.np+nshock;
-end
-for j=1:npar,
- i2=find(abs(c00(:,j))>alpha2);
- if length(i2)>0,
- for jx=1:length(i2),
- j2=j2+1;
- if mod(j2,12)==1,
- ifig=ifig+1;
- figure('name',['Correlations in the ',fnam,' sample ', num2str(ifig)]),
- end
- subplot(3,4,j2-(ifig-1)*12)
- % bar(c0(i2,j)),
- % set(gca,'xticklabel',bayestopt_.name(i2)),
- % set(gca,'xtick',[1:length(i2)])
- %plot(stock_par(ixx(nfilt+1:end,i),j),stock_par(ixx(nfilt+1:end,i),i2(jx)),'.k')
- %hold on,
- plot(x(:,j),x(:,i2(jx)),'.')
- % xlabel(deblank(estim_params_.param_names(j,:)),'interpreter','none'),
- % ylabel(deblank(estim_params_.param_names(i2(jx),:)),'interpreter','none'),
- if ishock,
- xlabel(bayestopt_.name{j},'interpreter','none'),
- ylabel(bayestopt_.name{i2(jx)},'interpreter','none'),
- else
- xlabel(bayestopt_.name{j+nshock},'interpreter','none'),
- ylabel(bayestopt_.name{i2(jx)+nshock},'interpreter','none'),
- end
- title(['cc = ',num2str(c0(i2(jx),j))])
- if (mod(j2,12)==0) & j2>0,
- saveas(gcf,[dirname,'/',fig_nam_,int2str(ifig)])
- eval(['print -depsc2 ' dirname '/' fig_nam_ int2str(ifig)]);
- eval(['print -dpdf ' dirname '/' fig_nam_ int2str(ifig)]);
- if options_.nograph, close(gcf), end
- end
- end
- end
- if (j==(npar)) & j2>0,
- saveas(gcf,[dirname,'/',fig_nam_,int2str(ifig)])
- eval(['print -depsc2 ' dirname '/' fig_nam_ int2str(ifig)]);
- eval(['print -dpdf ' dirname '/' fig_nam_ int2str(ifig)]);
- if options_.nograph, close(gcf), end
- end
-
-end
-if ifig==0,
- disp(['No correlation term >', num2str(alpha2),' found for ',fnam])
-end
-%close all
diff --git a/GSA_distrib/4.2/stand_.m b/GSA_distrib/4.2/stand_.m
deleted file mode 100644
index fb0b3fda399b0de41d620faf17510a213f653f89..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/stand_.m
+++ /dev/null
@@ -1,25 +0,0 @@
-function [y, meany, stdy] = stand_(x)
-% STAND_ Standardise a matrix by columns
-%
-% [x,my,sy]=stand(y)
-%
-% y: Time series (column matrix)
-%
-% x: standardised equivalent of y
-% my: Vector of mean values for each column of y
-% sy: Vector of standard deviations for each column of y
-%
-% Copyright (c) 2006 by JRC, European Commission, United Kingdom
-% Author : Marco Ratto
-
-
-if nargin==0,
- return;
-end
-
-for j=1:size(x,2);
-meany(j)=mean(x(find(~isnan(x(:,j))),j));
-stdy(j)=std(x(find(~isnan(x(:,j))),j));
- y(:,j)=(x(:,j)-meany(j))./stdy(j);
-end
-% end of m-file
\ No newline at end of file
diff --git a/GSA_distrib/4.2/teff.m b/GSA_distrib/4.2/teff.m
deleted file mode 100644
index 6c33706e53cee1c495bf876b5af289e4b5b35c69..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/teff.m
+++ /dev/null
@@ -1,51 +0,0 @@
-function [yt, j0, ir, ic]=teff(T,Nsam,istable)
-%
-% [yt, j0, ir, ic]=teff(T,Nsam,istable)
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-ndim = (length(size(T)));
-if ndim==3,
-if nargin==1,
- Nsam=size(T,3);
- istable = [1:Nsam]';
-end
-tmax=max(T,[],3);
-tmin=min(T,[],3);
-[ir, ic]=(find( (tmax-tmin)>1.e-8));
-j0 = length(ir);
-yt=zeros(Nsam, j0);
-
-for j=1:j0,
- y0=squeeze(T(ir(j),ic(j),:));
- %y1=ones(size(lpmat,1),1)*NaN;
- y1=ones(Nsam,1)*NaN;
- y1(istable,1)=y0;
- yt(:,j)=y1;
-end
-
-else
-tmax=max(T,[],2);
-tmin=min(T,[],2);
-ir=(find( (tmax-tmin)>1.e-8));
-j0 = length(ir);
-yt=NaN(Nsam, j0);
-yt(istable,:)=T(ir,:)';
-
-
-end
-%clear y0 y1;
diff --git a/GSA_distrib/4.2/th_moments.m b/GSA_distrib/4.2/th_moments.m
deleted file mode 100644
index 41bb18d7865567efefa2f466a988751683601fb1..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/th_moments.m
+++ /dev/null
@@ -1,66 +0,0 @@
-% Copyright (C) 2001 Michel Juillard
-%
-function [vdec, corr, autocorr, z, zz] = th_moments(dr,var_list)
- global M_ oo_ options_
-
- nvar = size(var_list,1);
- if nvar == 0
- nvar = length(dr.order_var);
- ivar = [1:nvar]';
- else
- ivar=zeros(nvar,1);
- for i=1:nvar
- i_tmp = strmatch(var_list(i,:),M_.endo_names,'exact');
- if isempty(i_tmp)
- error (['One of the variable specified does not exist']) ;
- else
- ivar(i) = i_tmp;
- end
- end
- end
-
- [gamma_y,ivar] = th_autocovariances(dr,ivar,M_, options_);
- m = dr.ys(ivar);
-
-
- i1 = find(abs(diag(gamma_y{1})) > 1e-12);
- s2 = diag(gamma_y{1});
- sd = sqrt(s2);
-
-
- z = [ m sd s2 ];
- mean = m;
- var = gamma_y{1};
-
-
-%'THEORETICAL MOMENTS';
-%'MEAN','STD. DEV.','VARIANCE');
-z;
-
-%'VARIANCE DECOMPOSITION (in percent)';
-if M_.exo_nbr>1,
-vdec = 100*gamma_y{options_.ar+2}(i1,:);
-else
-vdec = 100*ones(size(gamma_y{1}(i1,1)));
-end
-%'MATRIX OF CORRELATIONS';
-if options_.opt_gsa.useautocorr,
- corr = gamma_y{1}(i1,i1)./(sd(i1)*sd(i1)');
- corr = corr-diag(diag(corr))+diag(diag(gamma_y{1}(i1,i1)));
-else
- corr = gamma_y{1}(i1,i1);
-end
- if options_.ar > 0
-%'COEFFICIENTS OF AUTOCORRELATION';
- for i=1:options_.ar
- if options_.opt_gsa.useautocorr,
- autocorr{i} = gamma_y{i+1}(i1,i1);
- else
- autocorr{i} = gamma_y{i+1}(i1,i1).*(sd(i1)*sd(i1)');
- end
- zz(:,i) = diag(gamma_y{i+1}(i1,i1));
- end
- end
-
-
-
\ No newline at end of file
diff --git a/GSA_distrib/4.2/thet2tau.m b/GSA_distrib/4.2/thet2tau.m
deleted file mode 100644
index d0a8d0ed48f2548a8dfc3a137c892c8a0f35c0db..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/thet2tau.m
+++ /dev/null
@@ -1,45 +0,0 @@
-function tau = thet2tau(params, indx, indexo, flagmoments,mf,nlags,useautocorr)
-global M_ oo_ options_
-
-if nargin==1,
- indx = [1:M_.param_nbr];
- indexo = [];
-end
-
-if nargin<4,
- flagmoments=0;
-end
-if nargin<7 | isempty(useautocorr),
- useautocorr=0;
-end
-
-M_.params(indx) = params(length(indexo)+1:end);
-if ~isempty(indexo)
- M_.Sigma_e(indexo,indexo) = diag(params(1:length(indexo)).^2);
-end
-% [A(oo_.dr.order_var,oo_.dr.order_var),B(oo_.dr.order_var,:)]=dynare_resolve;
-[A,B]=dynare_resolve;
-if flagmoments==0,
-tau = [oo_.dr.ys(oo_.dr.order_var); A(:); dyn_vech(B*M_.Sigma_e*B')];
-else
-GAM = lyapunov_symm(A,B*M_.Sigma_e*B',options_.qz_criterium,options_.lyapunov_complex_threshold);
-k = find(abs(GAM) < 1e-12);
-GAM(k) = 0;
-if useautocorr,
- sy = sqrt(diag(GAM));
- sy = sy*sy';
- sy0 = sy-diag(diag(sy))+eye(length(sy));
- dum = GAM./sy0;
- tau = dyn_vech(dum(mf,mf));
-else
- tau = dyn_vech(GAM(mf,mf));
-end
-for ii = 1:nlags
- dum = A^(ii)*GAM;
- if useautocorr,
- dum = dum./sy;
- end
- tau = [tau;vec(dum(mf,mf))];
-end
-tau = [ oo_.dr.ys(oo_.dr.order_var(mf)); tau];
-end
\ No newline at end of file
diff --git a/GSA_distrib/4.2/trank.m b/GSA_distrib/4.2/trank.m
deleted file mode 100644
index a0c5bda999a6eebdf4d1b1977f1c47240d4c111d..0000000000000000000000000000000000000000
--- a/GSA_distrib/4.2/trank.m
+++ /dev/null
@@ -1,25 +0,0 @@
-function yr = trank(y);
-% yr = trank(y);
-% yr is the rank transformation of y
-%
-% Part of the Sensitivity Analysis Toolbox for DYNARE
-%
-% Written by Marco Ratto, 2006
-% Joint Research Centre, The European Commission,
-% (http://eemc.jrc.ec.europa.eu/),
-% marco.ratto@jrc.it
-%
-% Disclaimer: This software is not subject to copyright protection and is in the public domain.
-% It is an experimental system. The Joint Research Centre of European Commission
-% assumes no responsibility whatsoever for its use by other parties
-% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
-% characteristic. We would appreciate acknowledgement if the software is used.
-% Reference:
-% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
-%
-
-[nr, nc] = size(y);
-for j=1:nc,
- [dum, is]=sort(y(:,j));
- yr(is,j)=[1:nr]'./nr;
-end