diff --git a/matlab/global_initialization.m b/matlab/global_initialization.m
index 36a42f80ae4851a5e50d0a673cadc33b24429d3c..88fa04bfaecc83960edd241123306d7c4f23c891 100644
--- a/matlab/global_initialization.m
+++ b/matlab/global_initialization.m
@@ -458,16 +458,17 @@ options_.prefilter = 0;
options_.presample = 0;
options_.prior_trunc = 1e-10;
options_.smoother = 0;
-options_.student_degrees_of_freedom = 3;
options_.posterior_max_subsample_draws = 1200;
options_.sub_draws = [];
options_.use_mh_covariance_matrix = 0;
options_.gradient_method = 2; %used by csminwel and newrat
options_.gradient_epsilon = 1e-6; %used by csminwel and newrat
options_.posterior_sampler_options = []; %extended set of options for individual posterior samplers
-options_.posterior_sampling_method = 'random_walk_metropolis_hastings';
-options_.proposal_distribution = 'rand_multivariate_normal';
-options_.student_degrees_of_freedom = 3;
+options_.posterior_sampler_options.posterior_sampling_method = 'random_walk_metropolis_hastings';
+options_.posterior_sampler_options.rwmh.proposal_distribution = 'rand_multivariate_normal';
+options_.posterior_sampler_options.rwmh.student_degrees_of_freedom = 3;
+options_.posterior_sampler_options.tarb.proposal_distribution = 'rand_multivariate_normal';
+options_.posterior_sampler_options.tarb.student_degrees_of_freedom = 3;
options_.trace_plot_ma = 200;
options_.mh_autocorrelation_function_size = 30;
options_.plot_priors = 1;
diff --git a/preprocessor/DynareBison.yy b/preprocessor/DynareBison.yy
index 0c6e7fa8682a67ae2e03d1c202609e031bd1fcc3..17bd9ed20449af746f5ab3b569ff765d94cf5dc1 100644
--- a/preprocessor/DynareBison.yy
+++ b/preprocessor/DynareBison.yy
@@ -83,14 +83,14 @@ class ParsingDriver;
#define yylex driver.lexer->lex
}
-%token AIM_SOLVER ANALYTIC_DERIVATION AR AUTOCORR TARB_MODE_COMPUTE
-%token BAYESIAN_IRF BETA_PDF BLOCK USE_CALIBRATION USE_TARB TARB_NEW_BLOCK_PROBABILITY SILENT_OPTIMIZER
+%token AIM_SOLVER ANALYTIC_DERIVATION AR AUTOCORR POSTERIOR_SAMPLING_METHOD
+%token BAYESIAN_IRF BETA_PDF BLOCK USE_CALIBRATION SILENT_OPTIMIZER
%token BVAR_DENSITY BVAR_FORECAST NODECOMPOSITION DR_DISPLAY_TOL HUGE_NUMBER
%token BVAR_PRIOR_DECAY BVAR_PRIOR_FLAT BVAR_PRIOR_LAMBDA TARB_OPTIM
%token BVAR_PRIOR_MU BVAR_PRIOR_OMEGA BVAR_PRIOR_TAU BVAR_PRIOR_TRAIN
%token BVAR_REPLIC BYTECODE ALL_VALUES_REQUIRED PROPOSAL_DISTRIBUTION
%token CALIB_SMOOTHER CHANGE_TYPE CHECK CONDITIONAL_FORECAST CONDITIONAL_FORECAST_PATHS CONF_SIG CONSTANT CONTROLLED_VAREXO CORR COVAR CUTOFF CYCLE_REDUCTION LOGARITHMIC_REDUCTION
-%token CONSIDER_ALL_ENDOGENOUS CONSIDER_ONLY_OBSERVED STUDENT_DEGREES_OF_FREEDOM
+%token CONSIDER_ALL_ENDOGENOUS CONSIDER_ONLY_OBSERVED
%token DATAFILE FILE SERIES DOUBLING DR_CYCLE_REDUCTION_TOL DR_LOGARITHMIC_REDUCTION_TOL DR_LOGARITHMIC_REDUCTION_MAXITER DR_ALGO DROP DSAMPLE DYNASAVE DYNATYPE CALIBRATION DIFFERENTIATE_FORWARD_VARS
%token END ENDVAL EQUAL ESTIMATION ESTIMATED_PARAMS ESTIMATED_PARAMS_BOUNDS ESTIMATED_PARAMS_INIT EXTENDED_PATH ENDOGENOUS_PRIOR
%token FILENAME DIRNAME FILTER_STEP_AHEAD FILTERED_VARS FIRST_OBS LAST_OBS SET_TIME
@@ -152,7 +152,7 @@ class ParsingDriver;
%token GSIG2_LMDM Q_DIAG FLAT_PRIOR NCSK NSTD WEIBULL WEIBULL_PDF
%token INDXPARR INDXOVR INDXAP APBAND INDXIMF IMFBAND INDXFORE FOREBAND INDXGFOREHAT INDXGIMFHAT
%token INDXESTIMA INDXGDLS EQ_MS FILTER_COVARIANCE FILTER_DECOMPOSITION
-%token EQ_CMS TLINDX TLNUMBER BANACT RESTRICTIONS
+%token EQ_CMS TLINDX TLNUMBER BANACT RESTRICTIONS POSTERIOR_SAMPLER_OPTIONS
%token OUTPUT_FILE_TAG DRAWS_NBR_BURN_IN_1 DRAWS_NBR_BURN_IN_2 HORIZON
%token SBVAR TREND_VAR DEFLATOR GROWTH_FACTOR MS_IRF MS_VARIANCE_DECOMPOSITION
%token MS_ESTIMATION MS_SIMULATION MS_COMPUTE_MDD MS_COMPUTE_PROBABILITIES MS_FORECAST
@@ -1757,14 +1757,12 @@ estimation_options : o_datafile
| o_distribution_approximation
| o_dirname
| o_huge_number
- | o_use_tarb
- | o_tarb_mode_compute
- | o_tarb_new_block_probability
| o_tarb_optim
| o_silent_optimizer
| o_proposal_distribution
- | o_student_degrees_of_freedom
| o_no_posterior_kernel_density
+ | o_posterior_sampling_method
+ | o_posterior_sampler_options
;
list_optim_option : QUOTED_STRING COMMA QUOTED_STRING
@@ -1787,6 +1785,16 @@ tarb_optim_options : list_tarb_optim_option
| tarb_optim_options COMMA list_tarb_optim_option;
;
+list_sampling_option : QUOTED_STRING COMMA QUOTED_STRING
+ { driver.sampling_options_string($1, $3); }
+ | QUOTED_STRING COMMA signed_number
+ { driver.sampling_options_num($1, $3); }
+ ;
+
+sampling_options : list_sampling_option
+ | sampling_options COMMA list_sampling_option;
+ ;
+
varobs : VAROBS { driver.check_varobs(); } varobs_list ';';
varobs_list : varobs_list symbol
@@ -2679,6 +2687,8 @@ o_est_first_obs : FIRST_OBS EQUAL vec_int
| FIRST_OBS EQUAL vec_int_number
{ driver.option_vec_int("first_obs", $3); }
;
+o_posterior_sampling_method : POSTERIOR_SAMPLING_METHOD EQUAL QUOTED_STRING
+ { driver.option_str("posterior_sampler_options.posterior_sampling_method", $3); } ;
o_first_obs : FIRST_OBS EQUAL INT_NUMBER { driver.option_num("first_obs", $3); };
o_data_first_obs : FIRST_OBS EQUAL date_expr { driver.option_date("firstobs", $3); } ;
o_data_last_obs : LAST_OBS EQUAL date_expr { driver.option_date("lastobs", $3); } ;
@@ -2736,11 +2746,11 @@ o_mh_drop : MH_DROP EQUAL non_negative_number { driver.option_num("mh_drop", $3)
o_mh_jscale : MH_JSCALE EQUAL non_negative_number { driver.option_num("mh_jscale", $3); };
o_optim : OPTIM EQUAL '(' optim_options ')';
o_tarb_optim : TARB_OPTIM EQUAL '(' tarb_optim_options ')';
-o_proposal_distribution : PROPOSAL_DISTRIBUTION EQUAL symbol { driver.option_str("proposal_distribution", $3); };
+o_posterior_sampler_options : POSTERIOR_SAMPLER_OPTIONS EQUAL '(' sampling_options ')' ;
+o_proposal_distribution : PROPOSAL_DISTRIBUTION EQUAL symbol { driver.option_str("posterior_sampler_options.posterior_sampling_method.proposal_distribution", $3); };
o_no_posterior_kernel_density : NO_POSTERIOR_KERNEL_DENSITY
{ driver.option_num("moments_posterior_density.indicator", "0"); }
;
-o_student_degrees_of_freedom : STUDENT_DEGREES_OF_FREEDOM EQUAL INT_NUMBER { driver.option_num("student_degrees_of_freedom", $3); };
o_mh_init_scale : MH_INIT_SCALE EQUAL non_negative_number { driver.option_num("mh_init_scale", $3); };
o_mode_file : MODE_FILE EQUAL filename { driver.option_str("mode_file", $3); };
o_mode_compute : MODE_COMPUTE EQUAL INT_NUMBER { driver.option_num("mode_compute", $3); };
@@ -2999,9 +3009,6 @@ o_equations : EQUATIONS EQUAL vec_int
| EQUATIONS EQUAL vec_int_number
{ driver.option_vec_int("ms.equations",$3); }
;
-o_use_tarb : USE_TARB { driver.option_num("TaRB.use_TaRB", "1"); };
-o_tarb_mode_compute : TARB_MODE_COMPUTE EQUAL INT_NUMBER { driver.option_num("TaRB.mode_compute", $3); };
-o_tarb_new_block_probability : TARB_NEW_BLOCK_PROBABILITY EQUAL non_negative_number {driver.option_num("TaRB.new_block_probability",$3); };
o_silent_optimizer : SILENT_OPTIMIZER { driver.option_num("silent_optimizer", "1"); };
o_instruments : INSTRUMENTS EQUAL '(' symbol_list ')' {driver.option_symbol_list("instruments"); };
diff --git a/preprocessor/DynareFlex.ll b/preprocessor/DynareFlex.ll
index 37d88361f990e93dcf629634ca8230013059770a..b395c0a99d040119511c5cbbf3a35e2cce062135 100644
--- a/preprocessor/DynareFlex.ll
+++ b/preprocessor/DynareFlex.ll
@@ -390,7 +390,6 @@ DATE -?[0-9]+([YyAa]|[Mm]([1-9]|1[0-2])|[Qq][1-4]|[Ww]([1-9]{1}|[1-4][0-9]|5[0-2
<DYNARE_STATEMENT>distribution_approximation {return token::DISTRIBUTION_APPROXIMATION;}
<DYNARE_STATEMENT>proposal_distribution {return token::PROPOSAL_DISTRIBUTION;}
<DYNARE_STATEMENT>no_posterior_kernel_density {return token::NO_POSTERIOR_KERNEL_DENSITY;}
-<DYNARE_STATEMENT>student_degrees_of_freedom {return token::STUDENT_DEGREES_OF_FREEDOM;}
<DYNARE_STATEMENT>alpha {
yylval->string_val = new string(yytext);
@@ -588,10 +587,9 @@ DATE -?[0-9]+([YyAa]|[Mm]([1-9]|1[0-2])|[Qq][1-4]|[Ww]([1-9]{1}|[1-4][0-9]|5[0-2
<DYNARE_STATEMENT>outvars {return token::OUTVARS;}
<DYNARE_STATEMENT>huge_number {return token::HUGE_NUMBER;}
<DYNARE_STATEMENT>dr_display_tol {return token::DR_DISPLAY_TOL;}
-<DYNARE_STATEMENT>use_tarb {return token::USE_TARB;}
-<DYNARE_STATEMENT>tarb_mode_compute {return token::TARB_MODE_COMPUTE;}
-<DYNARE_STATEMENT>tarb_new_block_probability {return token::TARB_NEW_BLOCK_PROBABILITY;}
+<DYNARE_STATEMENT>posterior_sampling_method {return token::POSTERIOR_SAMPLING_METHOD;}
<DYNARE_STATEMENT>tarb_optim {return token::TARB_OPTIM;}
+<DYNARE_STATEMENT>posterior_sampler_options {return token::POSTERIOR_SAMPLER_OPTIONS;}
<DYNARE_STATEMENT>silent_optimizer {return token::SILENT_OPTIMIZER;}
<DYNARE_STATEMENT>lmmcp {return token::LMMCP;}
<DYNARE_STATEMENT>occbin {return token::OCCBIN;}
diff --git a/preprocessor/ParsingDriver.cc b/preprocessor/ParsingDriver.cc
index fa23d85290a76d2b140b2e9f54bd86072d271fce..35ff72e7e450a6c562ca757681b5826e6ad1d8d4 100644
--- a/preprocessor/ParsingDriver.cc
+++ b/preprocessor/ParsingDriver.cc
@@ -1682,6 +1682,35 @@ ParsingDriver::tarb_optim_options_num(string *name, string *value)
delete value;
}
+void
+ParsingDriver::sampling_options_helper(const string &name)
+{
+ if (options_list.string_options.find("posterior_sampler_options.sampling_opt") ==
+ options_list.string_options.end())
+ options_list.string_options["posterior_sampler_options.sampling_opt"] = "";
+ else
+ options_list.string_options["posterior_sampler_options.sampling_opt"] += ",";
+ options_list.string_options["posterior_sampler_options.sampling_opt"] += "''" + name + "'',";
+}
+
+void
+ParsingDriver::sampling_options_string(string *name, string *value)
+{
+ sampling_options_helper(*name);
+ options_list.string_options["posterior_sampler_options.sampling_opt"] += "''" + *value + "''";
+ delete name;
+ delete value;
+}
+
+void
+ParsingDriver::sampling_options_num(string *name, string *value)
+{
+ sampling_options_helper(*name);
+ options_list.string_options["posterior_sampler_options.sampling_opt"] += *value;
+ delete name;
+ delete value;
+}
+
void
ParsingDriver::check_varobs()
{
diff --git a/preprocessor/ParsingDriver.hh b/preprocessor/ParsingDriver.hh
index 32096308f2879e0165f8e51c9b508dc361eaa2c4..62c8a5d09ea9ad3cd8529bfcf84d1850a5fbc500 100644
--- a/preprocessor/ParsingDriver.hh
+++ b/preprocessor/ParsingDriver.hh
@@ -99,6 +99,7 @@ private:
//! Creates option "optim_opt" in OptionsList if it doesn't exist, else add a comma, and adds the option name
void optim_options_helper(const string &name);
void tarb_optim_options_helper(const string &name);
+ void sampling_options_helper(const string &name);
//! Stores temporary symbol table
SymbolList symbol_list;
@@ -454,6 +455,10 @@ public:
void tarb_optim_options_string(string *name, string *value);
//! Adds a TaRB optimization option (numeric value)
void tarb_optim_options_num(string *name, string *value);
+ //! Adds an sampling option (string value)
+ void sampling_options_string(string *name, string *value);
+ //! Adds an sampling option (numeric value)
+ void sampling_options_num(string *name, string *value);
//! Check that no observed variable has yet be defined
void check_varobs();
//! Add a new observed variable
diff --git a/tests/estimation/MH_recover/fs2000_recover_tarb.mod b/tests/estimation/MH_recover/fs2000_recover_tarb.mod
index 9c4fca92a4feacc1c1c0f94963cebb78aedd6e23..c2ce00f6d745096faedcc4b55e799f044df9b72a 100644
--- a/tests/estimation/MH_recover/fs2000_recover_tarb.mod
+++ b/tests/estimation/MH_recover/fs2000_recover_tarb.mod
@@ -1,14 +1,14 @@
-//Test mh_recover function for RW-MH when use_tarb was also used
+//Test mh_recover function for RW-MH when posterior_sampling_method='tarb' is also used
@#include "fs2000.common.inc"
options_.MaxNumberOfBytes=10*11*8/2;
-estimation(use_tarb,order=1, datafile='../fsdat_simul',nobs=192, loglinear, mh_replic=10, mh_nblocks=2, mh_jscale=0.8);
+estimation(posterior_sampling_method='tarb',order=1, datafile='../fsdat_simul',nobs=192, loglinear, mh_replic=10, mh_nblocks=2, mh_jscale=0.8);
copyfile([M_.dname filesep 'metropolis' filesep M_.dname '_mh1_blck1.mat'],[M_.dname '_mh1_blck1.mat'])
copyfile([M_.dname filesep 'metropolis' filesep M_.dname '_mh2_blck2.mat'],[M_.dname '_mh2_blck2.mat'])
delete([M_.dname filesep 'metropolis' filesep M_.dname '_mh2_blck2.mat'])
-estimation(use_tarb,order=1, datafile='../fsdat_simul',mode_compute=0,mode_file=fs2000_recover_mode, nobs=192, loglinear, mh_replic=2000, mh_nblocks=2, mh_jscale=0.8,mh_recover);
+estimation(posterior_sampling_method='tarb',order=1, datafile='../fsdat_simul',mode_compute=0,mode_file=fs2000_recover_mode, nobs=192, loglinear, mh_replic=2000, mh_nblocks=2, mh_jscale=0.8,mh_recover);
%check first unaffected chain
temp1=load([M_.dname '_mh1_blck1.mat']);
@@ -32,4 +32,4 @@ temp2=load([M_.dname filesep 'metropolis' filesep M_.dname '_mh2_blck2.mat']);
if max(max(abs(temp1.x2-temp2.x2)))>1e-10
error('Draws of affected chain''s affected files are not the same')
-end
\ No newline at end of file
+end
diff --git a/tests/estimation/TaRB/fs2000_tarb.mod b/tests/estimation/TaRB/fs2000_tarb.mod
index 6586df19504a43808b7eb38e1fee3e77990a76c6..4c7877ff147e125bff0514e61152e9b64879e8a7 100644
--- a/tests/estimation/TaRB/fs2000_tarb.mod
+++ b/tests/estimation/TaRB/fs2000_tarb.mod
@@ -17,7 +17,7 @@
*/
/*
- * Copyright (C) 2004-2010 Dynare Team
+ * Copyright (C) 2004-2016 Dynare Team
*
* This file is part of Dynare.
*
@@ -115,8 +115,7 @@ end;
varobs gp_obs gy_obs;
estimation(order=1, datafile='../fsdat_simul',nobs=192, loglinear, mh_replic=30, mh_nblocks=2, mh_jscale=0.5,mode_compute=4,
-use_TaRB,
-tarb_mode_compute=4,
-tarb_new_block_probability=0.3,
+posterior_sampling_method='tarb',
+posterior_sampler_options=('tarb_mode_compute',4,'tarb_new_block_probability',0.3),
silent_optimizer
);