From 88e170128914c701ef652bf62922f3772b45bda9 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?St=C3=A9phane=20Adjemian=20=28Charybdis=29?=
<stephane.adjemian@univ-lemans.fr>
Date: Tue, 16 May 2017 12:42:01 +0200
Subject: [PATCH] Removed useless commas and semicolons.
---
matlab/AHessian.m | 4 +-
matlab/AIM/SPAimerr.m | 2 +-
matlab/AIM/SPAmalg.m | 6 +-
matlab/AIM/SPReduced_form.m | 2 +-
matlab/AIM_first_order_solver.m | 2 +-
matlab/GetPosteriorParametersStatistics.m | 4 +-
matlab/PlotPosteriorDistributions.m | 2 +-
matlab/PosteriorIRF.m | 18 +-
matlab/PosteriorIRF_core1.m | 18 +-
matlab/PosteriorIRF_core2.m | 12 +-
matlab/ReshapeMatFiles.m | 6 +-
matlab/UnivariateSpectralDensity.m | 2 +-
matlab/WriteShockDecomp2Excel.m | 8 +-
matlab/annualized_shock_decomposition.m | 38 +-
matlab/basic_plan.m | 2 +-
matlab/check_posterior_sampler_options.m | 34 +-
matlab/chol_SE.m | 8 +-
.../convergence_diagnostics/McMCDiagnostics.m | 12 +-
.../McMCDiagnostics_core.m | 14 +-
.../geweke_chi2_test.m | 4 +-
.../convergence_diagnostics/geweke_moments.m | 10 +-
matlab/convergence_diagnostics/mcmc_ifac.m | 2 +-
.../convergence_diagnostics/raftery_lewis.m | 26 +-
matlab/convertAimCodeToInfo.m | 2 +-
matlab/convert_oo_.m | 2 +-
matlab/cosn.m | 6 +-
matlab/csolve.m | 4 +-
matlab/discretionary_policy_engine.m | 14 +-
matlab/disp_dr.m | 2 +-
matlab/disp_identification.m | 46 +-
matlab/disp_th_moments.m | 4 +-
matlab/display_problematic_vars_Jacobian.m | 2 +-
.../inverse_gamma_specification.m | 4 +-
.../distributions/multivariate_normal_pdf.m | 2 +-
.../distributions/multivariate_student_pdf.m | 2 +-
matlab/dr_block.m | 90 +--
matlab/draw_prior_density.m | 2 +-
matlab/dsge_likelihood.m | 83 ++-
.../dsge_simulated_theoretical_correlation.m | 2 +-
...lated_theoretical_variance_decomposition.m | 2 +-
matlab/dsge_var_likelihood.m | 10 +-
matlab/dyn_autocorr.m | 2 +-
matlab/dyn_first_order_solver.m | 11 +-
matlab/dyn_ramsey_static.m | 2 +-
matlab/dyn_waitbar.m | 25 +-
matlab/dyn_waitbar_close.m | 6 +-
matlab/dynare.m | 6 +-
matlab/dynare_estimation.m | 6 +-
matlab/dynare_estimation_1.m | 29 +-
matlab/dynare_estimation_init.m | 16 +-
matlab/dynare_graph.m | 2 +-
matlab/dynare_identification.m | 149 +++--
matlab/dynare_resolve.m | 2 +-
matlab/dynare_sensitivity.m | 142 +++--
matlab/dynare_solve.m | 4 +-
matlab/dynare_solve_block_or_bytecode.m | 2 +-
matlab/dynare_squeeze.m | 2 +-
matlab/endogenous_prior_restrictions.m | 65 +-
matlab/ep/extended_path_initialization.m | 2 +-
matlab/ep/extended_path_shocks.m | 2 +-
matlab/evaluate_steady_state.m | 50 +-
matlab/evaluate_steady_state_file.m | 2 +-
matlab/fjaco.m | 2 +-
matlab/flip_plan.m | 4 +-
matlab/forecast_graphs.m | 4 +-
matlab/formdata.m | 22 +-
matlab/gensylv/gensylv.m | 4 +-
matlab/gensylv/sylvester3.m | 18 +-
matlab/gensylv/sylvester3a.m | 2 +-
matlab/gensylv_fp.m | 8 +-
matlab/getH.m | 173 +++---
matlab/getJJ.m | 26 +-
matlab/get_Hessian.m | 6 +-
matlab/get_new_or_existing_ei_index.m | 2 +-
matlab/graph_decomp.m | 12 +-
matlab/graph_decomp_detail.m | 14 +-
matlab/gsa/Morris_Measure_Groups.m | 8 +-
matlab/gsa/cumplot.m | 4 +-
matlab/gsa/filt_mc_.m | 124 ++--
matlab/gsa/gsa_plotmatrix.m | 18 +-
matlab/gsa/gsa_skewness.m | 2 +-
matlab/gsa/gsa_speed.m | 4 +-
matlab/gsa/log_trans_.m | 12 +-
matlab/gsa/map_calibration.m | 104 ++--
matlab/gsa/map_ident_.m | 105 ++--
matlab/gsa/mc_moments.m | 4 +-
matlab/gsa/mcf_analysis.m | 6 +-
matlab/gsa/myboxplot.m | 4 +-
matlab/gsa/myprctilecol.m | 6 +-
matlab/gsa/pick.m | 6 +-
matlab/gsa/redform_map.m | 120 ++--
matlab/gsa/redform_screen.m | 30 +-
matlab/gsa/scatter_analysis.m | 4 +-
matlab/gsa/scatter_mcf.m | 26 +-
matlab/gsa/scatter_plots.m | 20 +-
matlab/gsa/smirnov.m | 4 +-
matlab/gsa/stab_map_.m | 120 ++--
matlab/gsa/stab_map_1.m | 24 +-
matlab/gsa/stab_map_2.m | 32 +-
matlab/gsa/stand_.m | 6 +-
matlab/gsa/tcrit.m | 12 +-
matlab/gsa/teff.m | 6 +-
matlab/gsa/th_moments.m | 6 +-
matlab/gsa/trank.m | 4 +-
matlab/ident_bruteforce.m | 12 +-
matlab/identification_analysis.m | 53 +-
matlab/identification_checks.m | 32 +-
matlab/initial_condition_decomposition.m | 2 +-
matlab/k_order_pert.m | 8 +-
matlab/kalman/likelihood/computeDLIK.m | 26 +-
matlab/kalman/likelihood/kalman_filter.m | 34 +-
matlab/kalman/likelihood/kalman_filter_fast.m | 18 +-
matlab/kalman/likelihood/kalman_filter_ss.m | 20 +-
.../missing_observations_kalman_filter.m | 2 +-
.../likelihood/univariate_computeDLIK.m | 40 +-
.../likelihood/univariate_computeDstate.m | 14 +-
.../likelihood/univariate_kalman_filter.m | 34 +-
.../likelihood/univariate_kalman_filter_ss.m | 26 +-
matlab/lmmcp/catstruct.m | 18 +-
matlab/lnsrch1.m | 2 +-
matlab/lpdfgam.m | 2 +-
matlab/lpdfgbeta.m | 2 +-
matlab/lyapunov_solver.m | 2 +-
matlab/lyapunov_symm.m | 14 +-
matlab/marginal_density.m | 2 +-
matlab/metropolis_hastings_initialization.m | 4 +-
matlab/mh_optimal_bandwidth.m | 12 +-
matlab/missing/corrcoef/corrcoef.m | 133 ++--
.../missing/corrcoef/flag_implicit_skip_nan.m | 10 +-
matlab/missing/corrcoef/sumskipnan.m | 68 +--
matlab/missing/corrcoef/tcdf.m | 4 +-
matlab/missing/ordeig/ordeig.m | 2 +-
matlab/missing/stats/betainv.m | 2 +-
matlab/missing/stats/corr.m | 4 +-
matlab/missing/stats/gaminv.m | 2 +-
matlab/mode_check.m | 12 +-
matlab/model_diagnostics.m | 8 +-
matlab/model_info.m | 108 ++--
matlab/moment_function.m | 2 +-
matlab/myboxplot.m | 6 +-
matlab/mydelete.m | 6 +-
matlab/occbin/call_solve_one_constraint.m | 2 +-
matlab/occbin/call_solve_two_constraints.m | 2 +-
matlab/occbin/get_deriv.m | 2 +-
matlab/occbin/get_pq.m | 2 +-
matlab/occbin/makechart.m | 6 +-
matlab/occbin/makechart9.m | 18 +-
matlab/occbin/map_regime.m | 2 +-
matlab/occbin/mkdatap_anticipated.m | 2 +-
.../occbin/mkdatap_anticipated_2constraints.m | 2 +-
matlab/occbin/solve_no_constraint_noclear.m | 4 +-
matlab/occbin/solve_one_constraint.m | 4 +-
matlab/occbin/solve_two_constraints.m | 6 +-
matlab/occbin/tokenize.m | 2 +-
matlab/optimization/apprgrdn.m | 2 +-
matlab/optimization/cmaes.m | 46 +-
matlab/optimization/csminit1.m | 2 +-
matlab/optimization/csminwel1.m | 8 +-
.../optimization/dynare_minimize_objective.m | 4 +-
matlab/optimization/gmhmaxlik.m | 2 +-
matlab/optimization/mr_gstep.m | 10 +-
matlab/optimization/mr_hessian.m | 14 +-
matlab/optimization/newrat.m | 20 +-
.../simplex_optimization_routine.m | 2 +-
matlab/optimization/simpsa.m | 100 ++--
matlab/optimization/simpsaget.m | 2 +-
matlab/optimization/simpsaset.m | 4 +-
matlab/optimization/simulated_annealing.m | 166 ++---
matlab/optimization/solvopt.m | 566 +++++++++++++-----
matlab/optimize_prior.m | 2 +-
.../AnalyseComputationalEnvironment.m | 39 +-
matlab/parallel/GiveCPUnumber.m | 2 +-
.../InitializeComputationalEnvironment.m | 10 +-
matlab/parallel/closeSlave.m | 27 +-
matlab/parallel/distributeJobs.m | 8 +-
matlab/parallel/dynareParallelDelete.m | 10 +-
.../parallel/dynareParallelDeleteNewFiles.m | 8 +-
matlab/parallel/dynareParallelDir.m | 24 +-
matlab/parallel/dynareParallelGetFiles.m | 24 +-
matlab/parallel/dynareParallelGetNewFiles.m | 6 +-
matlab/parallel/dynareParallelListAllFiles.m | 4 +-
matlab/parallel/dynareParallelMkDir.m | 16 +-
matlab/parallel/dynareParallelRmDir.m | 28 +-
matlab/parallel/dynareParallelSendFiles.m | 32 +-
matlab/parallel/dynareParallelSnapshot.m | 4 +-
matlab/parallel/fMessageStatus.m | 4 +-
matlab/parallel/fParallel.m | 16 +-
matlab/parallel/masterParallel.m | 168 +++---
matlab/parallel/slaveParallel.m | 32 +-
matlab/parallel/storeGlobalVars.m | 4 +-
matlab/parallel/struct2local.m | 2 +-
.../partial_information/PCL_Part_info_irf.m | 2 +-
.../PCL_Part_info_moments.m | 4 +-
matlab/partial_information/PI_gensys.m | 4 +-
.../partial_information/PI_gensys_singularC.m | 5 +-
.../add_auxiliary_variables_to_steadystate.m | 4 +-
matlab/partial_information/dr1_PI.m | 4 +-
.../det_cond_forecast.m | 170 +++---
.../solve_stacked_problem.m | 2 +-
matlab/plot_identification.m | 74 +--
matlab/plot_priors.m | 4 +-
matlab/plot_shock_decomposition.m | 48 +-
matlab/pm3.m | 10 +-
matlab/pm3_core.m | 12 +-
matlab/posterior_sampler.m | 12 +-
matlab/posterior_sampler_core.m | 8 +-
matlab/posterior_sampler_initialization.m | 8 +-
matlab/prior_draw.m | 14 +-
matlab/prior_posterior_statistics.m | 20 +-
matlab/prior_posterior_statistics_core.m | 40 +-
matlab/priordens.m | 14 +-
matlab/qzdiv.m | 4 +-
matlab/realtime_shock_decomposition.m | 24 +-
matlab/reduced_rank_cholesky.m | 2 +-
matlab/resol.m | 2 +-
matlab/rotated_slice_sampler.m | 18 +-
matlab/select_from_table.m | 2 +-
matlab/set_state_space.m | 2 +-
matlab/simulated_moment_uncertainty.m | 6 +-
matlab/simulated_moments_estimation.m | 2 +-
matlab/simult_.m | 4 +-
matlab/slice_sampler.m | 12 +-
matlab/smm_objective.m | 2 +-
matlab/solve1.m | 2 +-
matlab/solve_one_boundary.m | 2 +-
matlab/solve_perfect_foresight_model.m | 2 +-
matlab/solve_two_boundaries.m | 6 +-
matlab/stoch_simul.m | 2 +-
matlab/stochastic_solvers.m | 10 +-
matlab/th_autocovariances.m | 18 +-
matlab/thet2tau.m | 16 +-
matlab/trust_region.m | 2 +-
matlab/user_has_matlab_license.m | 4 +-
matlab/utilities/dataset/lagged.m | 8 +-
matlab/utilities/dataset/quarterly2annual.m | 20 +-
matlab/utilities/graphics/colorspace.m | 44 +-
.../graphics/distinguishable_colors.m | 4 +-
matlab/ver_greater_than.m | 8 +-
matlab/ver_less_than.m | 8 +-
matlab/write_latex_parameter_table.m | 12 +-
matlab/writedata_text.m | 7 +-
241 files changed, 2638 insertions(+), 2454 deletions(-)
diff --git a/matlab/AHessian.m b/matlab/AHessian.m
index 561c380a0..87e341643 100644
--- a/matlab/AHessian.m
+++ b/matlab/AHessian.m
@@ -39,7 +39,7 @@ function [AHess, DLIK, LIK] = AHessian(T,R,Q,H,P,Y,DT,DYss,DOm,DH,DP,start,mf,ka
lik = zeros(smpl,1); % Initialization of the vector gathering the densities.
LIK = Inf; % Default value of the log likelihood.
-if nargout > 1,
+if nargout > 1
DLIK = zeros(k,1); % Initialization of the score.
end
AHess = zeros(k,k); % Initialization of the Hessian
@@ -127,7 +127,7 @@ end
end
AHess = -AHess;
-if nargout > 1,
+if nargout > 1
DLIK = DLIK/2;
end
% adding log-likelihhod constants
diff --git a/matlab/AIM/SPAimerr.m b/matlab/AIM/SPAimerr.m
index 2894a89a7..9bffb54aa 100644
--- a/matlab/AIM/SPAimerr.m
+++ b/matlab/AIM/SPAimerr.m
@@ -1,4 +1,4 @@
-function e = SPAimerr(c);
+function e = SPAimerr(c)
% e = aimerr(c);
%
% Interpret the return codes generated by the aim routines.
diff --git a/matlab/AIM/SPAmalg.m b/matlab/AIM/SPAmalg.m
index 41307b445..6da8ac524 100644
--- a/matlab/AIM/SPAmalg.m
+++ b/matlab/AIM/SPAmalg.m
@@ -66,12 +66,12 @@ bcols=neq*nlag;q=zeros(qrows,qcols);rts=zeros(qcols,1);
[h,q,iq,nexact]=SPExact_shift(h,q,iq,qrows,qcols,neq);
if (iq>qrows)
aimcode = 61;
- return;
+ return
end
[h,q,iq,nnumeric]=SPNumeric_shift(h,q,iq,qrows,qcols,neq,condn);
if (iq>qrows)
aimcode = 62;
- return;
+ return
end
[a,ia,js] = SPBuild_a(h,qcols,neq);
if (ia ~= 0)
@@ -81,7 +81,7 @@ if (ia ~= 0)
return
end
[w,rts,lgroots,flag_trouble]=SPEigensystem(a,uprbnd,min(length(js),qrows-iq+1));
- if flag_trouble==1;
+ if flag_trouble==1
disp('Problem in SPEIG');
aimcode=64;
return
diff --git a/matlab/AIM/SPReduced_form.m b/matlab/AIM/SPReduced_form.m
index 3d5c88990..79ab3711d 100644
--- a/matlab/AIM/SPReduced_form.m
+++ b/matlab/AIM/SPReduced_form.m
@@ -1,4 +1,4 @@
-function [nonsing,b] = SPReduced_form(q,qrows,qcols,bcols,neq,condn);
+function [nonsing,b] = SPReduced_form(q,qrows,qcols,bcols,neq,condn)
% [nonsing,b] = SPReduced_form(q,qrows,qcols,bcols,neq,b,condn);
%
% Compute reduced-form coefficient matrix, b.
diff --git a/matlab/AIM_first_order_solver.m b/matlab/AIM_first_order_solver.m
index fb3a99dc6..94d8e3845 100644
--- a/matlab/AIM_first_order_solver.m
+++ b/matlab/AIM_first_order_solver.m
@@ -91,7 +91,7 @@ function [dr,info]=AIM_first_order_solver(jacobia,M,dr,qz_criterium)
if nba > nsfwrd
temp = temp(nd-nba+1:nd-nsfwrd)-1-qz_criterium;
info(1) = 3;
- elseif nba < nsfwrd;
+ elseif nba < nsfwrd
temp = temp(nd-nsfwrd+1:nd-nba)-1-qz_criterium;
info(1) = 4;
end
diff --git a/matlab/GetPosteriorParametersStatistics.m b/matlab/GetPosteriorParametersStatistics.m
index a7c910621..04648ea32 100644
--- a/matlab/GetPosteriorParametersStatistics.m
+++ b/matlab/GetPosteriorParametersStatistics.m
@@ -163,7 +163,7 @@ if nvx
end
disp(sprintf(pformat,header_width,name,bayestopt_.p1(ip),post_mean,hpd_interval,...
pnames(bayestopt_.pshape(ip)+1,:),bayestopt_.p2(ip)));
- if TeX,
+ if TeX
name = deblank(M_.exo_names_tex(k,:));
TeXCore(fid,name,deblank(pnames(bayestopt_.pshape(ip)+1,:)),bayestopt_.p1(ip),...
bayestopt_.p2(ip),post_mean,sqrt(post_var),hpd_interval);
@@ -311,7 +311,7 @@ if ncn
end
disp(sprintf(pformat, header_width,name,bayestopt_.p1(ip),post_mean,hpd_interval, ...
pnames(bayestopt_.pshape(ip)+1,:),bayestopt_.p2(ip)));
- if TeX,
+ if TeX
name = ['(',deblank(M_.endo_names_tex(k1,:)) ',' deblank(M_.endo_names_tex(k2,:)),')'];
TeXCore(fid,name,deblank(pnames(bayestopt_.pshape(ip)+1,:)),bayestopt_.p1(ip),...
bayestopt_.p2(ip),post_mean,sqrt(post_var),hpd_interval);
diff --git a/matlab/PlotPosteriorDistributions.m b/matlab/PlotPosteriorDistributions.m
index d2e89ea00..4358b07e4 100644
--- a/matlab/PlotPosteriorDistributions.m
+++ b/matlab/PlotPosteriorDistributions.m
@@ -151,7 +151,7 @@ for i=1:npar
title(nam,'Interpreter','none');
hold off;
drawnow
- if subplotnum == MaxNumberOfPlotPerFigure || i == npar;
+ if subplotnum == MaxNumberOfPlotPerFigure || i == npar
dyn_saveas(hfig,[OutputDirectoryName '/' M_.fname '_PriorsAndPosteriors' int2str(figunumber)],options_.nodisplay,options_.graph_format);
if TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fprintf(fidTeX,'\\begin{figure}[H]\n');
diff --git a/matlab/PosteriorIRF.m b/matlab/PosteriorIRF.m
index c0d393d4e..f0764f2a3 100644
--- a/matlab/PosteriorIRF.m
+++ b/matlab/PosteriorIRF.m
@@ -178,7 +178,7 @@ if strcmpi(type,'posterior')
end
end
-if ~strcmpi(type,'prior'),
+if ~strcmpi(type,'prior')
localVars.x=x;
end
@@ -202,16 +202,16 @@ localVars.ifil2=ifil2;
localVars.MhDirectoryName=MhDirectoryName;
% Like sequential execution!
-if isnumeric(options_.parallel),
+if isnumeric(options_.parallel)
[fout] = PosteriorIRF_core1(localVars,1,B,0);
nosaddle = fout.nosaddle;
else
% Parallel execution!
[nCPU, totCPU, nBlockPerCPU] = distributeJobs(options_.parallel, 1, B);
- for j=1:totCPU-1,
+ for j=1:totCPU-1
nfiles = ceil(nBlockPerCPU(j)/MAX_nirfs_dsge);
NumberOfIRFfiles_dsge(j+1) =NumberOfIRFfiles_dsge(j)+nfiles;
- if MAX_nirfs_dsgevar,
+ if MAX_nirfs_dsgevar
nfiles = ceil(nBlockPerCPU(j)/MAX_nirfs_dsgevar);
else
nfiles=0;
@@ -236,8 +236,8 @@ else
NamFileInput(1,:) = {'',[M_.fname '_static.m']};
NamFileInput(2,:) = {'',[M_.fname '_dynamic.m']};
NamFileInput(3,:) = {'',[M_.fname '_set_auxiliary_variables.m']};
- if options_.steadystate_flag,
- if options_.steadystate_flag == 1,
+ if options_.steadystate_flag
+ if options_.steadystate_flag == 1
NamFileInput(length(NamFileInput)+1,:)={'',[M_.fname '_steadystate.m']};
else
NamFileInput(length(NamFileInput)+1,:)={'',[M_.fname '_steadystate2.m']};
@@ -245,7 +245,7 @@ else
end
[fout] = masterParallel(options_.parallel, 1, B,NamFileInput,'PosteriorIRF_core1', localVars, globalVars, options_.parallel_info);
nosaddle=0;
- for j=1:length(fout),
+ for j=1:length(fout)
nosaddle = nosaddle + fout(j).nosaddle;
end
@@ -443,11 +443,11 @@ end
% Comment for testing!
if ~isoctave
- if isnumeric(options_.parallel) || (M_.exo_nbr*ceil(size(varlist,1)/MaxNumberOfPlotPerFigure))<8,
+ if isnumeric(options_.parallel) || (M_.exo_nbr*ceil(size(varlist,1)/MaxNumberOfPlotPerFigure))<8
[fout] = PosteriorIRF_core2(localVars,1,M_.exo_nbr,0);
else
isRemoteOctave = 0;
- for indPC=1:length(options_.parallel),
+ for indPC=1:length(options_.parallel)
isRemoteOctave = isRemoteOctave + (findstr(options_.parallel(indPC).MatlabOctavePath, 'octave'));
end
if isRemoteOctave
diff --git a/matlab/PosteriorIRF_core1.m b/matlab/PosteriorIRF_core1.m
index 37f98209b..8c74eb8c2 100644
--- a/matlab/PosteriorIRF_core1.m
+++ b/matlab/PosteriorIRF_core1.m
@@ -43,7 +43,7 @@ function myoutput=PosteriorIRF_core1(myinputs,fpar,B,whoiam, ThisMatlab)
global options_ estim_params_ oo_ M_ bayestopt_ dataset_ dataset_info
-if nargin<4,
+if nargin<4
whoiam=0;
end
@@ -55,7 +55,7 @@ irun =myinputs.irun;
irun2=myinputs.irun2;
npar=myinputs.npar;
type=myinputs.type;
-if ~strcmpi(type,'prior'),
+if ~strcmpi(type,'prior')
x=myinputs.x;
end
@@ -102,7 +102,7 @@ end
RemoteFlag = 0;
if whoiam
- if Parallel(ThisMatlab).Local==0,
+ if Parallel(ThisMatlab).Local==0
RemoteFlag =1;
end
prct0={0,whoiam,Parallel(ThisMatlab)};
@@ -165,7 +165,7 @@ while fpar<B
elseif info(1) == 5
errordef = 'Rank condition is not satisfied';
end
- if strcmpi(type,'prior'),
+ if strcmpi(type,'prior')
disp(['PosteriorIRF :: Dynare is unable to solve the model (' errordef ')'])
continue
else
@@ -240,9 +240,9 @@ while fpar<B
else
stock_irf_bvardsge(:,:,:,IRUN) = reshape(tmp_dsgevar,options_.irf,dataset_.vobs,M_.exo_nbr);
instr = [MhDirectoryName '/' M_.fname '_irf_bvardsge' ...
- int2str(NumberOfIRFfiles_dsgevar) '.mat stock_irf_bvardsge;'];,
+ int2str(NumberOfIRFfiles_dsgevar) '.mat stock_irf_bvardsge;'];
eval(['save ' instr]);
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_bvardsge = [OutputFileName_bvardsge; {[MhDirectoryName filesep], [M_.fname '_irf_bvardsge' int2str(NumberOfIRFfiles_dsgevar) '.mat']}];
end
NumberOfIRFfiles_dsgevar = NumberOfIRFfiles_dsgevar+1;
@@ -259,14 +259,14 @@ while fpar<B
int2str(NumberOfIRFfiles_dsgevar) '.mat stock_irf_bvardsge;'];
eval(['save ' instr]);
NumberOfIRFfiles_dsgevar = NumberOfIRFfiles_dsgevar+1;
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_bvardsge = [OutputFileName_bvardsge; {[MhDirectoryName filesep], [M_.fname '_irf_bvardsge' int2str(NumberOfIRFfiles_dsgevar) '.mat']}];
end
irun = 0;
end
end
save([MhDirectoryName '/' M_.fname '_irf_dsge' int2str(NumberOfIRFfiles_dsge) '.mat'],'stock_irf_dsge');
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_dsge = [OutputFileName_dsge; {[MhDirectoryName filesep], [M_.fname '_irf_dsge' int2str(NumberOfIRFfiles_dsge) '.mat']}];
end
NumberOfIRFfiles_dsge = NumberOfIRFfiles_dsge+1;
@@ -278,7 +278,7 @@ while fpar<B
end
stock = stock_param;
save([MhDirectoryName '/' M_.fname '_param_irf' int2str(ifil2) '.mat'],'stock');
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_param = [OutputFileName_param; {[MhDirectoryName filesep], [M_.fname '_param_irf' int2str(ifil2) '.mat']}];
end
ifil2 = ifil2 + 1;
diff --git a/matlab/PosteriorIRF_core2.m b/matlab/PosteriorIRF_core2.m
index abf1c3cbd..9f922a409 100644
--- a/matlab/PosteriorIRF_core2.m
+++ b/matlab/PosteriorIRF_core2.m
@@ -49,7 +49,7 @@ function myoutput=PosteriorIRF_core2(myinputs,fpar,npar,whoiam,ThisMatlab)
global options_ M_
-if nargin<4,
+if nargin<4
whoiam=0;
end
@@ -85,8 +85,8 @@ end
DirectoryName = CheckPath('Output',M_.dname);
RemoteFlag = 0;
-if whoiam,
- if Parallel(ThisMatlab).Local==0,
+if whoiam
+ if Parallel(ThisMatlab).Local==0
RemoteFlag =1;
end
prct0={0,whoiam,Parallel(ThisMatlab)};
@@ -96,7 +96,7 @@ end
OutputFileName={};
subplotnum = 0;
-for i=fpar:npar,
+for i=fpar:npar
figunumber = 0;
for j=1:nvar
@@ -153,13 +153,13 @@ for i=fpar:npar,
if subplotnum == MaxNumberOfPlotPerFigure || (j == nvar && subplotnum> 0)
figunumber = figunumber+1;
dyn_saveas(hh,[DirectoryName '/' M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) '_' int2str(figunumber)],options_.nodisplay,options_.graph_format);
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName = [OutputFileName; {[DirectoryName,filesep], [M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) '_' int2str(figunumber) '.*']}];
end
subplotnum = 0;
end
end% loop over selected endo_var
- if whoiam,
+ if whoiam
fprintf('Done! \n');
waitbarString = [ 'Exog. shocks ' int2str(i) '/' int2str(npar) ' done.'];
% fMessageStatus((i-fpar+1)/(npar-fpar+1),whoiam,waitbarString, waitbarTitle, Parallel(ThisMatlab));
diff --git a/matlab/ReshapeMatFiles.m b/matlab/ReshapeMatFiles.m
index 1ad90fce1..8b6c53c06 100644
--- a/matlab/ReshapeMatFiles.m
+++ b/matlab/ReshapeMatFiles.m
@@ -44,15 +44,15 @@ function ReshapeMatFiles(type, type2)
global M_ options_
-if nargin==1,
+if nargin==1
MhDirectoryName = [ CheckPath('metropolis',M_.dname) filesep ];
else
if strcmpi(type2,'posterior')
MhDirectoryName = [CheckPath('metropolis',M_.dname) filesep ];
elseif strcmpi(type2,'gsa')
- if options_.opt_gsa.morris==1,
+ if options_.opt_gsa.morris==1
MhDirectoryName = [CheckPath('gsa/screen',M_.dname) filesep ];
- elseif options_.opt_gsa.morris==2,
+ elseif options_.opt_gsa.morris==2
MhDirectoryName = [CheckPath('gsa/identif',M_.dname) filesep ];
elseif options_.opt_gsa.pprior
MhDirectoryName = [CheckPath(['gsa' filesep 'prior'],M_.dname) filesep ];
diff --git a/matlab/UnivariateSpectralDensity.m b/matlab/UnivariateSpectralDensity.m
index ab00d1856..d5a37f24f 100644
--- a/matlab/UnivariateSpectralDensity.m
+++ b/matlab/UnivariateSpectralDensity.m
@@ -134,7 +134,7 @@ for ig = 1:ngrid
g_omega = [aa*tneg(ig) bb]*f_omega*[aa'*tpos(ig); bb']; % selected variables
f_hp = filter_gain(ig)^2*g_omega; % spectral density of selected filtered series
mathp_col(ig,:) = (f_hp(:))'; % store as matrix row
-end;
+end
f = zeros(nvar,ngrid);
for i=1:nvar
diff --git a/matlab/WriteShockDecomp2Excel.m b/matlab/WriteShockDecomp2Excel.m
index dff5c79bb..618a6b064 100644
--- a/matlab/WriteShockDecomp2Excel.m
+++ b/matlab/WriteShockDecomp2Excel.m
@@ -42,7 +42,7 @@ end
% number of components equals number of shocks + 1 (initial conditions)
comp_nbr = size(z,2)-1;
-if nargin==8 ,
+if nargin==8
if isfield(opts_decomp,'steady_state')
SteadyState = opts_decomp.steady_state;
end
@@ -84,7 +84,7 @@ end
nvar = length(i_var);
labels = char(char(shock_names),'Initial values');
-if ~(screen_shocks && comp_nbr>18),
+if ~(screen_shocks && comp_nbr>18)
screen_shocks=0;
end
comp_nbr0=comp_nbr;
@@ -92,7 +92,7 @@ comp_nbr0=comp_nbr;
for j=1:nvar
d0={};
z1 = squeeze(z(i_var(j),:,:));
- if screen_shocks,
+ if screen_shocks
[junk, isort] = sort(mean(abs(z1(1:end-2,:)')), 'descend');
labels = char(char(shock_names(isort(1:16),:)),'Others', 'Initial values');
zres = sum(z1(isort(17:end),:),1);
@@ -107,7 +107,7 @@ for j=1:nvar
d0(LastRow+2,1)={'Legend.'};
d0(LastRow+2,2)={'Shocks include:'};
d0(LastRow+3:LastRow+3+comp_nbr-1,1)=cellstr(labels(1:comp_nbr,:));
- for ic=1:comp_nbr,
+ for ic=1:comp_nbr
group_members = shock_groups.(shock_ind{ic}).shocks;
d0(LastRow+2+ic,2:1+length(group_members))=group_members;
end
diff --git a/matlab/annualized_shock_decomposition.m b/matlab/annualized_shock_decomposition.m
index 9590699b3..f5ee9c8e6 100644
--- a/matlab/annualized_shock_decomposition.m
+++ b/matlab/annualized_shock_decomposition.m
@@ -75,7 +75,7 @@ if isfield(q2a,'name')
if isfield(q2a,'tex_name')
mytex = q2a.tex_name;
end
- if mytype==2,
+ if mytype==2
gtxt = ['PHI' mytxt]; % inflation rate
gtex = ['{\pi(' mytex ')}'];
elseif mytype
@@ -101,7 +101,7 @@ if isstruct(aux)
end
yaux=aux.y;
end
-if mytype==2,
+if mytype==2
gtxt = 'PHI'; % inflation rate
gtex = '\pi';
elseif mytype
@@ -115,7 +115,7 @@ nterms = size(z,2);
nfrcst = opts.forecast/4;
for j=1:nvar
- if j>1,
+ if j>1
endo_names = char(endo_names,[deblank(M_.endo_names(i_var(j),:)) '_A']);
endo_names_tex = char(endo_names_tex,['{' deblank(M_.endo_names_tex(i_var(j),:)) '}^A']);
gendo_names = char(gendo_names,[gtxt endo_names(j,:)]);
@@ -133,15 +133,15 @@ for j=1:nvar
gendo_names_tex = [gtex '(' deblank(endo_names_tex(j,:)) ')'];
end
end
- for k =1:nterms,
- if isstruct(aux),
+ for k =1:nterms
+ if isstruct(aux)
aux.y = squeeze(yaux(j,k,min((t0-3):-4:1):end));
end
[za(j,k,:), steady_state_a(j,1), gza(j,k,:), steady_state_ga(j,1)] = ...
quarterly2annual(squeeze(z(j,k,min((t0-3):-4:1):end)),steady_state(j),GYTREND0,var_type,islog,aux);
end
ztmp=squeeze(za(j,:,:));
- if cumfix==0,
+ if cumfix==0
zscale = sum(ztmp(1:end-1,:))./ztmp(end,:);
ztmp(1:end-1,:) = ztmp(1:end-1,:)./repmat(zscale,[nterms-1,1]);
else
@@ -149,7 +149,7 @@ for j=1:nvar
ztmp(end-1,:) = ztmp(end-1,:) + zres;
end
gztmp=squeeze(gza(j,:,:));
- if cumfix==0,
+ if cumfix==0
gscale = sum(gztmp(1:end-1,:))./ gztmp(end,:);
gztmp(1:end-1,:) = gztmp(1:end-1,:)./repmat(gscale,[nterms-1,1]);
else
@@ -160,7 +160,7 @@ for j=1:nvar
gza(j,:,:) = gztmp;
end
-if q2a.plot ==1,
+if q2a.plot ==1
z=gza;
endo_names = gendo_names;
endo_names_tex = gendo_names_tex;
@@ -176,9 +176,9 @@ end
% end
% realtime
-if realtime_ && isstruct(oo_) && isfield(oo_, 'realtime_shock_decomposition'),
+if realtime_ && isstruct(oo_) && isfield(oo_, 'realtime_shock_decomposition')
init=1;
-for i=t0:4:t1,
+for i=t0:4:t1
yr=floor(i/4);
za=[];
gza=[];
@@ -202,13 +202,13 @@ end
% z = z(i_var,:,:);
for j=1:nvar
- for k =nterms:-1:1,
+ for k =nterms:-1:1
% if k<nterms
% ztmp = squeeze(sum(z(j,[1:k-1,k+1:end-1],t0-4:end)));
% else
ztmp = squeeze(z(j,k,min((t0-3):-4:1):end));
% end
- if isstruct(aux),
+ if isstruct(aux)
aux.y = squeeze(yaux(j,k,min((t0-3):-4:1):end));
end
[za(j,k,:), steady_state_a(j,1), gza(j,k,:), steady_state_ga(j,1)] = ...
@@ -222,7 +222,7 @@ end
ztmp=squeeze(za(j,:,:));
- if cumfix==0,
+ if cumfix==0
zscale = sum(ztmp(1:end-1,:))./ztmp(end,:);
ztmp(1:end-1,:) = ztmp(1:end-1,:)./repmat(zscale,[nterms-1,1]);
else
@@ -231,7 +231,7 @@ end
end
gztmp=squeeze(gza(j,:,:));
- if cumfix==0,
+ if cumfix==0
gscale = sum(gztmp(1:end-1,:))./ gztmp(end,:);
gztmp(1:end-1,:) = gztmp(1:end-1,:)./repmat(gscale,[nterms-1,1]);
else
@@ -243,7 +243,7 @@ end
gza(j,:,:) = gztmp;
end
- if q2a.plot ==1,
+ if q2a.plot ==1
z=gza;
elseif q2a.plot == 2
z=za;
@@ -251,7 +251,7 @@ end
z=cat(1,za,gza);
end
- if init==1,
+ if init==1
oo_.annualized_realtime_shock_decomposition.pool = z;
else
oo_.annualized_realtime_shock_decomposition.pool(:,:,yr) = z(:,:,end-nfrcst);
@@ -272,7 +272,7 @@ end
oo_.annualized_realtime_conditional_shock_decomposition.(['yr_' int2str(yr-nfrcst)])(:,end,:) = ...
oo_.annualized_realtime_shock_decomposition.pool(:,end,yr-nfrcst:end);
if i==t1
- for my_forecast_=(nfrcst-1):-1:1,
+ for my_forecast_=(nfrcst-1):-1:1
oo_.annualized_realtime_conditional_shock_decomposition.(['yr_' int2str(yr-my_forecast_)]) = ...
oo_.annualized_realtime_shock_decomposition.pool(:,:,yr-my_forecast_:yr) - ...
oo_.annualized_realtime_forecast_shock_decomposition.(['yr_' int2str(yr-my_forecast_)])(:,:,1:my_forecast_+1);
@@ -320,12 +320,12 @@ switch realtime_
end
end
-if q2a.plot ==0,
+if q2a.plot ==0
i_var=1:2*nvar;
steady_state = [steady_state_a;steady_state_ga];
else
i_var=1:nvar;
- if q2a.plot ==1,
+ if q2a.plot ==1
steady_state = steady_state_ga;
else
steady_state = steady_state_a;
diff --git a/matlab/basic_plan.m b/matlab/basic_plan.m
index c7b4cb360..fb8847c8b 100644
--- a/matlab/basic_plan.m
+++ b/matlab/basic_plan.m
@@ -38,7 +38,7 @@ function plan = basic_plan(plan, exogenous, expectation_type, date, value)
ix = find(strcmp(exogenous, plan.exo_names));
if isempty(ix)
error(['in basic_plan the second argument ' exogenous ' is not an exogenous variable']);
- end;
+ end
sdate = length(date);
if sdate > 1
if date(1) < plan.date(1) || date(end) > plan.date(end)
diff --git a/matlab/check_posterior_sampler_options.m b/matlab/check_posterior_sampler_options.m
index 1980c0a79..199ac2369 100644
--- a/matlab/check_posterior_sampler_options.m
+++ b/matlab/check_posterior_sampler_options.m
@@ -32,11 +32,11 @@ function [posterior_sampler_options, options_] = check_posterior_sampler_options
init=0;
-if isempty(posterior_sampler_options),
+if isempty(posterior_sampler_options)
init=1;
end
-if init,
+if init
% set default options and user defined options
posterior_sampler_options.posterior_sampling_method = options_.posterior_sampler_options.posterior_sampling_method;
posterior_sampler_options.bounds = bounds;
@@ -253,7 +253,7 @@ if init,
% This will automatically trigger <rotated>
% default = []
tmp_mode = options_list{i,2};
- for j=1:size(tmp_mode,2),
+ for j=1:size(tmp_mode,2)
posterior_sampler_options.mode(j).m = tmp_mode(:,j);
end
@@ -328,7 +328,7 @@ if init,
end
end
- if any(isinf(bounds.lb)) || any(isinf(bounds.ub)),
+ if any(isinf(bounds.lb)) || any(isinf(bounds.ub))
skipline()
disp('some priors are unbounded and prior_trunc is set to zero')
error('The option "slice" is inconsistent with prior_trunc=0.')
@@ -347,21 +347,21 @@ if init,
posterior_sampler_options.W1=posterior_sampler_options.initial_step_size*(bounds.ub-bounds.lb);
- if options_.load_mh_file,
+ if options_.load_mh_file
posterior_sampler_options.slice_initialize_with_mode = 0;
else
- if ~posterior_sampler_options.slice_initialize_with_mode,
+ if ~posterior_sampler_options.slice_initialize_with_mode
posterior_sampler_options.invhess=[];
end
end
- if ~isempty(posterior_sampler_options.mode_files), % multimodal case
+ if ~isempty(posterior_sampler_options.mode_files) % multimodal case
modes = posterior_sampler_options.mode_files; % these can be also mean files from previous parallel slice chains
load(modes, 'xparams')
- if size(xparams,2)<2,
+ if size(xparams,2)<2
error(['check_posterior_sampler_options:: Variable xparams loaded in file <' modes '> has size [' int2str(size(xparams,1)) 'x' int2str(size(xparams,2)) ']: it must contain at least two columns, to allow multi-modal sampling.'])
end
- for j=1:size(xparams,2),
+ for j=1:size(xparams,2)
mode(j).m=xparams(:,j);
end
posterior_sampler_options.mode = mode;
@@ -386,7 +386,7 @@ if ~strcmp(posterior_sampler_options.posterior_sampling_method,'slice')
end
end
-if options_.load_mh_file && posterior_sampler_options.use_mh_covariance_matrix,
+if options_.load_mh_file && posterior_sampler_options.use_mh_covariance_matrix
[junk, invhess] = compute_mh_covariance_matrix;
posterior_sampler_options.invhess = invhess;
end
@@ -396,10 +396,8 @@ end
% check specific options for slice sampler
if strcmp(posterior_sampler_options.posterior_sampling_method,'slice')
invhess = posterior_sampler_options.invhess;
-
- if posterior_sampler_options.rotated,
- if isempty(posterior_sampler_options.mode_files) && isempty(posterior_sampler_options.mode), % rotated unimodal
-
+ if posterior_sampler_options.rotated
+ if isempty(posterior_sampler_options.mode_files) && isempty(posterior_sampler_options.mode) % rotated unimodal
if ~options_.cova_compute && ~(options_.load_mh_file && posterior_sampler_options.use_mh_covariance_matrix)
skipline()
disp('check_posterior_sampler_options:: I cannot start rotated slice sampler because')
@@ -419,19 +417,13 @@ if strcmp(posterior_sampler_options.posterior_sampling_method,'slice')
posterior_sampler_options.WR=sqrt(diag(D))*3;
end
else
- if ~options_.load_mh_file && ~posterior_sampler_options.slice_initialize_with_mode,
+ if ~options_.load_mh_file && ~posterior_sampler_options.slice_initialize_with_mode
posterior_sampler_options.invhess=[];
end
end
-
% needs to be re-set to zero otherwise posterior analysis is filtered
% out in dynare_estimation_1.m
options_.mh_posterior_mode_estimation = 0;
-
-
-else
-
-
end
return
diff --git a/matlab/chol_SE.m b/matlab/chol_SE.m
index 0ec5a900b..ae02493f0 100644
--- a/matlab/chol_SE.m
+++ b/matlab/chol_SE.m
@@ -293,16 +293,16 @@ function g=gersh_nested(A,j,n)
g=zeros(n,1);
for ii = j:n
- if ii == 1;
+ if ii == 1
sum_up_to_i = 0;
else
sum_up_to_i = sum(abs(A(ii,j:(ii-1))));
- end;
- if ii == n;
+ end
+ if ii == n
sum_after_i = 0;
else
sum_after_i = sum(abs(A((ii+1):n,ii)));
- end;
+ end
g(ii) = sum_up_to_i + sum_after_i- A(ii,ii);
end
end
diff --git a/matlab/convergence_diagnostics/McMCDiagnostics.m b/matlab/convergence_diagnostics/McMCDiagnostics.m
index c42467d31..769b70d35 100644
--- a/matlab/convergence_diagnostics/McMCDiagnostics.m
+++ b/matlab/convergence_diagnostics/McMCDiagnostics.m
@@ -101,7 +101,7 @@ end
my_title='MCMC Inefficiency factors per block';
IFAC_header='Parameter';
IFAC_header_tex='Parameter';
-for j=1:nblck,
+for j=1:nblck
IFAC_header = char(IFAC_header,['Block ' int2str(j)]);
IFAC_header_tex = char(IFAC_header_tex,['Block~' int2str(j)]);
end
@@ -220,7 +220,7 @@ if nblck == 1 % Brooks and Gelman tests need more than one block
end
end
- return;
+ return
end
Origin = 1000;
@@ -262,7 +262,7 @@ localVars.M_ = M_;
% Like sequential execution!
-if isnumeric(options_.parallel),
+if isnumeric(options_.parallel)
fout = McMCDiagnostics_core(localVars,1,npar,0);
UDIAG = fout.UDIAG;
clear fout
@@ -276,7 +276,7 @@ else
[fout, nBlockPerCPU, totCPU] = masterParallel(options_.parallel, 1, npar,NamFileInput,'McMCDiagnostics_core', localVars, [], options_.parallel_info);
UDIAG = fout(1).UDIAG;
- for j=2:totCPU,
+ for j=2:totCPU
UDIAG = cat(3,UDIAG ,fout(j).UDIAG);
end
end
@@ -346,7 +346,7 @@ if reste
if reste == 1
nr = 3;
nc = 1;
- elseif reste == 2;
+ elseif reste == 2
nr = 2;
nc = 3;
end
@@ -391,7 +391,7 @@ if reste
dyn_saveas(h,[ OutputFolder '/' ModelName '_udiag' int2str(pages+1)],options_.nodisplay,options_.graph_format);
if TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fprintf(fidTeX,'\\begin{figure}[H]\n');
- for jj = 1:size(NAMES,1);
+ for jj = 1:size(NAMES,1)
fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
end
fprintf(fidTeX,'\\centering \n');
diff --git a/matlab/convergence_diagnostics/McMCDiagnostics_core.m b/matlab/convergence_diagnostics/McMCDiagnostics_core.m
index af41566c9..db1673da2 100644
--- a/matlab/convergence_diagnostics/McMCDiagnostics_core.m
+++ b/matlab/convergence_diagnostics/McMCDiagnostics_core.m
@@ -50,7 +50,7 @@ function myoutput = McMCDiagnostics_core(myinputs,fpar,npar,whoiam, ThisMatlab)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-if nargin<4,
+if nargin<4
whoiam=0;
end
@@ -71,7 +71,7 @@ M_=myinputs.M_;
if whoiam
Parallel=myinputs.Parallel;
end
-if ~exist('MetropolisFolder'),
+if ~exist('MetropolisFolder')
MetropolisFolder = CheckPath('metropolis',M_.dname);
end
@@ -81,16 +81,16 @@ UDIAG = zeros(NumberOfLines,6,npar-fpar+1);
if whoiam
waitbarString = ['Please wait... McMCDiagnostics (' int2str(fpar) 'of' int2str(npar) ')...'];
- if Parallel(ThisMatlab).Local,
+ if Parallel(ThisMatlab).Local
waitbarTitle=['Local '];
else
waitbarTitle=[Parallel(ThisMatlab).ComputerName];
end
fMessageStatus(0,whoiam,waitbarString, waitbarTitle, Parallel(ThisMatlab));
end
-for j=fpar:npar,
+for j=fpar:npar
if isoctave
- if (whoiam==0),
+ if (whoiam==0)
printf(' Parameter %d... ',j);
end
else
@@ -131,13 +131,13 @@ for j=fpar:npar,
end
end
if isoctave
- if (whoiam==0),
+ if (whoiam==0)
printf('Done! \n');
end
else
fprintf('Done! \n');
end
- if whoiam,
+ if whoiam
waitbarString = [ 'Parameter ' int2str(j) '/' int2str(npar) ' done.'];
fMessageStatus((j-fpar+1)/(npar-fpar+1),whoiam,waitbarString, waitbarTitle, Parallel(ThisMatlab))
end
diff --git a/matlab/convergence_diagnostics/geweke_chi2_test.m b/matlab/convergence_diagnostics/geweke_chi2_test.m
index 7ed383139..bfd80a573 100644
--- a/matlab/convergence_diagnostics/geweke_chi2_test.m
+++ b/matlab/convergence_diagnostics/geweke_chi2_test.m
@@ -57,7 +57,7 @@ function results_struct = geweke_chi2_test(results1,results2,results_struct,opti
% based on code by James P. LeSage, who in turn
% drew on MATLAB programs written by Siddartha Chib
-for k=1:length(options.convergence.geweke.taper_steps)+1;
+for k=1:length(options.convergence.geweke.taper_steps)+1
NSE=[results1(:,3+(k-1)*2) results2(:,3+(k-1)*2)];
means=[results1(:,1) results2(:,1)];
diff_Means=means(:,1)-means(:,2);
@@ -70,5 +70,5 @@ for k=1:length(options.convergence.geweke.taper_steps)+1;
results_struct.pooled_mean(:,k) = pooled_mean;
results_struct.pooled_nse(:,k) = pooled_NSE;
results_struct.prob_chi2_test(:,k) = p;
-end;
+end
diff --git a/matlab/convergence_diagnostics/geweke_moments.m b/matlab/convergence_diagnostics/geweke_moments.m
index 242a9d550..4acf2cf19 100644
--- a/matlab/convergence_diagnostics/geweke_moments.m
+++ b/matlab/convergence_diagnostics/geweke_moments.m
@@ -64,10 +64,10 @@ n_draws_used = ns*n_groups; %effective number of draws used after rounding down
window_means= zeros(n_groups,1);
window_uncentered_variances= zeros(n_groups,1);
-for ig=1:n_groups;
+for ig=1:n_groups
window_means(ig,1)=sum(draws((ig-1)*ns+1:ig*ns,1))/ns;
window_uncentered_variances(ig,1)=sum(draws((ig-1)*ns+1:ig*ns,1).^2)/ns;
-end; %for ig
+end %for ig
total_mean=mean(window_means);
total_variance=mean(window_uncentered_variances)-total_mean^2;
@@ -88,9 +88,9 @@ results_struct.rne_iid = results_vec(1,4);
%get autocovariance of grouped means
centered_window_means=window_means-total_mean;
autocov_grouped_means=zeros(n_groups,1);
-for lag=0:n_groups-1;
+for lag=0:n_groups-1
autocov_grouped_means(lag+1)=centered_window_means(lag+1:n_groups,1)'*centered_window_means(1:n_groups-lag,1)/100;
-end;
+end
% numerical standard error with tapered autocovariance functions
for taper_index=1:length(taper_steps)
@@ -105,5 +105,5 @@ for taper_index=1:length(taper_steps)
eval(['results_struct.nse_taper_',num2str(taper),'= NSE_taper;']);
eval(['results_struct.rne_taper_',num2str(taper),'= total_variance/(n_draws_used*NSE_taper^2);']);
-end; % end of for mm loop
+end % end of for mm loop
diff --git a/matlab/convergence_diagnostics/mcmc_ifac.m b/matlab/convergence_diagnostics/mcmc_ifac.m
index 3688153f9..7537e62eb 100644
--- a/matlab/convergence_diagnostics/mcmc_ifac.m
+++ b/matlab/convergence_diagnostics/mcmc_ifac.m
@@ -54,7 +54,7 @@ function Ifac = mcmc_ifac(X, Nc)
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
Nc = floor(min(Nc, length(X)/2));
-if mod(Nc,2),
+if mod(Nc,2)
Nc=Nc-1;
end
AcorrXSIM = dyn_autocorr(X(:), Nc);
diff --git a/matlab/convergence_diagnostics/raftery_lewis.m b/matlab/convergence_diagnostics/raftery_lewis.m
index c2a162d87..0b61ca9ba 100644
--- a/matlab/convergence_diagnostics/raftery_lewis.m
+++ b/matlab/convergence_diagnostics/raftery_lewis.m
@@ -85,7 +85,7 @@ for nv = 1:n_vars % big loop over variables
work = (runs(:,nv) <= quantile(runs(:,nv),q));
else
error('Quantile must be between 0 and 1');
- end;
+ end
k_thin_current_var = 1;
bic = 1;
@@ -95,7 +95,7 @@ for nv = 1:n_vars % big loop over variables
thinned_chain=work(1:k_thin_current_var:n_runs,1);
[g2, bic] = first_vs_second_order_MC_test(thinned_chain);
k_thin_current_var = k_thin_current_var+1;
- end;
+ end
k_thin_current_var = k_thin_current_var-1; %undo last step
@@ -103,7 +103,7 @@ for nv = 1:n_vars % big loop over variables
transition_matrix = zeros(2,2);
for i1 = 2:size(thinned_chain,1)
transition_matrix(thinned_chain(i1-1)+1,thinned_chain(i1)+1) = transition_matrix(thinned_chain(i1-1)+1,thinned_chain(i1)+1)+1;
- end;
+ end
alpha = transition_matrix(1,2)/(transition_matrix(1,1)+transition_matrix(1,2)); %prob of going from 1 to 2
beta = transition_matrix(2,1)/(transition_matrix(2,1)+transition_matrix(2,2)); %prob of going from 2 to 1
@@ -114,7 +114,7 @@ for nv = 1:n_vars % big loop over variables
thinned_chain=work(1:kmind:n_runs,1);
[g2, bic] = independence_chain_test(thinned_chain);
kmind = kmind+1;
- end;
+ end
m_star = log((alpha + beta)*epss/max(alpha,beta))/log(abs(1 - alpha - beta)); %equation bottom page 4
raftery_lewis.M_burn(nv) = fix((m_star+1)*k_thin_current_var);
@@ -124,7 +124,7 @@ for nv = 1:n_vars % big loop over variables
raftery_lewis.k_ind(nv) = max(fix(raftery_lewis.I_stat(nv)+1),kmind);
raftery_lewis.k_thin(nv) = k_thin_current_var;
raftery_lewis.N_total(nv)= raftery_lewis.M_burn(nv)+raftery_lewis.N_prec(nv);
-end;
+end
end
@@ -135,7 +135,7 @@ g2 = 0;
tran=zeros(2,2,2);
for t_iter=3:n_obs % count state transitions
tran(d(t_iter-2,1)+1,d(t_iter-1,1)+1,d(t_iter,1)+1)=tran(d(t_iter-2,1)+1,d(t_iter-1,1)+1,d(t_iter,1)+1)+1;
-end;
+end
% Compute the log likelihood ratio statistic for second-order MC vs first-order MC. G2 statistic of Bishop, Fienberg and Holland (1975)
for ind_1 = 1:2
for ind_2 = 1:2
@@ -146,9 +146,9 @@ for ind_1 = 1:2
focus = tran(ind_1,ind_2,ind_3);
g2 = g2 + log(focus/fitted)*focus;
end
- end; % end of for i3
- end; % end of for i2
-end; % end of for i1
+ end % end of for i3
+ end % end of for i2
+end % end of for i1
g2 = g2*2;
bic = g2 - log(n_obs-2)*2;
@@ -161,7 +161,7 @@ n_obs=size(d,1);
trans = zeros(2,2);
for ind_1 = 2:n_obs
trans(d(ind_1-1)+1,d(ind_1)+1)=trans(d(ind_1-1)+1,d(ind_1)+1)+1;
-end;
+end
dcm1 = n_obs - 1;
g2 = 0;
% Compute the log likelihood ratio statistic for second-order MC vs first-order MC. G2 statistic of Bishop, Fienberg and Holland (1975)
@@ -171,9 +171,9 @@ for ind_1 = 1:2
fitted = ((trans(ind_1,1) + trans(ind_1,2))*(trans(1,ind_2) + trans(2,ind_2)))/dcm1;
focus = trans(ind_1,ind_2);
g2 = g2 + log(focus/fitted)*focus;
- end;
- end;
-end;
+ end
+ end
+end
g2 = g2*2;
bic = g2 - log(dcm1);
end
diff --git a/matlab/convertAimCodeToInfo.m b/matlab/convertAimCodeToInfo.m
index 2aaf05be7..159bc694c 100644
--- a/matlab/convertAimCodeToInfo.m
+++ b/matlab/convertAimCodeToInfo.m
@@ -55,7 +55,7 @@ switch aimCode
info = 161;
case 62
info = 162;
- case 63;
+ case 63
info = 163;
case 64
info = 164;
diff --git a/matlab/convert_oo_.m b/matlab/convert_oo_.m
index ef5f72280..dc358e87e 100644
--- a/matlab/convert_oo_.m
+++ b/matlab/convert_oo_.m
@@ -63,7 +63,7 @@ else
end
if strcmp(from_ver, to_ver)
- return;
+ return
end
if ver_greater_than(to_ver, from_ver)
diff --git a/matlab/cosn.m b/matlab/cosn.m
index 8fcf7fb79..adee1a45e 100644
--- a/matlab/cosn.m
+++ b/matlab/cosn.m
@@ -1,4 +1,4 @@
-function [co, b, yhat] = cosn(H);
+function [co, b, yhat] = cosn(H)
% function co = cosn(H);
% computes the cosine of the angle between the H(:,1) and its
@@ -28,11 +28,11 @@ y = H(:,1);
X = H(:,2:end);
b=(X\y);
-if any(isnan(b)) || any(isinf(b)),
+if any(isnan(b)) || any(isinf(b))
b=0;
end
yhat = X*b;
-if rank(yhat),
+if rank(yhat)
co = abs(y'*yhat/sqrt((y'*y)*(yhat'*yhat)));
else
co=0;
diff --git a/matlab/csolve.m b/matlab/csolve.m
index 3af47243e..b4d79229b 100644
--- a/matlab/csolve.m
+++ b/matlab/csolve.m
@@ -122,7 +122,7 @@ while ~done
factor=factor^.6;
shrink=1;
end
- if abs(lambda*(1-factor))*dxSize > .1*delta;
+ if abs(lambda*(1-factor))*dxSize > .1*delta
lambda = factor*lambda;
elseif (lambda > 0) && (factor==.6) %i.e., we've only been shrinking
lambda=-.3;
@@ -162,7 +162,7 @@ while ~done
if itct >= itmax
done=1;
rc=4;
- elseif af0<crit;
+ elseif af0<crit
done=1;
rc=0;
end
diff --git a/matlab/discretionary_policy_engine.m b/matlab/discretionary_policy_engine.m
index 154b66426..e365524df 100644
--- a/matlab/discretionary_policy_engine.m
+++ b/matlab/discretionary_policy_engine.m
@@ -239,11 +239,11 @@ function v= SylvesterDoubling (d,g,h,tol,maxit)
% to solve the Sylvester equation v = d + g v h
v = d;
-for i =1:maxit,
+for i =1:maxit
vadd = g*v*h;
v = v+vadd;
if norm (vadd,1) <= (tol*norm(v,1))
- break;
+ break
end
g = g*g;
h = h*h;
@@ -295,8 +295,8 @@ temp = [];
%First handle the i = 1 case outside the loop
-if i< n,
- if abs(h(i+1,i)) < tol,
+if i< n
+ if abs(h(i+1,i)) < tol
v(:,i)= (w - g*h(i,i))\d(:,i);
i = i+1;
else
@@ -312,10 +312,10 @@ end
%Handle the rest of the matrix with the possible exception of i=n
-while i<n,
+while i<n
b= i-1;
temp = [temp g*v(:,size(temp,2)+1:b)]; %#ok<AGROW>
- if abs(h(i+1,i)) < tol,
+ if abs(h(i+1,i)) < tol
v(:,i) = (w - g*h(i,i))\(d(:,i) + temp*h(1:b,i));
i = i+1;
else
@@ -332,7 +332,7 @@ end
%Handle the i = n case if i=n was not in a 2-2 block
-if i==n,
+if i==n
b = i-1;
temp = [temp g*v(:,size(temp,2)+1:b)];
v(:,i) = (w-g*h(i,i))\(d(:,i) + temp*h(1:b,i));
diff --git a/matlab/disp_dr.m b/matlab/disp_dr.m
index a23c8f4be..607ca066d 100644
--- a/matlab/disp_dr.m
+++ b/matlab/disp_dr.m
@@ -36,7 +36,7 @@ else
k = find(dr.kstate(:,2) <= M_.maximum_lag+1);
klag = dr.kstate(k,[1 2]);
k1 = dr.order_var;
-end;
+end
if size(var_list,1) == 0
var_list = M_.endo_names(1:M_.orig_endo_nbr, :);
diff --git a/matlab/disp_identification.m b/matlab/disp_identification.m
index 5bdb3e8e5..935b73dfc 100644
--- a/matlab/disp_identification.m
+++ b/matlab/disp_identification.m
@@ -19,7 +19,7 @@ function disp_identification(pdraws, idemodel, idemoments, name, advanced)
global options_
-if nargin < 5 || isempty(advanced),
+if nargin < 5 || isempty(advanced)
advanced=0;
end
@@ -84,16 +84,16 @@ end
disp([' ']),
-if any(idemodel.ino),
+if any(idemodel.ino)
disp('WARNING !!!')
- if SampleSize>1,
+ if SampleSize>1
disp(['The rank of H (model) is deficient for ', num2str(length(find(idemodel.ino))),' out of ',int2str(SampleSize),' MC runs!' ]),
else
disp(['The rank of H (model) is deficient!' ]),
end
skipline()
- for j=1:npar,
- if any(idemodel.ind0(:,j)==0),
+ for j=1:npar
+ if any(idemodel.ind0(:,j)==0)
pno = 100*length(find(idemodel.ind0(:,j)==0))/SampleSize;
if SampleSize>1
disp([' ',name{j},' is not identified in the model for ',num2str(pno),'% of MC runs!' ])
@@ -107,9 +107,9 @@ if any(idemodel.ino),
jmap_pair=dyn_unvech(1:npairs);
jstore=[];
skipline()
- for j=1:npairs,
+ for j=1:npairs
iweak = length(find(idemodel.jweak_pair(:,j)));
- if iweak,
+ if iweak
[jx,jy]=find(jmap_pair==j);
jstore=[jstore jx(1) jy(1)];
if SampleSize > 1
@@ -121,9 +121,9 @@ if any(idemodel.ino),
end
skipline()
- for j=1:npar,
+ for j=1:npar
iweak = length(find(idemodel.jweak(:,j)));
- if iweak && ~ismember(j,jstore),
+ if iweak && ~ismember(j,jstore)
% disp('WARNING !!!')
% disp(['Model derivatives of parameter ',name{j},' are multi-collinear (with tol = 1.e-10) for ',num2str(iweak/SampleSize*100),'% of MC runs!' ])
if SampleSize>1
@@ -157,10 +157,10 @@ if ~any(idemodel.ino) && ~any(any(idemodel.ind0==0))
skipline()
end
-if any(idemoments.ino),
+if any(idemoments.ino)
skipline()
disp('WARNING !!!')
- if SampleSize > 1,
+ if SampleSize > 1
disp(['The rank of J (moments) is deficient for ', num2str(length(find(idemoments.ino))),' out of ',int2str(SampleSize),' MC runs!' ]),
else
disp(['The rank of J (moments) is deficient!' ]),
@@ -173,8 +173,8 @@ if any(idemoments.ino),
% ifreq=find(freqno);
% disp('MOMENT RANK FAILURE DUE TO COLLINEARITY OF PARAMETERS:');
skipline()
- for j=1:npar,
- if any(idemoments.ind0(:,j)==0),
+ for j=1:npar
+ if any(idemoments.ind0(:,j)==0)
pno = 100*length(find(idemoments.ind0(:,j)==0))/SampleSize;
if SampleSize > 1
disp([' ',name{j},' is not identified by J moments for ',num2str(pno),'% of MC runs!' ])
@@ -188,9 +188,9 @@ if any(idemoments.ino),
npairs=size(idemoments.jweak_pair,2);
jmap_pair=dyn_unvech(1:npairs);
jstore=[];
- for j=1:npairs,
+ for j=1:npairs
iweak = length(find(idemoments.jweak_pair(:,j)));
- if iweak,
+ if iweak
[jx,jy]=find(jmap_pair==j);
jstore=[jstore' jx(1) jy(1)]';
if SampleSize > 1
@@ -202,12 +202,12 @@ if any(idemoments.ino),
end
skipline()
- for j=1:npar,
+ for j=1:npar
iweak = length(find(idemoments.jweak(:,j)));
- if iweak && ~ismember(j,jstore),
+ if iweak && ~ismember(j,jstore)
% disp('WARNING !!!')
% disp(['Moment derivatives of parameter ',name{j},' are multi-collinear (with tol = 1.e-10) for ',num2str(iweak/SampleSize*100),'% of MC runs!' ])
- if SampleSize > 1,
+ if SampleSize > 1
disp([name{j},' is collinear w.r.t. all other params ',num2str(iweak/SampleSize*100),'% of MC runs!' ])
else
disp([name{j},' is collinear w.r.t. all other params!' ])
@@ -266,19 +266,19 @@ end
% disp(' ')
% identificaton patterns
-if SampleSize==1 && advanced,
+if SampleSize==1 && advanced
skipline()
disp('Press ENTER to print advanced diagnostics'), pause(5),
- for j=1:size(idemoments.cosnJ,2),
+ for j=1:size(idemoments.cosnJ,2)
pax=NaN(npar,npar);
fprintf('\n')
disp(['Collinearity patterns with ', int2str(j) ,' parameter(s)'])
fprintf('%-15s [%-*s] %10s\n','Parameter',(15+1)*j,' Expl. params ','cosn')
- for i=1:npar,
+ for i=1:npar
namx='';
- for in=1:j,
+ for in=1:j
dumpindx = idemoments.pars{i,j}(in);
- if isnan(dumpindx),
+ if isnan(dumpindx)
namx=[namx ' ' sprintf('%-15s','--')];
else
namx=[namx ' ' sprintf('%-15s',name{dumpindx})];
diff --git a/matlab/disp_th_moments.m b/matlab/disp_th_moments.m
index 45d217611..b699a5156 100644
--- a/matlab/disp_th_moments.m
+++ b/matlab/disp_th_moments.m
@@ -127,7 +127,7 @@ if options_.nocorr == 0 && size(stationary_vars, 1) > 0
if options_.contemporaneous_correlation
oo_.contemporaneous_correlation = corr;
end
- if ~options_.noprint,
+ if ~options_.noprint
skipline()
if options_.order == 2
title='APPROXIMATED MATRIX OF CORRELATIONS';
@@ -153,7 +153,7 @@ if options_.ar > 0 && size(stationary_vars, 1) > 0
oo_.autocorr{i} = oo_.gamma_y{i+1};
z(:,i) = diag(oo_.gamma_y{i+1}(i1,i1));
end
- if ~options_.noprint,
+ if ~options_.noprint
skipline()
if options_.order == 2
title='APPROXIMATED COEFFICIENTS OF AUTOCORRELATION';
diff --git a/matlab/display_problematic_vars_Jacobian.m b/matlab/display_problematic_vars_Jacobian.m
index a4278208b..c302df213 100644
--- a/matlab/display_problematic_vars_Jacobian.m
+++ b/matlab/display_problematic_vars_Jacobian.m
@@ -50,7 +50,7 @@ if strcmp(type,'dynamic')
type_string='';
elseif var_row==1
type_string='lag of';
- elseif var_row==3;
+ elseif var_row==3
type_string='lead of';
end
if problemcol(ii)<=max(max(M_.lead_lag_incidence)) && var_index<=M_.orig_endo_nbr
diff --git a/matlab/distributions/inverse_gamma_specification.m b/matlab/distributions/inverse_gamma_specification.m
index c7f02a194..558fdbd7f 100644
--- a/matlab/distributions/inverse_gamma_specification.m
+++ b/matlab/distributions/inverse_gamma_specification.m
@@ -85,10 +85,10 @@ nu = [];
sigma = sqrt(sigma2);
mu2 = mu*mu;
-if type == 2; % Inverse Gamma 2
+if type == 2 % Inverse Gamma 2
nu = 2*(2+mu2/sigma2);
s = 2*mu*(1+mu2/sigma2);
-elseif type == 1; % Inverse Gamma 1
+elseif type == 1 % Inverse Gamma 1
if sigma2 < Inf
nu = sqrt(2*(2+mu2/sigma2));
if use_fzero_flag
diff --git a/matlab/distributions/multivariate_normal_pdf.m b/matlab/distributions/multivariate_normal_pdf.m
index 29feabaf6..c7dd73871 100644
--- a/matlab/distributions/multivariate_normal_pdf.m
+++ b/matlab/distributions/multivariate_normal_pdf.m
@@ -1,4 +1,4 @@
-function density = multivariate_normal_pdf(X,Mean,Sigma_upper_chol,n);
+function density = multivariate_normal_pdf(X,Mean,Sigma_upper_chol,n)
% Evaluates the density of a multivariate gaussian, with expectation Mean
% and variance Sigma_upper_chol'*Sigma_upper_chol, at X.
%
diff --git a/matlab/distributions/multivariate_student_pdf.m b/matlab/distributions/multivariate_student_pdf.m
index 3f498c673..54dadfc68 100644
--- a/matlab/distributions/multivariate_student_pdf.m
+++ b/matlab/distributions/multivariate_student_pdf.m
@@ -1,4 +1,4 @@
-function density = multivariate_student_pdf(X,Mean,Sigma_upper_chol,df);
+function density = multivariate_student_pdf(X,Mean,Sigma_upper_chol,df)
% Evaluates the density of a multivariate student, with expectation Mean,
% variance Sigma_upper_chol'*Sigma_upper_chol and degrees of freedom df, at X.
%
diff --git a/matlab/dr_block.m b/matlab/dr_block.m
index 47c20add2..b1e7f2296 100644
--- a/matlab/dr_block.m
+++ b/matlab/dr_block.m
@@ -69,13 +69,13 @@ if (isfield(M_,'block_structure'))
else
data = M_;
Size = 1;
-end;
+end
if (options_.bytecode)
[chck, zz, data]= bytecode('dynamic','evaluate', z, zx, M_.params, dr.ys, 1, data);
else
[r, data] = feval([M_.fname '_dynamic'], options_, M_, oo_, z', zx, M_.params, dr.ys, M_.maximum_lag+1, data);
chck = 0;
-end;
+end
mexErrCheck('bytecode', chck);
dr.full_rank = 1;
dr.eigval = [];
@@ -90,7 +90,7 @@ n_sv = size(dr.state_var, 2);
dr.ghx = zeros(M_.endo_nbr, length(dr.state_var));
dr.exo_var = 1:M_.exo_nbr;
dr.ghu = zeros(M_.endo_nbr, M_.exo_nbr);
-for i = 1:Size;
+for i = 1:Size
ghx = [];
indexi_0 = 0;
if (verbose)
@@ -98,7 +98,7 @@ for i = 1:Size;
disp(['Block ' int2str(i)]);
disp('-----------');
data(i)
- end;
+ end
n_pred = data(i).n_backward;
n_fwrd = data(i).n_forward;
n_both = data(i).n_mixed;
@@ -118,7 +118,7 @@ for i = 1:Size;
disp(jacob);
disp('lead_lag_incidence');
disp(lead_lag_incidence);
- end;
+ end
maximum_lag = data(i).maximum_endo_lag;
maximum_lead = data(i).maximum_endo_lead;
n = n_dynamic + n_static;
@@ -127,11 +127,11 @@ for i = 1:Size;
if task ~= 1
if block_type == 2 || block_type == 4 || block_type == 7
block_type = 8;
- end;
- end;
+ end
+ end
if maximum_lag > 0 && (n_pred > 0 || n_both > 0) && block_type ~= 1
indexi_0 = min(lead_lag_incidence(2,:));
- end;
+ end
switch block_type
case 1
%% ------------------------------------------------------------------
@@ -153,7 +153,7 @@ for i = 1:Size;
if (maximum_lag > 0 && n_pred > 0)
[indx_r, tmp1, indx_r_v] = find(M_.block_structure.block(i).lead_lag_incidence(1,:));
ghx = - B \ jacob(:,indx_r_v);
- end;
+ end
if other_endo_nbr
fx = data(i).g1_o;
% retrieves the derivatives with respect to endogenous
@@ -178,7 +178,7 @@ for i = 1:Size;
ghx_other = - B \ (fx_t * l_x + (fx_tp1 * l_x * l_x_sv) + fx_tm1 * selector_tm1);
dr.ghx(endo, :) = dr.ghx(endo, :) + ghx_other;
- end;
+ end
if exo_nbr
fu = data(i).g1_x;
@@ -194,7 +194,7 @@ for i = 1:Size;
fu_complet = zeros(n, M_.exo_nbr);
fu_complet(:,data(i).exogenous) = fu;
ghu = - B \ fu_complet;
- end;
+ end
else
exo = dr.exo_var;
if other_endo_nbr > 0
@@ -229,7 +229,7 @@ for i = 1:Size;
indx_r = find(M_.block_structure.block(i).lead_lag_incidence(3,:));
indx_c = M_.block_structure.block(i).lead_lag_incidence(3,indx_r);
ghx = - inv(jacob(indx_r, indx_c));
- end;
+ end
ghu = - inv(jacob(indx_r, indx_c)) * data(i).g1_x;
end
case 3
@@ -241,7 +241,7 @@ for i = 1:Size;
else
data(i).eigval = [];
data(i).rank = 0;
- end;
+ end
dr.eigval = [dr.eigval ; data(i).eigval];
%First order approximation
if task ~= 1
@@ -249,7 +249,7 @@ for i = 1:Size;
ghx = - jacob(1 , 1 : n_pred) / jacob(1 , n_pred + n_static + 1 : n_pred + n_static + n_pred + n_both);
else
ghx = 0;
- end;
+ end
if other_endo_nbr
fx = data(i).g1_o;
% retrieves the derivatives with respect to endogenous
@@ -274,7 +274,7 @@ for i = 1:Size;
ghx_other = - (fx_t * l_x + (fx_tp1 * l_x * l_x_sv) + fx_tm1 * selector_tm1) / jacob(1 , n_pred + 1 : n_pred + n_static + n_pred + n_both);
dr.ghx(endo, :) = dr.ghx(endo, :) + ghx_other;
- end;
+ end
if exo_nbr
fu = data(i).g1_x;
if other_endo_nbr > 0
@@ -287,7 +287,7 @@ for i = 1:Size;
exo = dr.exo_var;
else
ghu = - fu / jacob(1 , n_pred + 1 : n_pred + n_static + n_pred + n_both);
- end;
+ end
else
if other_endo_nbr > 0
l_u_sv = dr.ghu(dr.state_var,:);
@@ -311,7 +311,7 @@ for i = 1:Size;
data(i).eigval = [];
data(i).rank = 0;
full_rank = 1;
- end;
+ end
dr.full_rank = dr.full_rank && full_rank;
dr.eigval = [dr.eigval ; data(i).eigval];
case 6
@@ -322,7 +322,7 @@ for i = 1:Size;
+ n_pred + n_both) \ jacob(: , 1 : n_pred);
else
ghx = 0;
- end;
+ end
if maximum_lag > 0 && n_pred > 0
data(i).eigval = -eig(ghx(n_static+1:end,:));
data(i).rank = 0;
@@ -331,7 +331,7 @@ for i = 1:Size;
data(i).eigval = [];
data(i).rank = 0;
full_rank = 1;
- end;
+ end
dr.eigval = [dr.eigval ; data(i).eigval];
dr.full_rank = dr.full_rank && full_rank;
if task ~= 1
@@ -358,7 +358,7 @@ for i = 1:Size;
selector_tm1 = M_.block_structure.block(i).tm1;
ghx_other = - (fx_t * l_x + (fx_tp1 * l_x * l_x_sv) + fx_tm1 * selector_tm1) / jacob(: , n_pred + 1 : n_pred + n_static + n_pred + n_both);
dr.ghx(endo, :) = dr.ghx(endo, :) + ghx_other;
- end;
+ end
if exo_nbr
fu = data(i).g1_x;
if other_endo_nbr > 0
@@ -371,7 +371,7 @@ for i = 1:Size;
exo = dr.exo_var;
else
ghu = - fu / jacob(: , n_pred + 1 : n_pred + n_static + n_pred + n_both);
- end;
+ end
else
if other_endo_nbr > 0
l_u_sv = dr.ghu(dr.state_var,:);
@@ -397,7 +397,7 @@ for i = 1:Size;
data(i).eigval = [];
data(i).rank = 0;
full_rank = 1;
- end;
+ end
dr.full_rank = dr.full_rank && full_rank;
dr.eigval = [dr.eigval ; data(i).eigval];
case {5,8}
@@ -413,7 +413,7 @@ for i = 1:Size;
aa = Q'*jacob;
else
aa = jacob;
- end;
+ end
index_0m = (n_static+1:n_static+n_pred) + indexi_0 - 1;
index_0p = (n_static+n_pred+1:n) + indexi_0 - 1;
index_m = 1:(n_pred+n_both);
@@ -445,7 +445,7 @@ for i = 1:Size;
if (verbose)
disp('eigval');
disp(data(i).eigval);
- end;
+ end
if info1
if info1 == -30
% one eigenvalue is close to 0/0
@@ -468,7 +468,7 @@ for i = 1:Size;
disp(['sum eigval > 1 = ' int2str(sum(abs(data(i).eigval) > 1.)) ' nyf=' int2str(nyf) ' and dr.rank=' int2str(data(i).rank)]);
disp(['data(' int2str(i) ').eigval']);
disp(data(i).eigval);
- end;
+ end
%First order approximation
if task ~= 1
@@ -487,7 +487,7 @@ for i = 1:Size;
if nba > nyf
temp = sorted_roots(nd-nba+1:nd-nyf)-1-options_.qz_criterium;
info(1) = 3;
- elseif nba < nyf;
+ elseif nba < nyf
temp = sorted_roots(nd-nyf+1:nd-nba)-1-options_.qz_criterium;
info(1) = 4;
end
@@ -507,7 +507,7 @@ for i = 1:Size;
% condest() fails on a scalar under Octave
info(1) = 5;
info(2) = condest(Z21);
- return;
+ return
else
%gx = -inv(Z22) * Z21;
gx = - Z22 \ Z21;
@@ -520,8 +520,8 @@ for i = 1:Size;
k2 = 1:(n_fwrd+n_both);
ghx = [hx(k1,:); gx(k2(n_both+1:end),:)];
- end;
- end;
+ end
+ end
if task~= 1
%lead variables actually present in the model
@@ -533,7 +533,7 @@ for i = 1:Size;
B_static = B(:,1:n_static); % submatrix containing the derivatives w.r. to static variables
else
B_static = [];
- end;
+ end
%static variables, backward variable, mixed variables and forward variables
B_pred = B(:,n_static+1:n_static+n_pred+n_both);
B_fyd = B(:,n_static+n_pred+n_both+1:end);
@@ -549,7 +549,7 @@ for i = 1:Size;
temp = b10\(temp-b11*ghx);
ghx = [temp; ghx];
temp = [];
- end;
+ end
A_ = real([B_static C(:,j3)*gx+B_pred B_fyd]); % The state_variable of the block are located at [B_pred B_both]
@@ -558,7 +558,7 @@ for i = 1:Size;
fx = Q' * data(i).g1_o;
else
fx = data(i).g1_o;
- end;
+ end
% retrieves the derivatives with respect to endogenous
% variable belonging to previous blocks
fx_tm1 = zeros(n,other_endo_nbr);
@@ -592,21 +592,21 @@ for i = 1:Size;
ghx_other = gensylv_fp(A_, B_, C_, D_, i, options_.sylvester_fixed_point_tol);
else
[err, ghx_other] = gensylv(1, A_, B_, C_, -D_);
- end;
+ end
if options_.aim_solver ~= 1 && options_.use_qzdiv
% Necessary when using Sims' routines for QZ
ghx_other = real(ghx_other);
end
dr.ghx(endo, :) = dr.ghx(endo, :) + ghx_other;
- end;
+ end
if exo_nbr
if n_static > 0
fu = Q' * data(i).g1_x;
else
fu = data(i).g1_x;
- end;
+ end
if other_endo_nbr > 0
l_u_sv = dr.ghu(dr.state_var,:);
@@ -621,7 +621,7 @@ for i = 1:Size;
exo = dr.exo_var;
else
ghu = - A_ \ fu;
- end;
+ end
else
if other_endo_nbr > 0
l_u_sv = dr.ghu(dr.state_var,:);
@@ -633,7 +633,7 @@ for i = 1:Size;
exo = dr.exo_var;
else
ghu = [];
- end;
+ end
end
@@ -671,7 +671,7 @@ for i = 1:Size;
% end
end
end
- end;
+ end
if task ~=1
if (maximum_lag > 0 && (n_pred > 0 || n_both > 0))
sorted_col_dr_ghx = M_.block_structure.block(i).sorted_col_dr_ghx;
@@ -680,27 +680,27 @@ for i = 1:Size;
data(i).pol.i_ghx = sorted_col_dr_ghx;
else
data(i).pol.i_ghx = [];
- end;
+ end
data(i).ghu = ghu;
dr.ghu(endo, exo) = ghu;
data(i).pol.i_ghu = exo;
- end;
+ end
if (verbose)
disp('dr.ghx');
dr.ghx
disp('dr.ghu');
dr.ghu
- end;
+ end
-end;
+end
M_.block_structure.block = data ;
if (verbose)
disp('dr.ghx');
disp(real(dr.ghx));
disp('dr.ghu');
disp(real(dr.ghu));
-end;
+end
if (task == 1)
- return;
-end;
+ return
+end
diff --git a/matlab/draw_prior_density.m b/matlab/draw_prior_density.m
index 23479b404..5f4ce9b95 100644
--- a/matlab/draw_prior_density.m
+++ b/matlab/draw_prior_density.m
@@ -1,4 +1,4 @@
-function [x,f,abscissa,dens,binf,bsup] = draw_prior_density(indx,bayestopt_);
+function [x,f,abscissa,dens,binf,bsup] = draw_prior_density(indx,bayestopt_)
% Computes values of prior densities at many points (before plotting)
%
% INPUTS
diff --git a/matlab/dsge_likelihood.m b/matlab/dsge_likelihood.m
index 30bb87b5f..fc5e64295 100644
--- a/matlab/dsge_likelihood.m
+++ b/matlab/dsge_likelihood.m
@@ -167,11 +167,11 @@ if analytic_derivation && DynareOptions.loglinear
error('The analytic_derivation and loglinear options are not compatible')
end
-if nargout==1,
+if nargout==1
analytic_derivation=0;
end
-if analytic_derivation,
+if analytic_derivation
kron_flag=DynareOptions.analytic_derivation_mode;
end
@@ -186,7 +186,7 @@ if isestimation(DynareOptions) && ~isequal(DynareOptions.mode_compute,1) && any(
exit_flag = 0;
info(1) = 41;
info(4)= sum((BoundsInfo.lb(k)-xparam1(k)).^2);
- if analytic_derivation,
+ if analytic_derivation
DLIK=ones(length(xparam1),1);
end
return
@@ -199,7 +199,7 @@ if isestimation(DynareOptions) && ~isequal(DynareOptions.mode_compute,1) && any(
exit_flag = 0;
info(1) = 42;
info(4)= sum((xparam1(k)-BoundsInfo.ub(k)).^2);
- if analytic_derivation,
+ if analytic_derivation
DLIK=ones(length(xparam1),1);
end
return
@@ -274,35 +274,32 @@ if info(1)
fval = Inf;
info(4) = info(2);
exit_flag = 0;
- if analytic_derivation,
+ if analytic_derivation
DLIK=ones(length(xparam1),1);
end
-
return
else
fval = Inf;
info(4) = 0.1;
exit_flag = 0;
- if analytic_derivation,
+ if analytic_derivation
DLIK=ones(length(xparam1),1);
end
-
return
end
end
% check endogenous prior restrictions
info=endogenous_prior_restrictions(T,R,Model,DynareOptions,DynareResults);
-if info(1),
+if info(1)
fval = Inf;
info(4)=info(2);
exit_flag = 0;
- if analytic_derivation,
+ if analytic_derivation
DLIK=ones(length(xparam1),1);
end
return
end
-%
% Define a vector of indices for the observed variables. Is this really usefull?...
BayesInfo.mf = BayesInfo.mf1;
@@ -446,7 +443,7 @@ switch DynareOptions.lik_init
T,R,Q,H1,Z,mmm,pp,rr);
diffuse_periods = size(dlik,1);
end
- if isnan(dLIK),
+ if isnan(dLIK)
fval = Inf;
info(1) = 45;
info(4) = 0.1;
@@ -495,20 +492,19 @@ switch DynareOptions.lik_init
error('dsge_likelihood:: Unknown initialization approach for the Kalman filter!')
end
-if analytic_derivation,
+if analytic_derivation
offset = EstimatedParameters.nvx;
offset = offset+EstimatedParameters.nvn;
offset = offset+EstimatedParameters.ncx;
offset = offset+EstimatedParameters.ncn;
-
no_DLIK = 0;
full_Hess = analytic_derivation==2;
asy_Hess = analytic_derivation==-2;
outer_product_gradient = analytic_derivation==-1;
- if asy_Hess,
+ if asy_Hess
analytic_derivation=1;
end
- if outer_product_gradient,
+ if outer_product_gradient
analytic_derivation=1;
end
DLIK = [];
@@ -526,8 +522,7 @@ if analytic_derivation,
else
indparam=[];
end
-
- if full_Hess,
+ if full_Hess
[dum, DT, DOm, DYss, dum2, D2T, D2Om, D2Yss] = getH(A, B, EstimatedParameters, Model,DynareResults,DynareOptions,kron_flag,indparam,indexo,iv);
clear dum dum2;
else
@@ -537,15 +532,15 @@ if analytic_derivation,
DT = derivatives_info.DT(iv,iv,:);
DOm = derivatives_info.DOm(iv,iv,:);
DYss = derivatives_info.DYss(iv,:);
- if isfield(derivatives_info,'full_Hess'),
+ if isfield(derivatives_info,'full_Hess')
full_Hess = derivatives_info.full_Hess;
end
- if full_Hess,
+ if full_Hess
D2T = derivatives_info.D2T;
D2Om = derivatives_info.D2Om;
D2Yss = derivatives_info.D2Yss;
end
- if isfield(derivatives_info,'no_DLIK'),
+ if isfield(derivatives_info,'no_DLIK')
no_DLIK = derivatives_info.no_DLIK;
end
clear('derivatives_info');
@@ -554,8 +549,8 @@ if analytic_derivation,
DH=zeros([length(H),length(H),length(xparam1)]);
DQ=zeros([size(Q),length(xparam1)]);
DP=zeros([size(T),length(xparam1)]);
- if full_Hess,
- for j=1:size(D2Yss,1),
+ if full_Hess
+ for j=1:size(D2Yss,1)
tmp(j,:,:) = blkdiag(zeros(offset,offset), squeeze(D2Yss(j,:,:)));
end
D2Yss = tmp;
@@ -563,7 +558,7 @@ if analytic_derivation,
D2P=sparse(size(D2Om,1),size(D2Om,2)); %zeros([size(T),length(xparam1),length(xparam1)]);
jcount=0;
end
- if DynareOptions.lik_init==1,
+ if DynareOptions.lik_init==1
for i=1:EstimatedParameters.nvx
k =EstimatedParameters.var_exo(i,1);
DQ(k,k,i) = 2*sqrt(Q(k,k));
@@ -572,7 +567,7 @@ if analytic_derivation,
% dum(kk) = 0;
DP(:,:,i)=dum;
if full_Hess
- for j=1:i,
+ for j=1:i
jcount=jcount+1;
dum = lyapunov_symm(T,dyn_unvech(D2Om(:,jcount)),DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold,[],DynareOptions.debug);
% kk = (abs(dum) < 1e-12);
@@ -592,7 +587,7 @@ if analytic_derivation,
end
end
offset = offset + EstimatedParameters.nvn;
- if DynareOptions.lik_init==1,
+ if DynareOptions.lik_init==1
for j=1:EstimatedParameters.np
dum = lyapunov_symm(T,DT(:,:,j+offset)*Pstar*T'+T*Pstar*DT(:,:,j+offset)'+DOm(:,:,j+offset),DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold,[],DynareOptions.debug);
% kk = find(abs(dum) < 1e-12);
@@ -601,7 +596,7 @@ if analytic_derivation,
if full_Hess
DTj = DT(:,:,j+offset);
DPj = dum;
- for i=1:j+offset,
+ for i=1:j+offset
jcount=jcount+1;
DTi = DT(:,:,i);
DPi = DP(:,:,i);
@@ -616,11 +611,11 @@ if analytic_derivation,
end
end
end
- if analytic_derivation==1,
+ if analytic_derivation==1
analytic_deriv_info={analytic_derivation,DT,DYss,DOm,DH,DP,asy_Hess};
else
analytic_deriv_info={analytic_derivation,DT,DYss,DOm,DH,DP,D2T,D2Yss,D2Om,D2H,D2P};
- clear DT DYss DOm DP D2T D2Yss D2Om D2H D2P,
+ clear DT DYss DOm DP D2T D2Yss D2Om D2H D2P
end
else
analytic_deriv_info={0};
@@ -648,7 +643,6 @@ if ((kalman_algo==1) || (kalman_algo==3))% Multivariate Kalman Filter
exit_flag = 0;
return
end
-
[LIK,lik] = kalman_filter_fast(Y,diffuse_periods+1,size(Y,2), ...
a,Pstar, ...
kalman_tol, riccati_tol, ...
@@ -677,7 +671,7 @@ if ((kalman_algo==1) || (kalman_algo==3))% Multivariate Kalman Filter
T,Q,R,H,Z,mm,pp,rr,Zflag,diffuse_periods);
end
end
- if analytic_derivation,
+ if analytic_derivation
LIK1=LIK;
LIK=LIK1{1};
lik1=lik;
@@ -701,8 +695,8 @@ if ((kalman_algo==1) || (kalman_algo==3))% Multivariate Kalman Filter
else
if DynareOptions.lik_init==3
LIK = LIK + dLIK;
- if analytic_derivation==0 && nargout>3,
- if ~singular_diffuse_filter,
+ if analytic_derivation==0 && nargout>3
+ if ~singular_diffuse_filter
lik = [dlik; lik];
else
lik = [sum(dlik,2); lik];
@@ -718,7 +712,7 @@ if (kalman_algo==2) || (kalman_algo==4)
if isequal(H,0)
H1 = zeros(pp,1);
mmm = mm;
- if analytic_derivation,
+ if analytic_derivation
DH = zeros(pp,length(xparam1));
end
else
@@ -726,8 +720,8 @@ if (kalman_algo==2) || (kalman_algo==4)
H1 = diag(H);
mmm = mm;
clear('tmp')
- if analytic_derivation,
- for j=1:pp,
+ if analytic_derivation
+ for j=1:pp
tmp(j,:)=DH(j,j,:);
end
DH=tmp;
@@ -756,17 +750,16 @@ if (kalman_algo==2) || (kalman_algo==4)
end
end
end
- if analytic_derivation,
+ if analytic_derivation
analytic_deriv_info{5}=DH;
end
-
[LIK, lik] = univariate_kalman_filter(DatasetInfo.missing.aindex,DatasetInfo.missing.number_of_observations,DatasetInfo.missing.no_more_missing_observations,Y,diffuse_periods+1,size(Y,2), ...
a,Pstar, ...
DynareOptions.kalman_tol, ...
DynareOptions.riccati_tol, ...
DynareOptions.presample, ...
T,Q,R,H1,Z,mmm,pp,rr,Zflag,diffuse_periods,analytic_deriv_info{:});
- if analytic_derivation,
+ if analytic_derivation
LIK1=LIK;
LIK=LIK1{1};
lik1=lik;
@@ -774,7 +767,7 @@ if (kalman_algo==2) || (kalman_algo==4)
end
if DynareOptions.lik_init==3
LIK = LIK+dLIK;
- if analytic_derivation==0 && nargout>3,
+ if analytic_derivation==0 && nargout>3
lik = [dlik; lik];
end
end
@@ -785,12 +778,12 @@ if analytic_derivation
DLIK = LIK1{2};
% [DLIK] = score(T,R,Q,H,Pstar,Y,DT,DYss,DOm,DH,DP,start,Z,kalman_tol,riccati_tol);
end
- if full_Hess ,
+ if full_Hess
Hess = -LIK1{3};
% [Hess, DLL] = get_Hessian(T,R,Q,H,Pstar,Y,DT,DYss,DOm,DH,DP,D2T,D2Yss,D2Om,D2H,D2P,start,Z,kalman_tol,riccati_tol);
% Hess0 = getHessian(Y,T,DT,D2T, R*Q*transpose(R),DOm,D2Om,Z,DYss,D2Yss);
end
- if asy_Hess,
+ if asy_Hess
% if ~((kalman_algo==2) || (kalman_algo==4)),
% [Hess] = AHessian(T,R,Q,H,Pstar,Y,DT,DYss,DOm,DH,DP,start,Z,kalman_tol,riccati_tol);
% else
@@ -829,7 +822,7 @@ likelihood = LIK;
% 5. Adds prior if necessary
% ------------------------------------------------------------------------------
if analytic_derivation
- if full_Hess,
+ if full_Hess
[lnprior, dlnprior, d2lnprior] = priordens(xparam1,BayesInfo.pshape,BayesInfo.p6,BayesInfo.p7,BayesInfo.p3,BayesInfo.p4);
Hess = Hess - d2lnprior;
else
@@ -838,7 +831,7 @@ if analytic_derivation
if no_DLIK==0
DLIK = DLIK - dlnprior';
end
- if outer_product_gradient,
+ if outer_product_gradient
dlik = lik1{2};
dlik=[- dlnprior; dlik(start:end,:)];
Hess = dlik'*dlik;
@@ -884,7 +877,7 @@ if ~DynareOptions.kalman.keep_kalman_algo_if_singularity_is_detected
DynareOptions.kalman_algo = kalman_algo;
end
-if analytic_derivation==0 && nargout>3,
+if analytic_derivation==0 && nargout>3
lik=lik(start:end,:);
DLIK=[-lnprior; lik(:)];
end
diff --git a/matlab/dsge_simulated_theoretical_correlation.m b/matlab/dsge_simulated_theoretical_correlation.m
index 265336dbb..eded5cc80 100644
--- a/matlab/dsge_simulated_theoretical_correlation.m
+++ b/matlab/dsge_simulated_theoretical_correlation.m
@@ -126,7 +126,7 @@ for file = 1:NumberOfDrawsFiles
Correlation_array = zeros(NumberOfLinesInTheLastCorrFile,nvar,nvar,nar);
NumberOfCorrLines = NumberOfLinesInTheLastCorrFile;
CorrFileNumber = CorrFileNumber - 1;
- elseif test<0;
+ elseif test<0
Correlation_array = zeros(MaXNumberOfCorrLines,nvar,nvar,nar);
else
clear('Correlation_array');
diff --git a/matlab/dsge_simulated_theoretical_variance_decomposition.m b/matlab/dsge_simulated_theoretical_variance_decomposition.m
index a8ddadec6..491f4f148 100644
--- a/matlab/dsge_simulated_theoretical_variance_decomposition.m
+++ b/matlab/dsge_simulated_theoretical_variance_decomposition.m
@@ -150,7 +150,7 @@ for file = 1:NumberOfDrawsFiles
if ~test% Prepare the last round...
Decomposition_array = zeros(NumberOfLinesInTheLastDecompFile,nvar*nexo);
NumberOfDecompLines = NumberOfLinesInTheLastDecompFile;
- elseif test<0;
+ elseif test<0
Decomposition_array = zeros(MaXNumberOfDecompLines,nvar*nexo);
else
clear('Decomposition_array');
diff --git a/matlab/dsge_var_likelihood.m b/matlab/dsge_var_likelihood.m
index 94f8e21ac..d67dcfb84 100644
--- a/matlab/dsge_var_likelihood.m
+++ b/matlab/dsge_var_likelihood.m
@@ -108,7 +108,7 @@ if isestimation(DynareOptions) && DynareOptions.mode_compute ~= 1 && any(xparam1
exit_flag = 0;
info(1) = 41;
info(4)= sum((BoundsInfo.lb(k)-xparam1(k)).^2);
- return;
+ return
end
% Return, with endogenous penalty, if some dsge-parameters are greater than the upper bound of the prior domain.
@@ -118,7 +118,7 @@ if isestimation(DynareOptions) && DynareOptions.mode_compute ~= 1 && any(xparam1
exit_flag = 0;
info(1) = 42;
info(4) = sum((xparam1(k)-BoundsInfo.ub(k)).^2);
- return;
+ return
end
% Get the variance of each structural innovation.
@@ -137,7 +137,7 @@ Model.Sigma_e = Q;
dsge_prior_weight = Model.params(dsge_prior_weight_idx);
% Is the dsge prior proper?
-if dsge_prior_weight<(NumberOfParameters+NumberOfObservedVariables)/NumberOfObservations;
+if dsge_prior_weight<(NumberOfParameters+NumberOfObservedVariables)/NumberOfObservations
fval = Inf;
exit_flag = 0;
info(1) = 51;
@@ -239,7 +239,7 @@ if ~SIGMA_u_star_is_positive_definite
info(1) = 53;
info(4) = penalty;
exit_flag = 0;
- return;
+ return
end
if ~isinf(dsge_prior_weight)% Evaluation of the likelihood of the dsge-var model when the dsge prior weight is finite.
@@ -254,7 +254,7 @@ if ~isinf(dsge_prior_weight)% Evaluation of the likelihood of the dsge-var model
info(1) = 52;
info(4) = penalty;
exit_flag = 0;
- return;
+ return
end
SIGMA_u_tilde = SIGMA_u_tilde / (NumberOfObservations*(1+dsge_prior_weight)); %prefactor of formula (29), DS (2004)
PHI_tilde = tmp2*tmp1'; %formula (28), DS (2004)
diff --git a/matlab/dyn_autocorr.m b/matlab/dyn_autocorr.m
index 43534d7be..e4565cf45 100644
--- a/matlab/dyn_autocorr.m
+++ b/matlab/dyn_autocorr.m
@@ -35,6 +35,6 @@ acf = NaN(ar+1,1);
acf(1)=1;
m = mean(y);
sd = std(y,1);
-for i=1:ar,
+for i=1:ar
acf(i+1) = (y(i+1:end)-m)'*(y(1:end-i)-m)./((size(y,1))*sd^2);
end
diff --git a/matlab/dyn_first_order_solver.m b/matlab/dyn_first_order_solver.m
index cb5e407a8..00ae32cd2 100644
--- a/matlab/dyn_first_order_solver.m
+++ b/matlab/dyn_first_order_solver.m
@@ -244,14 +244,13 @@ else
if nba > nsfwrd
temp = temp(nd-nba+1:nd-nsfwrd)-1-DynareOptions.qz_criterium;
info(1) = 3;
- elseif nba < nsfwrd;
+ elseif nba < nsfwrd
temp = temp(nd-nsfwrd+1:nd-nba)-1-DynareOptions.qz_criterium;
info(1) = 4;
end
info(2) = temp'*temp;
return
end
-
%First order approximation
indx_stable_root = 1: (nd - nsfwrd); %=> index of stable roots
indx_explosive_root = npred + nboth + 1:nd; %=> index of explosive roots
@@ -267,7 +266,7 @@ else
% Z22 is near singular
info(1) = 5;
info(2) = -log(rc);
- return;
+ return
end
gx = -minus_gx;
% predetermined variables
@@ -285,7 +284,7 @@ if nstatic > 0
B_static = B(:,1:nstatic); % submatrix containing the derivatives w.r. to static variables
else
B_static = [];
-end;
+end
%static variables, backward variable, mixed variables and forward variables
B_pred = B(:,nstatic+1:nstatic+npred+nboth);
B_fyd = B(:,nstatic+npred+nboth+1:end);
@@ -309,12 +308,12 @@ if exo_nbr
fu = Q' * jacobia(:,innovations_idx);
else
fu = jacobia(:,innovations_idx);
- end;
+ end
ghu = - A_ \ fu;
else
ghu = [];
-end;
+end
dr.ghx = ghx;
dr.ghu = ghu;
diff --git a/matlab/dyn_ramsey_static.m b/matlab/dyn_ramsey_static.m
index 964bede38..323acb7d3 100644
--- a/matlab/dyn_ramsey_static.m
+++ b/matlab/dyn_ramsey_static.m
@@ -125,7 +125,7 @@ if options_.steadystate_flag
if any(imag(x(1:M.orig_endo_nbr))) %return with penalty
resids=1+sum(abs(imag(x(1:M.orig_endo_nbr)))); %return with penalty
steady_state=NaN(endo_nbr,1);
- return;
+ return
end
end
diff --git a/matlab/dyn_waitbar.m b/matlab/dyn_waitbar.m
index f9665c950..746b62a47 100644
--- a/matlab/dyn_waitbar.m
+++ b/matlab/dyn_waitbar.m
@@ -30,7 +30,7 @@ if iscell(prctdone)
prctdone=prctdone{1};
end
-if prctdone==0,
+if prctdone==0
init=1;
if isempty(whoiam)
whoiam=0;
@@ -38,46 +38,41 @@ if prctdone==0,
else
init=0;
end
-if nargout,
+if nargout
h=[];
end
if ~whoiam
-
- if isoctave || options_.console_mode
-
- if init,
+ if isoctave || options_.console_mode
+ if init
diary off;
running_text = varargin{1};
newString='';
- return;
- elseif nargin>2,
+ return
+ elseif nargin>2
running_text = varargin{2};
end
-
if isoctave
printf([running_text,' %3.f%% done\r'], prctdone*100);
else
s0=repmat('\b',1,length(newString));
newString=sprintf([running_text,' %3.f%% done'], prctdone*100);
fprintf([s0,'%s'],newString);
- end
-
+ end
else
- if nargout,
+ if nargout
h = waitbar(prctdone,varargin{:});
else
waitbar(prctdone,varargin{:});
end
end
-
else
- if init,
+ if init
running_text = varargin{1};
elseif nargin>2
running_text = varargin{2};
end
- if Parallel.Local,
+ if Parallel.Local
waitbarTitle=['Local '];
else
waitbarTitle=[Parallel.ComputerName];
diff --git a/matlab/dyn_waitbar_close.m b/matlab/dyn_waitbar_close.m
index 894e4c6fa..ae8ee67e4 100644
--- a/matlab/dyn_waitbar_close.m
+++ b/matlab/dyn_waitbar_close.m
@@ -22,12 +22,12 @@ function dyn_waitbar_close(h)
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
global options_
-if isoctave || options_.console_mode,
+if isoctave || options_.console_mode
clear dyn_waitbar;
- diary on,
+ diary on
fprintf('\n');
else
- close(h),
+ close(h)
end
clear dyn_waitbar;
diff --git a/matlab/dynare.m b/matlab/dynare.m
index 3ab08aef4..03616f51d 100644
--- a/matlab/dynare.m
+++ b/matlab/dynare.m
@@ -114,9 +114,9 @@ else
|| ~strcmp(upper(fname(size(fname,2)-3:size(fname,2))),'.MOD') ...
&& ~strcmp(upper(fname(size(fname,2)-3:size(fname,2))),'.DYN')
error('DYNARE: argument must be a filename with .mod or .dyn extension and must not include any other periods')
- end;
+ end
fnamelength = length(fname) - 4;
-end;
+end
if fnamelength + length('_set_auxiliary_variables') > namelengthmax()
error('The name of your MOD file is too long, please shorten it')
@@ -192,7 +192,7 @@ end
disp(result)
if ismember('onlymacro', varargin)
disp('Preprocesser stopped after macroprocessing step because of ''onlymacro'' option.');
- return;
+ return
end
% post-dynare-prerocessor-hook
diff --git a/matlab/dynare_estimation.m b/matlab/dynare_estimation.m
index 5d140bd18..cca524d64 100644
--- a/matlab/dynare_estimation.m
+++ b/matlab/dynare_estimation.m
@@ -82,7 +82,7 @@ if nnobs>1 || nfirstobs > 1
if nnobs>1
options_.nobs = nobs(i);
M_.dname = [dname '_' int2str(nobs(i))];
- elseif nfirstobs>1;
+ elseif nfirstobs>1
options_.first_obs=first_obs(i);
M_.dname = [dname '_' int2str(first_obs(i))];
end
@@ -97,7 +97,7 @@ if nnobs>1 || nfirstobs > 1
end
if nnobs>1
oo_recursive_{nobs(i)} = oo_;
- elseif nfirstobs>1;
+ elseif nfirstobs>1
oo_recursive_{first_obs(i)} = oo_;
end
end
@@ -105,7 +105,7 @@ else
dynare_estimation_1(var_list,dname);
end
-if isnumeric(options_.mode_compute) && options_.mode_compute && options_.analytic_derivation,
+if isnumeric(options_.mode_compute) && options_.mode_compute && options_.analytic_derivation
options_.analytic_derivation=analytic_derivation0;
end
diff --git a/matlab/dynare_estimation_1.m b/matlab/dynare_estimation_1.m
index 0a27271de..cd0e28c9b 100644
--- a/matlab/dynare_estimation_1.m
+++ b/matlab/dynare_estimation_1.m
@@ -202,7 +202,7 @@ if ~isequal(options_.mode_compute,0) && ~options_.mh_posterior_mode_estimation
end
end
end
- if options_.analytic_derivation,
+ if options_.analytic_derivation
options_analytic_derivation_old = options_.analytic_derivation;
options_.analytic_derivation = -1;
if ~isempty(newratflag) && newratflag~=0 %numerical hessian explicitly specified
@@ -229,13 +229,13 @@ if ~isequal(options_.mode_compute,0) && ~options_.mh_posterior_mode_estimation
end
if ~isnumeric(options_.mode_compute) || ~isequal(options_.mode_compute,6) %always already computes covariance matrix
if options_.cova_compute == 1 %user did not request covariance not to be computed
- if options_.analytic_derivation && strcmp(func2str(objective_function),'dsge_likelihood'),
+ if options_.analytic_derivation && strcmp(func2str(objective_function),'dsge_likelihood')
ana_deriv_old = options_.analytic_derivation;
options_.analytic_derivation = 2;
[junk1, junk2,junk3, junk4, hh] = feval(objective_function,xparam1, ...
dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,bounds,oo_);
options_.analytic_derivation = ana_deriv_old;
- elseif ~isnumeric(options_.mode_compute) || ~(isequal(options_.mode_compute,5) && newratflag~=1),
+ elseif ~isnumeric(options_.mode_compute) || ~(isequal(options_.mode_compute,5) && newratflag~=1)
% with flag==0, we force to use the hessian from outer product gradient of optimizer 5
if options_.hessian.use_penalized_objective
penalized_objective_function = str2func('penalty_objective_function');
@@ -258,15 +258,15 @@ if ~isequal(options_.mode_compute,0) && ~options_.mh_posterior_mode_estimation
% densitities for outer product gradient
kalman_algo0 = options_.kalman_algo;
compute_hessian = 1;
- if ~((options_.kalman_algo == 2) || (options_.kalman_algo == 4)),
+ if ~((options_.kalman_algo == 2) || (options_.kalman_algo == 4))
options_.kalman_algo=2;
- if options_.lik_init == 3,
+ if options_.lik_init == 3
options_.kalman_algo=4;
end
- elseif newratflag==0, % hh already contains outer product gradient with univariate filter
+ elseif newratflag==0 % hh already contains outer product gradient with univariate filter
compute_hessian = 0;
end
- if compute_hessian,
+ if compute_hessian
crit = options_.newrat.tolerance.f;
newratflag = newratflag>0;
hh = reshape(mr_hessian(xparam1,objective_function,fval,newratflag,crit,new_rat_hess_info,dataset_, dataset_info, options_,M_,estim_params_,bayestopt_,bounds,oo_), nx, nx);
@@ -530,14 +530,13 @@ if options_.particle.status
return
end
-if (~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.pshape ...
- > 0) && options_.load_mh_file)) ...
+if (~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.pshape> 0) && options_.load_mh_file)) ...
|| ~options_.smoother ) && options_.partial_information == 0 % to be fixed
%% ML estimation, or posterior mode without Metropolis-Hastings or Metropolis without Bayesian smoothes variables
[atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,T,R,P,PK,decomp,Trend,state_uncertainty,M_,oo_,options_,bayestopt_] = DsgeSmoother(xparam1,dataset_.nobs,transpose(dataset_.data),dataset_info.missing.aindex,dataset_info.missing.state,M_,oo_,options_,bayestopt_,estim_params_);
[oo_,yf]=store_smoother_results(M_,oo_,options_,bayestopt_,dataset_,dataset_info,atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,P,PK,decomp,Trend,state_uncertainty);
- if ~options_.nograph,
+ if ~options_.nograph
[nbplt,nr,nc,lr,lc,nstar] = pltorg(M_.exo_nbr);
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fidTeX = fopen([M_.fname '_SmoothedShocks.tex'],'w');
@@ -545,7 +544,7 @@ if (~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.psha
fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
fprintf(fidTeX,' \n');
end
- for plt = 1:nbplt,
+ for plt = 1:nbplt
fh = dyn_figure(options_.nodisplay,'Name','Smoothed shocks');
NAMES = [];
if options_.TeX, TeXNAMES = []; end
@@ -557,7 +556,7 @@ if (~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.psha
marker_string{1,1}='-r';
marker_string{2,1}='-k';
end
- for i=1:nstar0,
+ for i=1:nstar0
k = (plt-1)*nstar+i;
subplot(nr,nc,i);
plot([1 gend],[0 0],marker_string{1,1},'linewidth',.5)
@@ -699,7 +698,7 @@ if (~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.psha
fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
fprintf(fidTeX,' \n');
end
- for plt = 1:nbplt,
+ for plt = 1:nbplt
fh = dyn_figure(options_.nodisplay,'Name','Historical and smoothed variables');
NAMES = [];
if options_.TeX, TeXNAMES = []; end
@@ -711,7 +710,7 @@ if (~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.psha
marker_string{1,1}='-r';
marker_string{2,1}='--k';
end
- for i=1:nstar0,
+ for i=1:nstar0
k = (plt-1)*nstar+i;
subplot(nr,nc,i);
plot(1:gend,yf(k,:),marker_string{1,1},'linewidth',1)
@@ -745,7 +744,7 @@ if (~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.psha
dyn_saveas(fh,[M_.fname '_HistoricalAndSmoothedVariables' int2str(plt)],options_.nodisplay,options_.graph_format);
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fprintf(fidTeX,'\\begin{figure}[H]\n');
- for jj = 1:nstar0,
+ for jj = 1:nstar0
fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(jj,:)),deblank(TeXNAMES(jj,:)));
end
fprintf(fidTeX,'\\centering \n');
diff --git a/matlab/dynare_estimation_init.m b/matlab/dynare_estimation_init.m
index b8e8b4ff6..30b584ce4 100644
--- a/matlab/dynare_estimation_init.m
+++ b/matlab/dynare_estimation_init.m
@@ -474,18 +474,18 @@ else
[junk,ic] = intersect(bayestopt_.smoother_var_list,nstatic+(1:npred)');
bayestopt_.smoother_restrict_columns = ic;
[junk,bayestopt_.smoother_mf] = ismember(var_obs_index_dr, bayestopt_.smoother_var_list);
-end;
+end
-if options_.analytic_derivation,
- if options_.lik_init == 3,
+if options_.analytic_derivation
+ if options_.lik_init == 3
error('analytic derivation is incompatible with diffuse filter')
end
options_.analytic_derivation = 1;
- if ~(exist('sylvester3','file')==2),
+ if ~(exist('sylvester3','file')==2)
dynareroot = strrep(which('dynare'),'dynare.m','');
addpath([dynareroot 'gensylv'])
end
- if estim_params_.np,
+ if estim_params_.np
% check if steady state changes param values
M=M_;
M.params(estim_params_.param_vals(:,1)) = xparam1(estim_params_.nvx+estim_params_.ncx+estim_params_.nvn+estim_params_.ncn+1:end); %set parameters
@@ -497,8 +497,8 @@ if options_.analytic_derivation,
end
[tmp1, params] = evaluate_steady_state(oo_.steady_state,M,options_,oo_,steadystate_check_flag);
change_flag=any(find(params-M.params));
- if change_flag,
- skipline();
+ if change_flag
+ skipline()
if any(isnan(params))
disp('After computing the steadystate, the following parameters are still NaN: '),
disp(M.param_names(isnan(params),:))
@@ -609,7 +609,7 @@ if options_.load_results_after_load_mh
end
end
-if options_.mh_replic || options_.load_mh_file,
+if options_.mh_replic || options_.load_mh_file
[current_options, options_] = check_posterior_sampler_options([], options_, bounds);
options_.posterior_sampler_options.current_options = current_options;
end
diff --git a/matlab/dynare_graph.m b/matlab/dynare_graph.m
index 9af832f7f..c4a2a8e12 100644
--- a/matlab/dynare_graph.m
+++ b/matlab/dynare_graph.m
@@ -42,7 +42,7 @@ subplot(dyn_graph.nr,dyn_graph.nc,nplot);
line_types = dyn_graph.line_types;
line_type = line_types{1};
-for i=1:size(y,2);
+for i=1:size(y,2)
if length(line_types) > 1
line_type = line_types{i};
end
diff --git a/matlab/dynare_identification.m b/matlab/dynare_identification.m
index c84faf2c6..14ff50c79 100644
--- a/matlab/dynare_identification.m
+++ b/matlab/dynare_identification.m
@@ -78,48 +78,48 @@ end
options_ident = set_default_option(options_ident,'lik_init',1);
options_ident = set_default_option(options_ident,'analytic_derivation',1);
-if isfield(options_ident,'nograph'),
+if isfield(options_ident,'nograph')
options_.nograph=options_ident.nograph;
end
-if isfield(options_ident,'nodisplay'),
+if isfield(options_ident,'nodisplay')
options_.nodisplay=options_ident.nodisplay;
end
-if isfield(options_ident,'graph_format'),
+if isfield(options_ident,'graph_format')
options_.graph_format=options_ident.graph_format;
end
-if isfield(options_ident,'prior_trunc'),
+if isfield(options_ident,'prior_trunc')
options_.prior_trunc=options_ident.prior_trunc;
end
-if options_ident.gsa_sample_file,
+if options_ident.gsa_sample_file
GSAFolder = checkpath('gsa',M_.dname);
- if options_ident.gsa_sample_file==1,
+ if options_ident.gsa_sample_file==1
load([GSAFolder,filesep,fname_,'_prior'],'lpmat','lpmat0','istable');
- elseif options_ident.gsa_sample_file==2,
+ elseif options_ident.gsa_sample_file==2
load([GSAFolder,filesep,fname_,'_mc'],'lpmat','lpmat0','istable');
else
load([GSAFolder,filesep,options_ident.gsa_sample_file],'lpmat','lpmat0','istable');
end
- if isempty(istable),
+ if isempty(istable)
istable=1:size(lpmat,1);
end
- if ~isempty(lpmat0),
+ if ~isempty(lpmat0)
lpmatx=lpmat0(istable,:);
else
lpmatx=[];
end
pdraws0 = [lpmatx lpmat(istable,:)];
clear lpmat lpmat0 istable;
-elseif nargin==1,
+elseif nargin==1
pdraws0=[];
end
external_sample=0;
-if nargin==2 || ~isempty(pdraws0),
+if nargin==2 || ~isempty(pdraws0)
options_ident.prior_mc=size(pdraws0,1);
options_ident.load_ident_files = 0;
external_sample=1;
end
-if isempty(estim_params_),
+if isempty(estim_params_)
options_ident.prior_mc=1;
options_ident.prior_range=0;
prior_exist=0;
@@ -164,28 +164,24 @@ end
SampleSize = options_ident.prior_mc;
-if ~(exist('sylvester3','file')==2),
-
+if ~(exist('sylvester3','file')==2)
dynareroot = strrep(which('dynare'),'dynare.m','');
addpath([dynareroot 'gensylv'])
end
IdentifDirectoryName = CheckPath('identification',M_.dname);
-if prior_exist,
-
+if prior_exist
indx = [];
- if ~isempty(estim_params_.param_vals),
+ if ~isempty(estim_params_.param_vals)
indx = estim_params_.param_vals(:,1);
end
indexo=[];
if ~isempty(estim_params_.var_exo)
indexo = estim_params_.var_exo(:,1);
end
-
nparam = length(bayestopt_.name);
np = estim_params_.np;
-
- if estim_params_.nvn || estim_params_.ncn,
+ if estim_params_.nvn || estim_params_.ncn
error('Identification does not support measurement errors. Instead, define them explicitly in measurement equations in model definition.')
else
offset = estim_params_.nvx;
@@ -229,9 +225,9 @@ else
end
skipline()
-disp(['==== Identification analysis ====' ]),
+disp(['==== Identification analysis ====' ])
skipline()
-if nparam<2,
+if nparam<2
options_ident.advanced=0;
advanced = options_ident.advanced;
disp('There is only one parameter to study for identitification.')
@@ -246,10 +242,9 @@ options_ident.max_dim_cova_group = min([options_ident.max_dim_cova_group,nparam-
MaxNumberOfBytes=options_.MaxNumberOfBytes;
store_options_ident = options_ident;
-if iload <=0,
-
+if iload <=0
[I,J]=find(M_.lead_lag_incidence');
- if prior_exist,
+ if prior_exist
% if exist([fname_,'_mean.mat'],'file'),
% % disp('Testing posterior mean')
% load([fname_,'_mean'],'xparam1')
@@ -272,7 +267,7 @@ if iload <=0,
case 'calibration'
parameters_TeX = 'Calibration';
disp('Testing calibration')
- params(1,:) = get_all_parameters(estim_params_,M_);;
+ params(1,:) = get_all_parameters(estim_params_,M_);
case 'posterior_mode'
parameters_TeX = 'Posterior mode';
disp('Testing posterior mode')
@@ -311,37 +306,37 @@ if iload <=0,
end
[idehess_point, idemoments_point, idemodel_point, idelre_point, derivatives_info_point, info, options_ident] = ...
identification_analysis(params,indx,indexo,options_ident,dataset_, dataset_info, prior_exist, name_tex,1,parameters,bounds);
- if info(1)~=0,
+ if info(1)~=0
skipline()
disp('----------- ')
disp('Parameter error:')
disp(['The model does not solve for ', parameters, ' with error code info = ', int2str(info(1))]),
skipline()
- if info(1)==1,
+ if info(1)==1
disp('info==1 %! The model doesn''t determine the current variables uniquely.')
- elseif info(1)==2,
+ elseif info(1)==2
disp('info==2 %! MJDGGES returned an error code.')
- elseif info(1)==3,
+ elseif info(1)==3
disp('info==3 %! Blanchard & Kahn conditions are not satisfied: no stable equilibrium. ')
- elseif info(1)==4,
+ elseif info(1)==4
disp('info==4 %! Blanchard & Kahn conditions are not satisfied: indeterminacy. ')
- elseif info(1)==5,
+ elseif info(1)==5
disp('info==5 %! Blanchard & Kahn conditions are not satisfied: indeterminacy due to rank failure. ')
- elseif info(1)==6,
+ elseif info(1)==6
disp('info==6 %! The jacobian evaluated at the deterministic steady state is complex.')
- elseif info(1)==19,
+ elseif info(1)==19
disp('info==19 %! The steadystate routine thrown an exception (inconsistent deep parameters). ')
- elseif info(1)==20,
+ elseif info(1)==20
disp('info==20 %! Cannot find the steady state, info(2) contains the sum of square residuals (of the static equations). ')
- elseif info(1)==21,
+ elseif info(1)==21
disp('info==21 %! The steady state is complex, info(2) contains the sum of square of imaginary parts of the steady state.')
- elseif info(1)==22,
+ elseif info(1)==22
disp('info==22 %! The steady has NaNs. ')
- elseif info(1)==23,
+ elseif info(1)==23
disp('info==23 %! M_.params has been updated in the steadystate routine and has complex valued scalars. ')
- elseif info(1)==24,
+ elseif info(1)==24
disp('info==24 %! M_.params has been updated in the steadystate routine and has some NaNs. ')
- elseif info(1)==30,
+ elseif info(1)==30
disp('info==30 %! Ergodic variance can''t be computed. ')
end
disp('----------- ')
@@ -349,7 +344,7 @@ if iload <=0,
if any(bayestopt_.pshape)
disp('Try sampling up to 50 parameter sets from the prior.')
kk=0;
- while kk<50 && info(1),
+ while kk<50 && info(1)
kk=kk+1;
params = prior_draw();
[idehess_point, idemoments_point, idemodel_point, idelre_point, derivatives_info_point, info, options_ident] = ...
@@ -381,11 +376,11 @@ if iload <=0,
save([IdentifDirectoryName '/' M_.fname '_identif.mat'], 'idehess_point', 'idemoments_point','idemodel_point', 'idelre_point','store_options_ident')
save([IdentifDirectoryName '/' M_.fname '_' parameters '_identif.mat'], 'idehess_point', 'idemoments_point','idemodel_point', 'idelre_point','store_options_ident')
disp_identification(params, idemodel_point, idemoments_point, name, advanced);
- if ~options_.nograph,
+ if ~options_.nograph
plot_identification(params,idemoments_point,idehess_point,idemodel_point,idelre_point,advanced,parameters,name,IdentifDirectoryName,parameters_TeX,name_tex);
end
- if SampleSize > 1,
+ if SampleSize > 1
skipline()
disp('Monte Carlo Testing')
h = dyn_waitbar(0,'Monte Carlo identification checks ...');
@@ -399,16 +394,16 @@ if iload <=0,
iteration = 1;
pdraws = [];
end
- while iteration < SampleSize,
+ while iteration < SampleSize
loop_indx = loop_indx+1;
- if external_sample,
+ if external_sample
params = pdraws0(iteration+1,:);
else
params = prior_draw();
end
[dum1, ideJ, ideH, ideGP, dum2 , info, options_MC] = ...
identification_analysis(params,indx,indexo,options_MC,dataset_, dataset_info, prior_exist, name_tex,0,[],bounds);
- if iteration==0 && info(1)==0,
+ if iteration==0 && info(1)==0
MAX_tau = min(SampleSize,ceil(MaxNumberOfBytes/(size(ideH.siH,1)*nparam)/8));
stoH = zeros([size(ideH.siH,1),nparam,MAX_tau]);
stoJJ = zeros([size(ideJ.siJ,1),nparam,MAX_tau]);
@@ -439,7 +434,7 @@ if iload <=0,
idemoments.V = zeros(SampleSize,nparam,min(8,nparam));
delete([IdentifDirectoryName '/' M_.fname '_identif_*.mat'])
end
- if info(1)==0,
+ if info(1)==0
iteration = iteration + 1;
run_index = run_index + 1;
TAU(:,iteration)=ideH.TAU;
@@ -469,9 +464,9 @@ if iload <=0,
stoH(:,:,run_index) = ideH.siH;
stoJJ(:,:,run_index) = ideJ.siJ;
pdraws(iteration,:) = params;
- if run_index==MAX_tau || iteration==SampleSize,
+ if run_index==MAX_tau || iteration==SampleSize
file_index = file_index + 1;
- if run_index<MAX_tau,
+ if run_index<MAX_tau
stoH = stoH(:,:,1:run_index);
stoJJ = stoJJ(:,:,1:run_index);
stoLRE = stoLRE(:,:,1:run_index);
@@ -484,7 +479,7 @@ if iload <=0,
end
- if SampleSize > 1,
+ if SampleSize > 1
% if isoctave || options_.console_mode,
% console_waitbar(0,iteration/SampleSize);
% else
@@ -496,21 +491,21 @@ if iload <=0,
end
- if SampleSize > 1,
- if isoctave || options_.console_mode,
+ if SampleSize > 1
+ if isoctave || options_.console_mode
fprintf('\n');
diary on;
else
- close(h),
+ close(h)
end
normTAU=std(TAU')';
normLRE=std(LRE')';
normGAM=std(GAM')';
normaliz1=std(pdraws);
iter=0;
- for ifile_index = 1:file_index,
+ for ifile_index = 1:file_index
load([IdentifDirectoryName '/' M_.fname '_identif_' int2str(ifile_index) '.mat'], 'stoH', 'stoJJ', 'stoLRE')
- for irun=1:size(stoH,3),
+ for irun=1:size(stoH,3)
iter=iter+1;
siJnorm(iter,:) = vnorm(stoJJ(:,:,irun)./repmat(normGAM,1,nparam)).*normaliz1;
siHnorm(iter,:) = vnorm(stoH(:,:,irun)./repmat(normTAU,1,nparam)).*normaliz1;
@@ -539,12 +534,12 @@ else
options_.options_ident = options_ident;
end
-if nargout>3 && iload,
+if nargout>3 && iload
filnam = dir([IdentifDirectoryName '/' M_.fname '_identif_*.mat']);
H=[];
JJ = [];
gp = [];
- for j=1:length(filnam),
+ for j=1:length(filnam)
load([IdentifDirectoryName '/' M_.fname '_identif_',int2str(j),'.mat']);
H = cat(3,H, stoH(:,abs(iload),:));
JJ = cat(3,JJ, stoJJ(:,abs(iload),:));
@@ -553,70 +548,70 @@ if nargout>3 && iload,
end
end
-if iload,
+if iload
disp(['Testing ',parameters])
disp_identification(idehess_point.params, idemodel_point, idemoments_point, name,advanced);
- if ~options_.nograph,
+ if ~options_.nograph
plot_identification(idehess_point.params,idemoments_point,idehess_point,idemodel_point,idelre_point,advanced,parameters,name,IdentifDirectoryName,[],name_tex);
end
end
-if SampleSize > 1,
+if SampleSize > 1
fprintf('\n')
disp('Testing MC sample')
disp_identification(pdraws, idemodel, idemoments, name);
- if ~options_.nograph,
+ if ~options_.nograph
plot_identification(pdraws,idemoments,idehess_point,idemodel,idelre,advanced,'MC sample ',name, IdentifDirectoryName,[],name_tex);
end
- if advanced,
+ if advanced
jcrit=find(idemoments.ino);
- if length(jcrit)<SampleSize,
- if isempty(jcrit),
+ if length(jcrit)<SampleSize
+ if isempty(jcrit)
[dum,jmax]=max(idemoments.cond);
fprintf('\n')
tittxt = 'Draw with HIGHEST condition number';
fprintf('\n')
disp(['Testing ',tittxt, '. Press ENTER']), pause(5),
- if ~iload,
+ if ~iload
[idehess_max, idemoments_max, idemodel_max, idelre_max, derivatives_info_max, info_max, options_ident] = ...
identification_analysis(pdraws(jmax,:),indx,indexo,options_ident,dataset_,dataset_info, prior_exist, name_tex,1,tittxt);
save([IdentifDirectoryName '/' M_.fname '_identif.mat'], 'idehess_max', 'idemoments_max','idemodel_max', 'idelre_max', 'jmax', '-append');
end
disp_identification(pdraws(jmax,:), idemodel_max, idemoments_max, name,1);
close all,
- if ~options_.nograph,
+ if ~options_.nograph
plot_identification(pdraws(jmax,:),idemoments_max,idehess_max,idemodel_max,idelre_max,1,tittxt,name,IdentifDirectoryName,tittxt,name_tex);
end
[dum,jmin]=min(idemoments.cond);
fprintf('\n')
tittxt = 'Draw with SMALLEST condition number';
fprintf('\n')
- disp(['Testing ',tittxt, '. Press ENTER']), pause(5),
- if ~iload,
+ disp(['Testing ',tittxt, '. Press ENTER']), pause(5)
+ if ~iload
[idehess_min, idemoments_min, idemodel_min, idelre_min, derivatives_info_min, info_min, options_ident] = ...
identification_analysis(pdraws(jmin,:),indx,indexo,options_ident,dataset_, dataset_info, prior_exist, name_tex,1,tittxt);
save([IdentifDirectoryName '/' M_.fname '_identif.mat'], 'idehess_min', 'idemoments_min','idemodel_min', 'idelre_min', 'jmin', '-append');
end
disp_identification(pdraws(jmin,:), idemodel_min, idemoments_min, name,1);
close all,
- if ~options_.nograph,
+ if ~options_.nograph
plot_identification(pdraws(jmin,:),idemoments_min,idehess_min,idemodel_min,idelre_min,1,tittxt,name,IdentifDirectoryName,tittxt,name_tex);
end
else
- for j=1:length(jcrit),
+ for j=1:length(jcrit)
tittxt = ['Rank deficient draw n. ',int2str(j)];
fprintf('\n')
disp(['Testing ',tittxt, '. Press ENTER']), pause(5),
- if ~iload,
+ if ~iload
[idehess_(j), idemoments_(j), idemodel_(j), idelre_(j), derivatives_info_(j), info_resolve, options_ident] = ...
identification_analysis(pdraws(jcrit(j),:),indx,indexo,options_ident,dataset_, dataset_info, prior_exist, name_tex,1,tittxt);
end
disp_identification(pdraws(jcrit(j),:), idemodel_(j), idemoments_(j), name,1);
- close all,
- if ~options_.nograph,
+ close all
+ if ~options_.nograph
plot_identification(pdraws(jcrit(j),:),idemoments_(j),idehess_(j),idemodel_(j),idelre_(j),1,tittxt,name,IdentifDirectoryName,tittxt,name_tex);
end
end
- if ~iload,
+ if ~iload
save([IdentifDirectoryName '/' M_.fname '_identif.mat'], 'idehess_', 'idemoments_','idemodel_', 'idelre_', 'jcrit', '-append');
end
end
@@ -625,13 +620,13 @@ if SampleSize > 1,
end
if isoctave
- warning('on'),
+ warning('on')
else
- warning on,
+ warning on
end
skipline()
-disp(['==== Identification analysis completed ====' ]),
+disp(['==== Identification analysis completed ====' ])
skipline(2)
options_ = options0_;
diff --git a/matlab/dynare_resolve.m b/matlab/dynare_resolve.m
index a2fad992a..0911fec75 100644
--- a/matlab/dynare_resolve.m
+++ b/matlab/dynare_resolve.m
@@ -90,7 +90,7 @@ switch nargin
ic = [ nstatic+(1:nspred) endo_nbr+(1:size(DynareResults.dr.ghx,2)-nspred) ]';
else
ic = DynareResults.dr.restrict_columns;
- end;
+ end
case 4
iv = DynareResults.dr.restrict_var_list;
ic = DynareResults.dr.restrict_columns;
diff --git a/matlab/dynare_sensitivity.m b/matlab/dynare_sensitivity.m
index 62f688ec7..d84300c9a 100644
--- a/matlab/dynare_sensitivity.m
+++ b/matlab/dynare_sensitivity.m
@@ -32,36 +32,36 @@ lgy_ = M_.endo_names;
x0=[];
% check user defined options
-if isfield(options_gsa,'neighborhood_width') && options_gsa.neighborhood_width,
- if isfield(options_gsa,'pprior') && options_gsa.pprior,
+if isfield(options_gsa,'neighborhood_width') && options_gsa.neighborhood_width
+ if isfield(options_gsa,'pprior') && options_gsa.pprior
error('sensitivity:: neighborhood_width is incompatible with prior sampling')
end
- if isfield(options_gsa,'ppost') && options_gsa.ppost,
+ if isfield(options_gsa,'ppost') && options_gsa.ppost
error('sensitivity:: neighborhood_width is incompatible with posterior sampling')
end
end
-if isfield(options_gsa,'morris') && options_gsa.morris==1,
- if isfield(options_gsa,'identification') && options_gsa.identification==0,
+if isfield(options_gsa,'morris') && options_gsa.morris==1
+ if isfield(options_gsa,'identification') && options_gsa.identification==0
% options_gsa.redform=1;
end
- if isfield(options_gsa,'ppost') && options_gsa.ppost,
+ if isfield(options_gsa,'ppost') && options_gsa.ppost
error('sensitivity:: Morris is incompatible with posterior sampling')
- elseif isfield(options_gsa,'pprior') && options_gsa.pprior==0,
- if ~(isfield(options_gsa,'neighborhood_width') && options_gsa.neighborhood_width),
+ elseif isfield(options_gsa,'pprior') && options_gsa.pprior==0
+ if ~(isfield(options_gsa,'neighborhood_width') && options_gsa.neighborhood_width)
error('sensitivity:: Morris is incompatible with MC sampling with correlation matrix')
end
end
- if isfield(options_gsa,'rmse') && options_gsa.rmse,
+ if isfield(options_gsa,'rmse') && options_gsa.rmse
error('sensitivity:: Morris is incompatible with rmse analysis')
end
if (isfield(options_gsa,'alpha2_stab') && options_gsa.alpha2_stab<1) || ...
(isfield(options_gsa,'pvalue_ks') && options_gsa.pvalue_ks) || ...
(isfield(options_gsa,'pvalue_corr') && options_gsa.pvalue_corr)
-
error('sensitivity:: Morris is incompatible with Monte Carlo filtering')
end
end
+
% end check user defined options
options_gsa = set_default_option(options_gsa,'datafile',[]);
options_gsa = set_default_option(options_gsa,'rmse',0);
@@ -69,51 +69,50 @@ options_gsa = set_default_option(options_gsa,'useautocorr',0);
options_gsa = set_default_option(options_gsa,'moment_calibration',options_.endogenous_prior_restrictions.moment);
options_gsa = set_default_option(options_gsa,'irf_calibration',options_.endogenous_prior_restrictions.irf);
-if isfield(options_gsa,'nograph'),
+if isfield(options_gsa,'nograph')
options_.nograph=options_gsa.nograph;
end
-if isfield(options_gsa,'nodisplay'),
+if isfield(options_gsa,'nodisplay')
options_.nodisplay=options_gsa.nodisplay;
end
-if isfield(options_gsa,'graph_format'),
+if isfield(options_gsa,'graph_format')
options_.graph_format=options_gsa.graph_format;
end
-if isfield(options_gsa,'mode_file'),
+if isfield(options_gsa,'mode_file')
options_.mode_file=options_gsa.mode_file;
-elseif isfield(options_gsa,'neighborhood_width') && options_gsa.neighborhood_width>0,
- options_.mode_file='';
+elseif isfield(options_gsa,'neighborhood_width') && options_gsa.neighborhood_width>0
+ options_.mode_file='';
end
options_.order = 1;
-if ~isempty(options_gsa.datafile) || isempty(bayestopt_) || options_gsa.rmse,
- if isempty(options_gsa.datafile) && options_gsa.rmse,
+if ~isempty(options_gsa.datafile) || isempty(bayestopt_) || options_gsa.rmse
+ if isempty(options_gsa.datafile) && options_gsa.rmse
disp('The data file and all relevant estimation options ')
disp('[first_obs, nobs, presample, prefilter, loglinear, lik_init, kalman_algo, ...]')
disp('must be specified for RMSE analysis!');
- error('Sensitivity anaysis error!');
+ error('Sensitivity anaysis error!')
end
-
options_.datafile = options_gsa.datafile;
- if isfield(options_gsa,'first_obs'),
+ if isfield(options_gsa,'first_obs')
options_.first_obs=options_gsa.first_obs;
end
- if isfield(options_gsa,'nobs'),
+ if isfield(options_gsa,'nobs')
options_.nobs=options_gsa.nobs;
end
- if isfield(options_gsa,'presample'),
+ if isfield(options_gsa,'presample')
options_.presample=options_gsa.presample;
end
- if isfield(options_gsa,'prefilter'),
+ if isfield(options_gsa,'prefilter')
options_.prefilter=options_gsa.prefilter;
end
- if isfield(options_gsa,'loglinear'),
+ if isfield(options_gsa,'loglinear')
options_.loglinear=options_gsa.loglinear;
end
- if isfield(options_gsa,'lik_init'),
+ if isfield(options_gsa,'lik_init')
options_.lik_init=options_gsa.lik_init;
end
- if isfield(options_gsa,'kalman_algo'),
+ if isfield(options_gsa,'kalman_algo')
options_.kalman_algo=options_gsa.kalman_algo;
end
options_.mode_compute = 0;
@@ -124,25 +123,25 @@ if ~isempty(options_gsa.datafile) || isempty(bayestopt_) || options_gsa.rmse,
else
if isempty(options_.qz_criterium)
options_.qz_criterium = 1+1e-6;
- end
+ end
end
[make,my,day,punk,M_,options_,oo_] = dynare_resolve(M_,options_,oo_);
options_gsa = set_default_option(options_gsa,'identification',0);
-if options_gsa.identification,
+if options_gsa.identification
options_gsa.redform=0;
options_gsa = set_default_option(options_gsa,'morris',1);
options_gsa = set_default_option(options_gsa,'trans_ident',0);
options_gsa = set_default_option(options_gsa,'load_ident_files',0);
options_gsa = set_default_option(options_gsa,'ar',1);
options_.ar = options_gsa.ar;
- if options_gsa.morris==0,
+ if options_gsa.morris==0
disp('The option morris = 0 is no longer supported (Type I errors)')
disp('This option is reset at morris = 2 (local identification analysis).')
options_gsa.morris=2;
end
- if options_gsa.morris==2,
- if isfield(options_,'options_ident'),
+ if options_gsa.morris==2
+ if isfield(options_,'options_ident')
options_.options_ident.load_ident_files = options_gsa.load_ident_files;
options_.options_ident.useautocorr = options_gsa.useautocorr;
options_.options_ident.ar = options_gsa.ar;
@@ -199,27 +198,27 @@ options_gsa = set_default_option(options_gsa,'istart_rmse',options_.presample+1)
options_gsa = set_default_option(options_gsa,'alpha_rmse',0.001);
options_gsa = set_default_option(options_gsa,'alpha2_rmse',1.e-5);
-if options_gsa.neighborhood_width,
+if options_gsa.neighborhood_width
options_gsa.pprior=0;
options_gsa.ppost=0;
end
-if options_gsa.redform && options_gsa.neighborhood_width==0 && isempty(options_gsa.threshold_redform),
+if options_gsa.redform && options_gsa.neighborhood_width==0 && isempty(options_gsa.threshold_redform)
options_gsa.pprior=1;
options_gsa.ppost=0;
end
-if options_gsa.morris>2,
+if options_gsa.morris>2
disp('The option morris = 3 is no longer supported')
disp('the option is reset at morris = 1 .')
options_gsa.morris=1;
end
-if options_gsa.morris==1,
- if ~options_gsa.identification,
+if options_gsa.morris==1
+ if ~options_gsa.identification
options_gsa.redform=1;
end
- if options_gsa.neighborhood_width,
+ if options_gsa.neighborhood_width
options_gsa.pprior=0;
else
options_gsa.pprior=1;
@@ -244,38 +243,37 @@ end
% options_.opt_gsa = options_gsa;
-if (options_gsa.load_stab || options_gsa.load_rmse || options_gsa.load_redform) ...
- && options_gsa.pprior,
+if (options_gsa.load_stab || options_gsa.load_rmse || options_gsa.load_redform) && options_gsa.pprior
filetoload=[OutputDirectoryName '/' fname_ '_prior.mat'];
- if ~exist(filetoload),
+ if ~exist(filetoload)
disp([filetoload,' not found!'])
disp(['You asked to load a non existent analysis'])
%options_gsa.load_stab=0;
- return,
+ return
else
- if isempty(strmatch('bkpprior',who('-file', filetoload),'exact')),
+ if isempty(strmatch('bkpprior',who('-file', filetoload),'exact'))
disp('Warning! Missing prior info for saved sample') % trap for files previous
disp('The saved files are generated with previous version of GSA package') % trap for files previous
else
- load(filetoload,'bkpprior'),
+ load(filetoload,'bkpprior')
if any(bayestopt_.pshape~=bkpprior.pshape) || ...
any(bayestopt_.p1~=bkpprior.p1) || ...
any(bayestopt_.p2~=bkpprior.p2) || ...
any(bayestopt_.p3(~isnan(bayestopt_.p3))~=bkpprior.p3(~isnan(bkpprior.p3))) || ...
- any(bayestopt_.p4(~isnan(bayestopt_.p4))~=bkpprior.p4(~isnan(bkpprior.p4))),
+ any(bayestopt_.p4(~isnan(bayestopt_.p4))~=bkpprior.p4(~isnan(bkpprior.p4)))
disp('WARNING!')
disp('The saved sample has different priors w.r.t. to current ones!!')
skipline()
disp('Press ENTER to continue')
- pause;
+ pause
end
end
end
end
-if options_gsa.stab && ~options_gsa.ppost,
+if options_gsa.stab && ~options_gsa.ppost
x0 = stab_map_(OutputDirectoryName,options_gsa);
- if isempty(x0),
+ if isempty(x0)
skipline()
disp('Sensitivity computations stopped: no parameter set provided a unique solution')
return
@@ -286,20 +284,19 @@ end
% redform_map(namendo, namlagendo, namexo, icomp, pprior, ilog, threshold)
options_.opt_gsa = options_gsa;
-if ~isempty(options_gsa.moment_calibration) || ~isempty(options_gsa.irf_calibration),
+if ~isempty(options_gsa.moment_calibration) || ~isempty(options_gsa.irf_calibration)
map_calibration(OutputDirectoryName, M_, options_, oo_, estim_params_,bayestopt_);
end
-if options_gsa.identification,
+if options_gsa.identification
map_ident_(OutputDirectoryName,options_gsa);
end
-if options_gsa.redform && ~isempty(options_gsa.namendo),% ...
- % && ~options_gsa.ppost,
- if options_gsa.ppost,
+if options_gsa.redform && ~isempty(options_gsa.namendo)
+ if options_gsa.ppost
filnam = dir([M_.dname filesep 'metropolis' filesep '*param_irf*.mat']);
lpmat=[];
- for j=1:length(filnam),
+ for j=1:length(filnam)
load ([M_.dname filesep 'metropolis' filesep M_.fname '_param_irf' int2str(j) '.mat'])
lpmat=[lpmat; stock];
end
@@ -320,22 +317,21 @@ if options_gsa.redform && ~isempty(options_gsa.namendo),% ...
x0 = stab_map_(OutputDirectoryName,options_gsa);
end
- if strmatch(':',options_gsa.namendo,'exact'),
+ if strmatch(':',options_gsa.namendo,'exact')
options_gsa.namendo=M_.endo_names(1:M_.orig_endo_nbr,:);
end
- if strmatch(':',options_gsa.namexo,'exact'),
+ if strmatch(':',options_gsa.namexo,'exact')
options_gsa.namexo=M_.exo_names;
end
- if strmatch(':',options_gsa.namlagendo,'exact'),
+ if strmatch(':',options_gsa.namlagendo,'exact')
options_gsa.namlagendo=M_.endo_names(1:M_.orig_endo_nbr,:);
end
% options_.opt_gsa = options_gsa;
- if options_gsa.morris==1,
+ if options_gsa.morris==1
redform_screen(OutputDirectoryName,options_gsa);
else
% check existence of the SS_ANOVA toolbox
- if isempty(options_gsa.threshold_redform) && ...
- ~(exist('gsa_sdp','file')==6 || exist('gsa_sdp','file')==2),
+ if isempty(options_gsa.threshold_redform) && ~(exist('gsa_sdp','file')==6 || exist('gsa_sdp','file')==2)
fprintf('\nThe "SS-ANOVA-R: MATLAB Toolbox for the estimation of Smoothing Spline ANOVA models with Recursive algorithms" is missing.\n')
fprintf('To obtain it, go to:\n\n')
fprintf('http://ipsc.jrc.ec.europa.eu/?id=790 \n\n')
@@ -350,26 +346,26 @@ end
% RMSE mapping
% function [rmse_MC, ixx] = filt_mc_(vvarvecm, loadSA, pfilt, alpha, alpha2)
options_.opt_gsa = options_gsa;
-if options_gsa.rmse,
+if options_gsa.rmse
if ~options_gsa.ppost
if options_gsa.pprior
a=whos('-file',[OutputDirectoryName,'/',fname_,'_prior'],'logpo2');
else
a=whos('-file',[OutputDirectoryName,'/',fname_,'_mc'],'logpo2');
end
- if isoctave
+ if isoctave()
aflag=0;
- for ja=1:length(a),
+ for ja=1:length(a)
aflag=aflag+strcmp('logpo2',a(ja).name);
end
- if aflag==0,
+ if aflag==0
a=[];
else
a=1;
end
end
- if isempty(a),
- if options_gsa.lik_only,
+ if isempty(a)
+ if options_gsa.lik_only
options_.smoother=0;
options_.filter_step_ahead=[];
options_.forecast=0;
@@ -381,13 +377,13 @@ if options_gsa.rmse,
else
TmpDirectoryName = ([M_.dname filesep 'gsa' filesep 'mc']);
end
- if exist(TmpDirectoryName,'dir');
+ if exist(TmpDirectoryName,'dir')
mydelete([M_.fname '_filter_step_ahead*.mat'],[TmpDirectoryName filesep]);
mydelete([M_.fname '_inno*.mat'],[TmpDirectoryName filesep]);
mydelete([M_.fname '_smooth*.mat'],[TmpDirectoryName filesep]);
mydelete([M_.fname '_update*.mat'],[TmpDirectoryName filesep]);
filparam = dir([TmpDirectoryName filesep M_.fname '_param*.mat']);
- for j=1:length(filparam),
+ for j=1:length(filparam)
if isempty(strmatch([M_.fname '_param_irf'],filparam(j).name))
delete([TmpDirectoryName filesep filparam(j).name]);
end
@@ -422,7 +418,7 @@ end
options_.opt_gsa = options_gsa;
-if options_gsa.glue,
+if options_gsa.glue
dr_ = oo_.dr;
if options_gsa.ppost
load([OutputDirectoryName,'/',fname_,'_post']);
@@ -434,7 +430,7 @@ if options_gsa.glue,
load([OutputDirectoryName,'/',fname_,'_mc']);
end
end
- if ~exist('x'),
+ if ~exist('x')
disp(['No RMSE analysis is available for current options'])
disp(['No GLUE file prepared'])
return,
@@ -497,8 +493,8 @@ if options_gsa.glue,
end
jsmoo = length(options_.varobs);
- for j=1:M_.endo_nbr,
- if ~ismember(j,ismoo),
+ for j=1:M_.endo_nbr
+ if ~ismember(j,ismoo)
jsmoo=jsmoo+1;
vj=deblank(M_.endo_names(dr_.order_var(j),:));
if ~options_gsa.ppost
@@ -517,7 +513,7 @@ if options_gsa.glue,
end
end
tit(M_.exo_names_orig_ord,:) = M_.exo_names;
- for j=1:M_.exo_nbr,
+ for j=1:M_.exo_nbr
Exo(j).name = deblank(tit(j,:));
end
if ~options_gsa.ppost
diff --git a/matlab/dynare_solve.m b/matlab/dynare_solve.m
index 149d2f9ed..75659ee5e 100644
--- a/matlab/dynare_solve.m
+++ b/matlab/dynare_solve.m
@@ -80,7 +80,7 @@ i = find(~isfinite(fvec));
if ~isempty(i)
info = 1;
x = NaN(size(fvec));
- return;
+ return
end
% this test doesn't check complementarity conditions and is not used for
@@ -125,7 +125,7 @@ if options.solve_algo == 0
[x,fval,exitval,output] = fsolve(func,x,options4fsolve);
else
exitval = 3;
- end;
+ end
end
if exitval == 1
diff --git a/matlab/dynare_solve_block_or_bytecode.m b/matlab/dynare_solve_block_or_bytecode.m
index 1032d0921..d074f6bf2 100644
--- a/matlab/dynare_solve_block_or_bytecode.m
+++ b/matlab/dynare_solve_block_or_bytecode.m
@@ -80,7 +80,7 @@ elseif options.bytecode
info = 1;
return
end
- end;
+ end
end
else
[x, check] = dynare_solve('bytecode_steadystate', y, ...
diff --git a/matlab/dynare_squeeze.m b/matlab/dynare_squeeze.m
index b01be342f..a2797b8cb 100644
--- a/matlab/dynare_squeeze.m
+++ b/matlab/dynare_squeeze.m
@@ -1,4 +1,4 @@
-function B = dynare_squeeze(A);
+function B = dynare_squeeze(A)
% Same as matlab's squeeze function except that it also affects 2D arrays.
% Copyright (C) 2009 Dynare Team
diff --git a/matlab/endogenous_prior_restrictions.m b/matlab/endogenous_prior_restrictions.m
index 617116a89..7d6b979db 100644
--- a/matlab/endogenous_prior_restrictions.m
+++ b/matlab/endogenous_prior_restrictions.m
@@ -1,4 +1,4 @@
-function [info, info_irf, info_moment, data_irf, data_moment] = endogenous_prior_restrictions(T,R,Model,DynareOptions,DynareResults);
+function [info, info_irf, info_moment, data_irf, data_moment] = endogenous_prior_restrictions(T,R,Model,DynareOptions,DynareResults)
% Check for prior (sign) restrictions on irf's and theoretical moments
%
% INPUTS
@@ -41,17 +41,17 @@ data_moment=[];
endo_prior_restrictions.irf= DynareOptions.endogenous_prior_restrictions.irf;
endo_prior_restrictions.moment= DynareOptions.endogenous_prior_restrictions.moment;
-if ~isempty(endo_prior_restrictions.irf),
+if ~isempty(endo_prior_restrictions.irf)
data_irf=cell(size(endo_prior_restrictions.irf,1),1);
- if DynareOptions.order>1,
+ if DynareOptions.order>1
error('The algorithm for prior (sign) restrictions on irf''s is currently restricted to first-order decision rules')
return
end
varlist=Model.endo_names(DynareResults.dr.order_var,:);
- if isempty(T),
+ if isempty(T)
[T,R,SteadyState,infox,Model,DynareOptions,DynareResults] = dynare_resolve(Model,DynareOptions,DynareResults);
else % check if T and R are given in the restricted form!!!
- if size(T,1)<size(varlist,1),
+ if size(T,1)<size(varlist,1)
varlist=varlist(DynareResults.dr.restrict_var_list,:);
end
% check if endo_prior_restrictions.irf{:,1} variables are in varlist
@@ -67,27 +67,27 @@ if ~isempty(endo_prior_restrictions.irf),
end
end
NT=1;
- for j=1:size(endo_prior_restrictions.irf,1),
+ for j=1:size(endo_prior_restrictions.irf,1)
NT=max(NT,max(endo_prior_restrictions.irf{j,3}));
end
info_irf=ones(size(endo_prior_restrictions.irf,1),2);
- for t=1:NT,
- if ~DynareOptions.relative_irf,
+ for t=1:NT
+ if ~DynareOptions.relative_irf
RR = T^(t-1)*R*diag(sqrt(diag(Model.Sigma_e)));
else
RR = T^(t-1)*R*100;
end
- for j=1:size(endo_prior_restrictions.irf,1),
- if endo_prior_restrictions.irf{j,3}~=t,
- continue,
+ for j=1:size(endo_prior_restrictions.irf,1)
+ if endo_prior_restrictions.irf{j,3}~=t
+ continue
end
iendo=strmatch(endo_prior_restrictions.irf{j,1},varlist,'exact');
iexo=strmatch(endo_prior_restrictions.irf{j,2},Model.exo_names,'exact');
data_irf{j}=[data_irf{j}; [t RR(iendo,iexo)]];
- if (RR(iendo,iexo)>endo_prior_restrictions.irf{j,4}(1)) && (RR(iendo,iexo)<endo_prior_restrictions.irf{j,4}(2)),
+ if (RR(iendo,iexo)>endo_prior_restrictions.irf{j,4}(1)) && (RR(iendo,iexo)<endo_prior_restrictions.irf{j,4}(2))
info_irf(j,:)=info_irf(j,:).*[0, 0];
else
- if RR(iendo,iexo)<endo_prior_restrictions.irf{j,4}(1),
+ if RR(iendo,iexo)<endo_prior_restrictions.irf{j,4}(1)
delt = (RR(iendo,iexo)-endo_prior_restrictions.irf{j,4}(1))^2;
else
delt = (RR(iendo,iexo)-endo_prior_restrictions.irf{j,4}(2))^2;
@@ -96,34 +96,32 @@ if ~isempty(endo_prior_restrictions.irf),
end
end
end
- if any(info_irf),
+ if any(info_irf)
info=[49,sum(info_irf(:,2))];
end
end
-if ~isempty(endo_prior_restrictions.moment),
-
- if DynareOptions.order>1,
+if ~isempty(endo_prior_restrictions.moment)
+ if DynareOptions.order>1
error('The algorithm for prior (sign) restrictions on moments is currently restricted to first-order decision rules')
return
end
-
data_moment=cell(size(endo_prior_restrictions.moment,1),1);
var_list_=endo_prior_restrictions.moment{1,1};
- for j=1:size(endo_prior_restrictions.moment,1),
+ for j=1:size(endo_prior_restrictions.moment,1)
tmp=endo_prior_restrictions.moment{j,1};
- if ~ismember(tmp,cellstr(var_list_)),
+ if ~ismember(tmp,cellstr(var_list_))
var_list_ = char(var_list_, tmp);
end
tmp=endo_prior_restrictions.moment{j,2};
- if ~ismember(tmp,cellstr(var_list_)),
+ if ~ismember(tmp,cellstr(var_list_))
var_list_ = char(var_list_, tmp);
end
end
NTmax=0;
NTmin=0;
- for j=1:size(endo_prior_restrictions.moment,1),
+ for j=1:size(endo_prior_restrictions.moment,1)
NTmax=max(NTmax,max(endo_prior_restrictions.moment{j,3}));
NTmin=min(NTmin,min(endo_prior_restrictions.moment{j,3}));
end
@@ -133,21 +131,21 @@ if ~isempty(endo_prior_restrictions.moment),
for i=1:nvar
i_tmp = strmatch(var_list_(i,:),Model.endo_names,'exact');
if isempty(i_tmp)
- error (['One of the variable specified does not exist']) ;
+ error (['One of the variable specified does not exist'])
else
ivar(i) = i_tmp;
end
end
DynareOptions.ar = max(abs(NTmin),NTmax);
[gamma_y,stationary_vars] = th_autocovariances(DynareResults.dr, ivar, Model, DynareOptions,1);
- for t=NTmin:NTmax,
+ for t=NTmin:NTmax
RR = gamma_y{abs(t)+1};
- if t==0,
+ if t==0
RR = RR./(sqrt(diag(RR))*sqrt(diag(RR))')-eye(nvar)+diag(diag(gamma_y{t+1})); % becomes correlation
end
- for j=1:size(endo_prior_restrictions.moment,1),
- if endo_prior_restrictions.moment{j,3}~=t,
- continue,
+ for j=1:size(endo_prior_restrictions.moment,1)
+ if endo_prior_restrictions.moment{j,3}~=t
+ continue
end
iendo1 = strmatch(endo_prior_restrictions.moment{j,1},var_list_,'exact');
iendo2 = strmatch(endo_prior_restrictions.moment{j,2},var_list_,'exact');
@@ -157,10 +155,10 @@ if ~isempty(endo_prior_restrictions.moment),
iendo2=tmp0;
end
data_moment{j}=[data_moment{j}; [t RR(iendo1,iendo2)]];
- if (RR(iendo1,iendo2)>endo_prior_restrictions.moment{j,4}(1)) && (RR(iendo1,iendo2)<endo_prior_restrictions.moment{j,4}(2)),
+ if (RR(iendo1,iendo2)>endo_prior_restrictions.moment{j,4}(1)) && (RR(iendo1,iendo2)<endo_prior_restrictions.moment{j,4}(2))
info_moment(j,:)=info_moment(j,:).*[0, 0];
else
- if RR(iendo1,iendo2)<endo_prior_restrictions.moment{j,4}(1),
+ if RR(iendo1,iendo2)<endo_prior_restrictions.moment{j,4}(1)
delt = (RR(iendo1,iendo2)-endo_prior_restrictions.moment{j,4}(1))^2;
else
delt = (RR(iendo1,iendo2)-endo_prior_restrictions.moment{j,4}(2))^2;
@@ -169,10 +167,7 @@ if ~isempty(endo_prior_restrictions.moment),
end
end
end
- if any(info_moment),
+ if any(info_moment)
info=[49, info(2) + sum(info_moment(:,2))];
end
-end
-return
-
-
+end
\ No newline at end of file
diff --git a/matlab/ep/extended_path_initialization.m b/matlab/ep/extended_path_initialization.m
index 34d7cdc68..8a6117df8 100644
--- a/matlab/ep/extended_path_initialization.m
+++ b/matlab/ep/extended_path_initialization.m
@@ -134,6 +134,6 @@ if DynareOptions.ep.solve_algo == 10
elseif DynareOptions.ep.solve_algo == 11
DynareOptions.mcppath.lb = repmat(lb,block_nbr,1);
DynareOptions.mcppath.ub = repmat(ub,block_nbr,1);
-end;
+end
pfm.block_nbr = block_nbr;
diff --git a/matlab/ep/extended_path_shocks.m b/matlab/ep/extended_path_shocks.m
index 693990340..e83fa4f22 100644
--- a/matlab/ep/extended_path_shocks.m
+++ b/matlab/ep/extended_path_shocks.m
@@ -1,4 +1,4 @@
-function [shocks, spfm_exo_simul, innovations, DynareResults] = extended_path_shocks(innovations, ep, exogenousvariables, sample_size,DynareModel,DynareOptions, DynareResults);
+function [shocks, spfm_exo_simul, innovations, DynareResults] = extended_path_shocks(innovations, ep, exogenousvariables, sample_size,DynareModel,DynareOptions, DynareResults)
% Copyright (C) 2016 Dynare Team
%
diff --git a/matlab/evaluate_steady_state.m b/matlab/evaluate_steady_state.m
index 053d62255..5ab906be9 100644
--- a/matlab/evaluate_steady_state.m
+++ b/matlab/evaluate_steady_state.m
@@ -67,7 +67,7 @@ function [ys,params,info] = evaluate_steady_state(ys_init,M,options,oo,steadysta
if options.debug
fprintf('\nevaluate_steady_state: The steady state file computation for the Ramsey problem resulted in NaNs.\n')
fprintf('evaluate_steady_state: The steady state was computed conditional on the following initial instrument values: \n')
- for ii = 1:size(options.instruments,1);
+ for ii = 1:size(options.instruments,1)
fprintf('\t %s \t %f \n',options.instruments(ii,:),ys_init(strmatch(options.instruments(ii,:),M.endo_names,'exact')))
end
fprintf('evaluate_steady_state: The problem occured in the following equations: \n')
@@ -75,35 +75,35 @@ function [ys,params,info] = evaluate_steady_state(ys_init,M,options,oo,steadysta
for ii=1:length(nan_indices)
fprintf('%d, ',nan_indices(ii));
end
- skipline();
+ skipline()
fprintf('evaluate_steady_state: If those initial values are not admissable, change them using an initval-block.\n')
- skipline(2);
+ skipline(2)
end
info(1) = 84;
info(2) = resids'*resids;
- return;
+ return
end
if any(imag(ys(n_multipliers+1:end)))
if options.debug
fprintf('\nevaluate_steady_state: The steady state file computation for the Ramsey problem resulted in complex numbers.\n')
fprintf('evaluate_steady_state: The steady state was computed conditional on the following initial instrument values: \n')
- for ii = 1:size(options.instruments,1);
+ for ii = 1:size(options.instruments,1)
fprintf('\t %s \t %f \n',options.instruments(ii,:),ys_init(strmatch(options.instruments(ii,:),M.endo_names,'exact')))
end
fprintf('evaluate_steady_state: If those initial values are not admissable, change them using an initval-block.\n')
- skipline(2);
+ skipline(2)
end
info(1) = 86;
info(2) = resids'*resids;
- return;
+ return
end
if max(abs(resids(n_multipliers+1:end))) > options.solve_tolf %does it solve for all variables except for the Lagrange multipliers
if options.debug
fprintf('\nevaluate_steady_state: The steady state file does not solve the steady state for the Ramsey problem.\n')
fprintf('evaluate_steady_state: Conditional on the following instrument values: \n')
- for ii = 1:size(options.instruments,1);
+ for ii = 1:size(options.instruments,1)
fprintf('\t %s \t %f \n',options.instruments(ii,:),ys_init(strmatch(options.instruments(ii,:),M.endo_names,'exact')))
end
fprintf('evaluate_steady_state: the following equations have non-zero residuals: \n')
@@ -112,11 +112,11 @@ function [ys,params,info] = evaluate_steady_state(ys_init,M,options,oo,steadysta
fprintf('\t Equation number %d: %f\n',ii-n_multipliers, resids(ii))
end
end
- skipline(2);
+ skipline(2)
end
info(1) = 85;
info(2) = resids'*resids;
- return;
+ return
end
end
if options.debug
@@ -138,7 +138,7 @@ function [ys,params,info] = evaluate_steady_state(ys_init,M,options,oo,steadysta
%either if no steady state file or steady state file without problems
[ys,params,info] = dyn_ramsey_static(ys_init,M,options,oo);
if info
- return;
+ return
end
%check whether steady state really solves the model
resids = evaluate_static_model(ys,exo_ss,params,M,options);
@@ -151,7 +151,7 @@ function [ys,params,info] = evaluate_steady_state(ys_init,M,options,oo,steadysta
if options.debug
fprintf('\nevaluate_steady_state: The steady state computation for the Ramsey problem resulted in NaNs.\n')
fprintf('evaluate_steady_state: The steady state computation resulted in the following instrument values: \n')
- for i = 1:size(options.instruments,1);
+ for i = 1:size(options.instruments,1)
fprintf('\t %s \t %f \n',options.instruments(i,:),ys(strmatch(options.instruments(i,:),M.endo_names,'exact')))
end
fprintf('evaluate_steady_state: The problem occured in the following equations: \n')
@@ -159,17 +159,17 @@ function [ys,params,info] = evaluate_steady_state(ys_init,M,options,oo,steadysta
for ii=1:length(nan_indices)
fprintf('%d, ',nan_indices(ii));
end
- skipline();
+ skipline()
end
info(1) = 82;
- return;
+ return
end
if ~isempty(nan_indices_multiplier)
if options.debug
fprintf('\nevaluate_steady_state: The steady state computation for the Ramsey problem resulted in NaNs in the auxiliary equations.\n')
fprintf('evaluate_steady_state: The steady state computation resulted in the following instrument values: \n')
- for i = 1:size(options.instruments,1);
+ for i = 1:size(options.instruments,1)
fprintf('\t %s \t %f \n',options.instruments(i,:),ys(strmatch(options.instruments(i,:),M.endo_names,'exact')))
end
fprintf('evaluate_steady_state: The problem occured in the following equations: \n')
@@ -177,17 +177,17 @@ function [ys,params,info] = evaluate_steady_state(ys_init,M,options,oo,steadysta
for ii=1:length(nan_indices_multiplier)
fprintf('%d, ',nan_indices_multiplier(ii));
end
- skipline();
+ skipline()
end
info(1) = 83;
- return;
+ return
end
if max(abs(resids)) > options.solve_tolf %does it solve for all variables including the auxiliary ones
if options.debug
fprintf('\nevaluate_steady_state: The steady state for the Ramsey problem could not be computed.\n')
fprintf('evaluate_steady_state: The steady state computation stopped with the following instrument values:: \n')
- for i = 1:size(options.instruments,1);
+ for i = 1:size(options.instruments,1)
fprintf('\t %s \t %f \n',options.instruments(i,:),ys(strmatch(options.instruments(i,:),M.endo_names,'exact')))
end
fprintf('evaluate_steady_state: The following equations have non-zero residuals: \n')
@@ -201,21 +201,20 @@ function [ys,params,info] = evaluate_steady_state(ys_init,M,options,oo,steadysta
fprintf('\t Equation number %d: %f\n',ii-n_multipliers, resids(ii))
end
end
- skipline(2);
+ skipline(2)
end
info(1) = 81;
info(2) = resids'*resids;
- return;
+ return
end
elseif steadystate_flag
% explicit steady state file
- [ys,params,info] = evaluate_steady_state_file(ys_init,exo_ss,M, ...
- options,steadystate_check_flag);
+ [ys,params,info] = evaluate_steady_state_file(ys_init,exo_ss,M, options,steadystate_check_flag);
if size(ys,2)>size(ys,1)
error('STEADY: steady_state-file must return a column vector, not a row vector.')
end
if info(1)
- return;
+ return
end
elseif (options.bytecode == 0 && options.block == 0)
if options.linear == 0
@@ -268,7 +267,6 @@ function [ys,params,info] = evaluate_steady_state(ys_init,M,options,oo,steadysta
fprintf('STEADY: No steady state for your model could be found\n')
fprintf('STEADY: Check whether your model is truly linear. Put "resid(1);" before "steady;" to see the problematic equations.\n')
end
-
else
ys = ys_init;
end
@@ -285,8 +283,7 @@ function [ys,params,info] = evaluate_steady_state(ys_init,M,options,oo,steadysta
end
else
% block or bytecode
- [ys,check] = dynare_solve_block_or_bytecode(ys_init,exo_ss, params, ...
- options, M);
+ [ys,check] = dynare_solve_block_or_bytecode(ys_init,exo_ss, params, options, M);
end
if check
@@ -320,7 +317,6 @@ function [ys,params,info] = evaluate_steady_state(ys_init,M,options,oo,steadysta
xys = z(iyr0);
r = feval([M.fname '_dynamic'], z(iyr0), zx, M.params, ys, M.maximum_lag + 1);
end
-
% Fail if residual greater than tolerance
if max(abs(r)) > options.solve_tolf
info(1) = 25;
diff --git a/matlab/evaluate_steady_state_file.m b/matlab/evaluate_steady_state_file.m
index 8f67a5b87..fbb3cf030 100644
--- a/matlab/evaluate_steady_state_file.m
+++ b/matlab/evaluate_steady_state_file.m
@@ -134,7 +134,7 @@ function [ys,params,info] = evaluate_steady_state_file(ys_init,exo_ss,M,options,
if check
info(1) = 19;
info(2) = check; % to be improved
- return;
+ return
end
if max(abs(residuals)) > options.dynatol.f
info(1) = 19;
diff --git a/matlab/fjaco.m b/matlab/fjaco.m
index 5217ca93a..63a218af0 100644
--- a/matlab/fjaco.m
+++ b/matlab/fjaco.m
@@ -34,7 +34,7 @@ h = tol.*max(abs(x),1);
xh1=x+h; xh0=x-h;
h=xh1-xh0;
fjac = NaN(length(ff),length(x));
-for j=1:length(x);
+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{:});
diff --git a/matlab/flip_plan.m b/matlab/flip_plan.m
index a5a0952a9..dc9794a83 100644
--- a/matlab/flip_plan.m
+++ b/matlab/flip_plan.m
@@ -38,12 +38,12 @@ function plan = flip_plan(plan, exogenous, endogenous, expectation_type, date, v
ix = find(strcmp(exogenous, plan.endo_names));
if isempty(ix)
error(['in flip_plan the second argument ' exogenous ' is not an endogenous variable']);
- end;
+ end
endogenous = strtrim(endogenous);
iy = find(strcmp(endogenous, plan.exo_names));
if isempty(iy)
error(['in flip_plan the third argument ' endogenous ' is not an exogenous variable']);
- end;
+ end
sdate = length(date);
if sdate > 1
if date(1) < plan.date(1) || date(end) > plan.date(end)
diff --git a/matlab/forecast_graphs.m b/matlab/forecast_graphs.m
index 50e682c3a..108e0498b 100644
--- a/matlab/forecast_graphs.m
+++ b/matlab/forecast_graphs.m
@@ -63,7 +63,7 @@ m = 1;
n_fig = 1;
hh=dyn_figure(options_.nodisplay,'Name','Forecasts (I)');
for j= 1:nvar
- if m > nc*nr;
+ if m > nc*nr
dyn_saveas(hh,[ dname '/graphs/forcst' int2str(n_fig)],options_.nodisplay,options_.graph_format);
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fprintf(fidTeX,'\\begin{figure}[H]\n');
@@ -127,7 +127,7 @@ if isfield(oo_.forecast,'HPDinf_ME')
n_fig = 1;
hh=dyn_figure(options_.nodisplay,'Name','Forecasts including ME (I)');
for j= 1:length(var_names)
- if m > nc*nr;
+ if m > nc*nr
dyn_saveas(hh,[ dname '/graphs/forcst_ME' int2str(n_fig)],options_.nodisplay,options_.graph_format);
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fprintf(fidTeX,'\\begin{figure}[H]\n');
diff --git a/matlab/formdata.m b/matlab/formdata.m
index 06dba8416..159853645 100644
--- a/matlab/formdata.m
+++ b/matlab/formdata.m
@@ -29,6 +29,7 @@ function formdata(fname,date)
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
global M_ oo_
+
fid = fopen([fname '_endo.frm'],'w');
n=size(oo_.endo_simul,1);
t=size(oo_.endo_simul,2);
@@ -46,11 +47,10 @@ for i=1:n
fprintf(fid,'%10.5f %10.5f\n',oo_.endo_simul(i,floor(t/4)*4+1:t));
case 3
fprintf(fid,'%10.5f %10.5f %10.5f\n',oo_.endo_simul(i,floor(t/4)*4+1:t));
- end;
- %else
- % fprintf(fid,'\n');
- end;
-end;
+ end
+ end
+end
+
fclose(fid);
fid = fopen([fname '_exo.frm'],'w');
@@ -70,10 +70,8 @@ for i=1:n
fprintf(fid,'%10.5f %10.5f\n',oo_.exo_simul(floor(t/4)*4+1:t,i)');
case 3
fprintf(fid,'%10.5f %10.5f %10.5f\n',oo_.exo_simul(floor(t/4)*4+1:t,i)');
- end;
- %else
- % fprintf(fid,'\n');
- end;
-end;
-fclose(fid);
-return;
\ No newline at end of file
+ end
+ end
+end
+
+fclose(fid);
\ No newline at end of file
diff --git a/matlab/gensylv/gensylv.m b/matlab/gensylv/gensylv.m
index 26624fea7..3eb389fcf 100644
--- a/matlab/gensylv/gensylv.m
+++ b/matlab/gensylv/gensylv.m
@@ -36,9 +36,9 @@ function [err, E] = gensylv(kron_prod,A,B,C0,D)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
C = C0;
-for i=1:(kron_prod-1);
+for i=1:(kron_prod-1)
C = kron(C0,C);
-end;
+end
x0 = sylvester3(A,B,C,D);
E = sylvester3a(x0,A,B,C,D);
diff --git a/matlab/gensylv/sylvester3.m b/matlab/gensylv/sylvester3.m
index be4d8c574..a94e389b7 100644
--- a/matlab/gensylv/sylvester3.m
+++ b/matlab/gensylv/sylvester3.m
@@ -23,21 +23,21 @@ m = size(c,1);
p = size(d,3);
x=zeros(n,m,p);
if n == 1
- for j=1:p,
+ for j=1:p
x(:,:,j)=d(:,:,j)./(a*ones(1,m)+b*c);
end
return
end
if m == 1
- for j=1:p,
+ for j=1:p
x(:,:,j) = (a+c*b)\d(:,:,j);
end
- return;
+ return
end
[u,t]=schur(c);
if isoctave
[aa,bb,qq,zz]=qz(full(a),full(b));
- for j=1:p,
+ for j=1:p
if octave_ver_less_than('3.4.0')
d(:,:,j)=qq'*d(:,:,j)*u;
else
@@ -46,7 +46,7 @@ if isoctave
end
else
[aa,bb,qq,zz]=qz(full(a),full(b),'real'); % available in Matlab version 6.0
- for j=1:p,
+ for j=1:p
d(:,:,j)=qq*d(:,:,j)*u;
end
end
@@ -58,7 +58,7 @@ while i < m
if i == 1
c = zeros(n,1,p);
else
- for j=1:p,
+ for j=1:p
c(:,:,j) = bb*(x(:,1:i-1,j)*t(1:i-1,i));
end
end
@@ -69,7 +69,7 @@ while i < m
c = zeros(n,1,p);
c1 = zeros(n,1,p);
else
- for j=1:p,
+ for j=1:p
c(:,:,j) = bb*(x(:,1:i-1,j)*t(1:i-1,i));
c1(:,:,j) = bb*(x(:,1:i-1,j)*t(1:i-1,i+1));
end
@@ -82,13 +82,13 @@ while i < m
end
end
if i == m
- for j=1:p,
+ for j=1:p
c(:,:,j) = bb*(x(:,1:m-1,j)*t(1:m-1,m));
end
aabbt = (aa+bb*t(m,m));
x(:,m,:)=aabbt\squeeze(d(:,m,:)-c);
end
-for j=1:p,
+for j=1:p
x(:,:,j)=zz*x(:,:,j)*u';
end
diff --git a/matlab/gensylv/sylvester3a.m b/matlab/gensylv/sylvester3a.m
index 00724dc38..744a7ee85 100644
--- a/matlab/gensylv/sylvester3a.m
+++ b/matlab/gensylv/sylvester3a.m
@@ -21,7 +21,7 @@ function [x0, flag]=sylvester3a(x0,a,b,c,dd)
a_1 = inv(a);
b = a_1*b;
flag=0;
-for j=1:size(dd,3),
+for j=1:size(dd,3)
d = a_1*dd(:,:,j);
e = 1;
iter = 1;
diff --git a/matlab/gensylv_fp.m b/matlab/gensylv_fp.m
index 2e5c167b5..73ad0b315 100644
--- a/matlab/gensylv_fp.m
+++ b/matlab/gensylv_fp.m
@@ -50,11 +50,11 @@ if isempty(hxo)
X = zeros(size(B, 2), size(C, 1));
else
X = hxo;
-end;
+end
it_fp = 0;
maxit_fp = 1000;
Z = - (B * X * C + D);
-while it_fp < maxit_fp && evol > tol;
+while it_fp < maxit_fp && evol > tol
%X_old = X;
%X = - A1 * ( B * X * C + D);
%evol = max(max(abs(X - X_old)));
@@ -64,10 +64,10 @@ while it_fp < maxit_fp && evol > tol;
evol = max(sum(abs(Z - Z_old))); %norm_1
%evol = max(sum(abs(Z - Z_old)')); %norm_inf
it_fp = it_fp + 1;
-end;
+end
%fprintf('sylvester it_fp=%d evol=%g | ',it_fp,evol);
if evol < tol
eval(['hxo_' int2str(block) ' = X;']);
else
error(['convergence not achieved in fixed point solution of Sylvester equation after ' int2str(it_fp) ' iterations']);
-end;
\ No newline at end of file
+end
\ No newline at end of file
diff --git a/matlab/getH.m b/matlab/getH.m
index 0db11d8e3..4bfa6949d 100644
--- a/matlab/getH.m
+++ b/matlab/getH.m
@@ -66,7 +66,7 @@ end
yy0=oo_.dr.ys(I);
param_nbr = length(indx);
tot_param_nbr = param_nbr + length(indexo);
-if nargout>5,
+if nargout>5
param_nbr_2 = param_nbr*(param_nbr+1)/2;
tot_param_nbr_2 = tot_param_nbr*(tot_param_nbr+1)/2;
end
@@ -75,18 +75,18 @@ m = size(A,1);
m1=length(iv);
n = size(B,2);
-if kronflag==-1, % perturbation
+if kronflag==-1 % perturbation
gp=0;
fun = 'thet2tau';
params0 = M_.params;
H = fjaco(fun,[sqrt(diag(M_.Sigma_e(indexo,indexo))); M_.params(indx)], M_, oo_, indx, indexo,0);
- if nargout>1,
+ if nargout>1
dOm = zeros(m1,m1,tot_param_nbr);
dA=zeros(m1,m1,tot_param_nbr);
Hss=H(iv,length(indexo)+1:end);
da = H(m+1:m+m*m,:);
dom = H(m+m*m+1:end,:);
- for j=1:tot_param_nbr,
+ for j=1:tot_param_nbr
tmp = dyn_unvech(dom(:,j));
dOm(:,:,j) = tmp(iv,iv);
tmp = reshape(da(:,j),m,m);
@@ -94,13 +94,13 @@ if kronflag==-1, % perturbation
end
clear da dom tmp
end
- if nargout>5,
+ if nargout>5
H2 = hessian_sparse('thet2tau',[sqrt(diag(M_.Sigma_e(indexo,indexo))); M_.params(indx)], ...
options_.gstep,estim_params_,M_, oo_, indx,indexo,0,[],[],[],iv);
H2ss = zeros(m1,tot_param_nbr,tot_param_nbr);
iax=find(triu(rand(tot_param_nbr,tot_param_nbr)));
H2 = H2(:,iax);
- for j=1:m1,
+ for j=1:m1
H2ss(j,:,:)=dyn_unvech(full(H2(j,:)));
end
H2ss=H2ss(:,length(indexo)+1:end,length(indexo)+1:end);
@@ -122,20 +122,20 @@ if kronflag==-1, % perturbation
return
end
-if kronflag==-2,
- if nargout>5,
+if kronflag==-2
+ if nargout>5
[residual, g1, g2 ] = feval([M_.fname,'_dynamic'],yy0, oo_.exo_steady_state', ...
M_.params, oo_.dr.ys, 1);
g22 = hessian_sparse('thet2tau',[M_.params(indx)],options_.gstep,estim_params_,M_, oo_, indx,[],-1);
H2ss=full(g22(1:M_.endo_nbr,:));
H2ss = reshape(H2ss,[M_.endo_nbr param_nbr param_nbr]);
- for j=1:M_.endo_nbr,
+ for j=1:M_.endo_nbr
H2ss(j,:,:)=dyn_unvech(dyn_vech(H2ss(j,:,:)));
end
g22=g22(M_.endo_nbr+1:end,:);
inx=find(g22);
gx22=zeros(length(inx),5);
- for j=1:length(inx),
+ for j=1:length(inx)
[i1, i2] = ind2sub(size(g22),inx(j));
[ig1, ig2] = ind2sub(size(g1),i1);
[ip1, ip2] = ind2sub([param_nbr param_nbr],i2);
@@ -152,18 +152,13 @@ if kronflag==-2,
gp=gp(M_.endo_nbr+1:end,:);
gp = reshape(gp,[size(g1) param_nbr]);
else
-
-% yy0=[];
-% for j=1:size(M_.lead_lag_incidence,1);
-% yy0 = [ yy0; oo_.dr.ys(find(M_.lead_lag_incidence(j,:)))];
-% end
dyssdtheta=zeros(length(oo_.dr.ys),M_.param_nbr);
d2yssdtheta=zeros(length(oo_.dr.ys),M_.param_nbr,M_.param_nbr);
[residual, gg1] = feval([M_.fname,'_static'],oo_.dr.ys, oo_.exo_steady_state', M_.params);
df = feval([M_.fname,'_static_params_derivs'],oo_.dr.ys, repmat(oo_.exo_steady_state',[M_.maximum_exo_lag+M_.maximum_exo_lead+1]), ...
M_.params);
dyssdtheta = -gg1\df;
-if nargout>5,
+if nargout>5
[residual, gg1, gg2] = feval([M_.fname,'_static'],oo_.dr.ys, oo_.exo_steady_state', M_.params);
[residual, g1, g2, g3] = feval([M_.fname,'_dynamic'],yy0, oo_.exo_steady_state', ...
M_.params, oo_.dr.ys, 1);
@@ -172,27 +167,25 @@ if nargout>5,
[df, gpx, d2f] = feval([M_.fname,'_static_params_derivs'],oo_.dr.ys, oo_.exo_steady_state', ...
M_.params);%, oo_.dr.ys, 1, dyssdtheta*0, d2yssdtheta);
d2f = get_all_resid_2nd_derivs(d2f,length(oo_.dr.ys),M_.param_nbr);
-
- if isempty(find(gg2)),
- for j=1:M_.param_nbr,
+ if isempty(find(gg2))
+ for j=1:M_.param_nbr
d2yssdtheta(:,:,j) = -gg1\d2f(:,:,j);
end
else
gam = d2f*0;
- for j=1:nr,
+ for j=1:nr
tmp1 = (squeeze(gpx(j,:,:))'*dyssdtheta);
gam(j,:,:)=transpose(reshape(gg2(j,:),[nr nr])*dyssdtheta)*dyssdtheta ...
+ tmp1 + tmp1';
end
- for j=1:M_.param_nbr,
+ for j=1:M_.param_nbr
d2yssdtheta(:,:,j) = -gg1\(d2f(:,:,j)+gam(:,:,j));
-% d2yssdtheta(:,:,j) = -gg1\(d2f(:,:,j)+gam(:,:,j)+ squeeze(gpx(:,:,j))*dyssdtheta);
end
- clear tmp1 gpx gam,
+ clear tmp1 gpx gam
end
end
-if any(any(isnan(dyssdtheta))),
+if any(any(isnan(dyssdtheta)))
[U,T] = schur(gg1);
qz_criterium=options_.qz_criterium;
e1 = abs(ordeig(T)) < qz_criterium-1;
@@ -201,19 +194,16 @@ if any(any(isnan(dyssdtheta))),
[U,T] = ordschur(U,T,e1);
T = T(k+1:end,k+1:end);
dyssdtheta = -U(:,k+1:end)*(T\U(:,k+1:end)')*df;
- if nargout>5,
- for j=1:length(indx),
+ if nargout>5
+ for j=1:length(indx)
d2yssdtheta(:,:,j) = -U(:,k+1:end)*(T\U(:,k+1:end)')*d2f(:,:,j);
end
end
end
-if nargout>5,
+if nargout>5
[df, gp, d2f, gpp, hp] = feval([M_.fname,'_params_derivs'],yy0, oo_.exo_steady_state', ...
M_.params, oo_.dr.ys, 1, dyssdtheta, d2yssdtheta);
H2ss = d2yssdtheta(oo_.dr.order_var,indx,indx);
-% nelem=size(g1,2);
-% g22 = get_all_2nd_derivs(gpp,m,nelem,M_.param_nbr);
-% g22 = g22(:,:,indx,indx);
else
[df, gp] = feval([M_.fname,'_params_derivs'],yy0, repmat(oo_.exo_steady_state',[M_.maximum_exo_lag+M_.maximum_exo_lead+1,1]), ...
M_.params, oo_.dr.ys, 1, dyssdtheta,d2yssdtheta);
@@ -227,12 +217,12 @@ Hss = dyssdtheta(oo_.dr.order_var,indx);
dyssdtheta = dyssdtheta(I,:);
ns = max(max(M_.lead_lag_incidence)); % retrieve the number of states excluding columns for shocks
gp2 = gp*0;
-for j=1:nr,
+for j=1:nr
[II JJ]=ind2sub([nc nc],find(g2(j,:)));
- for i=1:nc,
+ for i=1:nc
is = find(II==i);
is = is(find(JJ(is)<=ns));
- if ~isempty(is),
+ if ~isempty(is)
g20=full(g2(j,find(g2(j,:))));
gp2(j,i,:)=g20(is)*dyssdtheta(JJ(is),:);
end
@@ -242,7 +232,7 @@ end
gp = gp+gp2;
gp = gp(:,:,indx);
-if nargout>5,
+if nargout>5
% h22 = get_all_hess_derivs(hp,nr,nc,M_.param_nbr);
g22 = gpp;
gp22 = sparse(nr*nc,param_nbr*param_nbr);
@@ -251,16 +241,16 @@ if nargout>5,
% tmp2=tmp1*[dyssdtheta; zeros(nc-ns,M_.param_nbr)];
tmpa=[dyssdtheta; zeros(nc-ns,M_.param_nbr)];
tmpa=sparse(tmpa);
- for j=1:M_.param_nbr,
+ for j=1:M_.param_nbr
tmp2(:,j)=tmp1*tmpa(:,j);
end
% tmp2=sparse(tmp2);
% [i1 i2]=ind2sub([nc M_.param_nbr],[1:nc*M_.param_nbr]');
- for j=1:nr,
+ for j=1:nr
tmp0=reshape(g2(j,:),[nc nc]);
tmp0 = tmp0(:,1:ns)*reshape(d2yssdtheta(I,:,:),[ns,M_.param_nbr*M_.param_nbr]);
- for i=1:nc,
+ for i=1:nc
indo = sub2ind([nr nc nc], ones(nc,1)*j ,ones(nc,1)*i, (1:nc)');
tmpx = (tmp2(indo,:))'*[dyssdtheta; zeros(nc-ns,M_.param_nbr)];
% gp22(j,i,:,:)=squeeze(tmp1(j,i,:,:))'*[dyssdtheta; zeros(nc-ns,M_.param_nbr)];
@@ -268,7 +258,7 @@ if nargout>5,
tmpy = tmpx+tmpu+tmpu'+reshape(tmp0(i,:,:),[M_.param_nbr M_.param_nbr]);
tmpy = tmpy + get_2nd_deriv_mat(gpp,j,i,M_.param_nbr);
tmpy = tmpy(indx,indx);
- if any(any(tmpy)),
+ if any(any(tmpy))
ina = find(triu(tmpy));
gp22(sub2ind([nr nc],j,i),ina)=transpose(tmpy(ina));
% gp22(j,i,:,:)= reshape(tmpy,[1 1 M_.param_nbr M_.param_nbr]);
@@ -280,10 +270,10 @@ if nargout>5,
% g22 = g22+gp22;
% g22 = g22(:,:,indx,indx);
- clear tmp0 tmp1 tmp2 tmpu tmpx tmpy,
+ clear tmp0 tmp1 tmp2 tmpu tmpx tmpy
inx=find(gp22);
gx22=zeros(length(inx),5);
- for j=1:length(inx),
+ for j=1:length(inx)
[i1, i2] = ind2sub(size(gp22),inx(j));
[ig1, ig2] = ind2sub(size(g1),i1);
[ip1, ip2] = ind2sub([param_nbr param_nbr],i2);
@@ -301,15 +291,14 @@ klen = M_.maximum_endo_lag + M_.maximum_endo_lead + 1;
k11 = M_.lead_lag_incidence(find([1:klen] ~= M_.maximum_endo_lag+1),:);
a = g1(:,nonzeros(k11'));
da = gp(:,nonzeros(k11'),:);
-if nargout > 5,
+if nargout > 5
indind = ismember(g22(:,2),nonzeros(k11'));
tmp = g22(indind,:);
d2a=tmp;
- for j=1:size(tmp,1),
+ for j=1:size(tmp,1)
inxinx = find(nonzeros(k11')==tmp(j,2));
d2a(j,2) = inxinx;
end
-% d2a = g22(:,nonzeros(k11'),:,:);
end
kstate = oo_.dr.kstate;
@@ -319,12 +308,12 @@ Dg1 = zeros(M_.endo_nbr,M_.endo_nbr,param_nbr);
k1 = find(kstate(:,2) == M_.maximum_endo_lag+2 & kstate(:,3));
GAM1(:, kstate(k1,1)) = -a(:,kstate(k1,3));
Dg1(:, kstate(k1,1), :) = -da(:,kstate(k1,3),:);
-if nargout > 5,
+if nargout > 5
indind = ismember(d2a(:,2),kstate(k1,3));
tmp = d2a(indind,:);
tmp(:,end)=-tmp(:,end);
D2g1 = tmp;
- for j=1:size(tmp,1),
+ for j=1:size(tmp,1)
inxinx = (kstate(k1,3)==tmp(j,2));
D2g1(j,2) = kstate(k1(inxinx),1);
end
@@ -336,11 +325,11 @@ GAM0 = zeros(M_.endo_nbr,M_.endo_nbr);
Dg0 = zeros(M_.endo_nbr,M_.endo_nbr,param_nbr);
GAM0(:,cols_b) = g1(:,cols_j);
Dg0(:,cols_b,:) = gp(:,cols_j,:);
-if nargout > 5,
+if nargout > 5
indind = ismember(g22(:,2),cols_j);
tmp = g22(indind,:);
D2g0=tmp;
- for j=1:size(tmp,1),
+ for j=1:size(tmp,1)
inxinx = (cols_j==tmp(j,2));
D2g0(j,2) = cols_b(inxinx);
end
@@ -352,12 +341,12 @@ GAM2 = zeros(M_.endo_nbr,M_.endo_nbr);
Dg2 = zeros(M_.endo_nbr,M_.endo_nbr,param_nbr);
GAM2(:, kstate(k2,1)) = -a(:,kstate(k2,4));
Dg2(:, kstate(k2,1), :) = -da(:,kstate(k2,4),:);
-if nargout > 5,
+if nargout > 5
indind = ismember(d2a(:,2),kstate(k2,4));
tmp = d2a(indind,:);
tmp(:,end)=-tmp(:,end);
D2g2 = tmp;
- for j=1:size(tmp,1),
+ for j=1:size(tmp,1)
inxinx = (kstate(k2,4)==tmp(j,2));
D2g2(j,2) = kstate(k2(inxinx),1);
end
@@ -365,13 +354,13 @@ end
GAM3 = -g1(:,length(yy0)+1:end);
Dg3 = -gp(:,length(yy0)+1:end,:);
-if nargout>5,
+if nargout>5
cols_ex = [length(yy0)+1:size(g1,2)];
indind = ismember(g22(:,2),cols_ex);
tmp = g22(indind,:);
tmp(:,end)=-tmp(:,end);
D2g3=tmp;
- for j=1:size(tmp,1),
+ for j=1:size(tmp,1)
inxinx = find(cols_ex==tmp(j,2));
D2g3(j,2) = inxinx;
end
@@ -380,11 +369,11 @@ end
clear g1 g2 g3 df d2f gpp hp residual gg1 gg2 gp2 dyssdtheta d2yssdtheta
-if kronflag==1, % kronecker products
+if kronflag==1 % kronecker products
Dg0=reshape(Dg0,m^2,param_nbr);
Dg1=reshape(Dg1,m^2,param_nbr);
Dg2=reshape(Dg2,m^2,param_nbr);
- for j=1:param_nbr,
+ for j=1:param_nbr
Dg3(:,:,j)=Dg3(:,:,j)*M_.Sigma_e;
end
Dg3=reshape(Dg3,m*n,param_nbr);
@@ -427,7 +416,7 @@ if kronflag==1, % kronecker products
H(m*m+1:end,:) = tmpH(Index,:);
Hx = [];
- if ~isempty(indexo),
+ if ~isempty(indexo)
dSig = zeros(M_.exo_nbr,M_.exo_nbr);
dOm = cat(3,zeros(size(dOm,1),size(dOm,1),length(indexo)),dOm);
for j=1:length(indexo)
@@ -435,7 +424,7 @@ if kronflag==1, % kronecker products
y = B*dSig*B';
y = y(nauxe+1:end,nauxe+1:end);
Hx(:,j) = [zeros((m-nauxe)^2,1); dyn_vech(y)];
- if nargout>1,
+ if nargout>1
dOm(:,:,j) = y;
end
dSig(indexo(j),indexo(j)) = 0;
@@ -452,24 +441,24 @@ else % generalized sylvester equation
c = A;
elem = zeros(m,m,param_nbr);
d = elem;
- for j=1:param_nbr,
+ for j=1:param_nbr
elem(:,:,j) = (Dg0(:,:,j)-Dg1(:,:,j)*A);
d(:,:,j) = Dg2(:,:,j)-elem(:,:,j)*A;
end
xx=sylvester3(a,b,c,d);
flag=1;
icount=0;
- while flag && icount<4,
+ while flag && icount<4
[xx, flag]=sylvester3a(xx,a,b,c,d);
icount=icount+1;
end
H=zeros(m1*m1+m1*(m1+1)/2,param_nbr+length(indexo));
- if nargout>1,
+ if nargout>1
dOm = zeros(m1,m1,param_nbr+length(indexo));
dA=zeros(m1,m1,param_nbr+length(indexo));
dB=zeros(m,n,param_nbr);
end
- if ~isempty(indexo),
+ if ~isempty(indexo)
dSig = zeros(M_.exo_nbr,M_.exo_nbr,length(indexo));
for j=1:length(indexo)
dSig(indexo(j),indexo(j),j) = 2*sqrt(M_.Sigma_e(indexo(j),indexo(j)));
@@ -477,22 +466,22 @@ else % generalized sylvester equation
% y = y(nauxe+1:end,nauxe+1:end);
% H(:,j) = [zeros((m-nauxe)^2,1); dyn_vech(y)];
H(:,j) = [zeros(m1^2,1); dyn_vech(y(iv,iv))];
- if nargout>1,
+ if nargout>1
dOm(:,:,j) = y(iv,iv);
end
% dSig(indexo(j),indexo(j)) = 0;
end
end
- for j=1:param_nbr,
+ for j=1:param_nbr
x = xx(:,:,j);
y = inva * (Dg3(:,:,j)-(elem(:,:,j)-GAM1*x)*B);
- if nargout>1,
+ if nargout>1
dB(:,:,j) = y;
end
y = y*M_.Sigma_e*B'+B*M_.Sigma_e*y';
% x = x(nauxe+1:end,nauxe+1:end);
% y = y(nauxe+1:end,nauxe+1:end);
- if nargout>1,
+ if nargout>1
dA(:,:,j+length(indexo)) = x(iv,iv);
dOm(:,:,j+length(indexo)) = y(iv,iv);
end
@@ -515,7 +504,7 @@ else % generalized sylvester equation
end
-if nargout > 5,
+if nargout > 5
H2ss = H2ss(iv,:,:);
d = zeros(m,m,floor(sqrt(param_nbr_2)));
% d2A = zeros(m,m,tot_param_nbr,tot_param_nbr);
@@ -533,8 +522,8 @@ if nargout > 5,
jinx = [];
x2x=sparse(m*m,param_nbr_2);
% x2x=[];
- for i=1:param_nbr,
- for j=1:i,
+ for i=1:param_nbr
+ for j=1:i
elem1 = (get_2nd_deriv(D2g0,m,m,j,i)-get_2nd_deriv(D2g1,m,m,j,i)*A);
elem1 = get_2nd_deriv(D2g2,m,m,j,i)-elem1*A;
elemj0 = Dg0(:,:,j)-Dg1(:,:,j)*A;
@@ -545,15 +534,15 @@ if nargout > 5,
jcount=jcount+1;
jinx = [jinx; [j i]];
d(:,:,jcount) = elem1+elem2;
- if jcount==floor(sqrt(param_nbr_2)) || (j*i)==param_nbr^2,
- if (j*i)==param_nbr^2,
+ if jcount==floor(sqrt(param_nbr_2)) || (j*i)==param_nbr^2
+ if (j*i)==param_nbr^2
d = d(:,:,1:jcount);
end
% d(find(abs(d)<1.e-12))=0;
xx2=sylvester3(a,b,c,d);
flag=1;
icount=0;
- while flag && icount<4,
+ while flag && icount<4
[xx2, flag]=sylvester3a(xx2,a,b,c,d);
icount = icount + 1;
end
@@ -583,11 +572,11 @@ if nargout > 5,
offset = length(indexo);
% d2B = zeros(m,n,tot_param_nbr,tot_param_nbr);
d2Sig = zeros(M_.exo_nbr,M_.exo_nbr,length(indexo));
- for j=1:tot_param_nbr,
- for i=1:j,
+ for j=1:tot_param_nbr
+ for i=1:j
jcount=jcount+1;
- if j<=offset,
- if i==j,
+ if j<=offset
+ if i==j
d2Sig(indexo(j),indexo(j),j) = 2;
y = B*d2Sig(:,:,j)*B';
% y(abs(y)<1.e-8)=0;
@@ -596,7 +585,7 @@ if nargout > 5,
else
jind = j-offset;
iind = i-offset;
- if i<=offset,
+ if i<=offset
y = dB(:,:,jind)*dSig(:,:,i)*B'+B*dSig(:,:,i)*dB(:,:,jind)';
% y(abs(y)<1.e-8)=0;
d2Om_tmp(:,jcount) = dyn_vech(y(iv,iv));
@@ -620,7 +609,7 @@ if nargout > 5,
d2Om_tmp(:,jcount) = dyn_vech(y(iv,iv));
end
end
- if jcount==ncol || i*j==tot_param_nbr^2,
+ if jcount==ncol || i*j==tot_param_nbr^2
d2A(:,cumjcount+1:cumjcount+jcount) = d2A_tmp(:,1:jcount);
% d2A(:,:,j+length(indexo),i+length(indexo)) = x;
% d2A(:,:,i+length(indexo),j+length(indexo)) = x;
@@ -643,35 +632,35 @@ end
return
-function g22 = get_2nd_deriv(gpp,m,n,i,j),
+function g22 = get_2nd_deriv(gpp,m,n,i,j)
g22=zeros(m,n);
is=find(gpp(:,3)==i);
is=is(find(gpp(is,4)==j));
-if ~isempty(is),
+if ~isempty(is)
g22(sub2ind([m,n],gpp(is,1),gpp(is,2)))=gpp(is,5)';
end
return
-function g22 = get_2nd_deriv_mat(gpp,i,j,n),
+function g22 = get_2nd_deriv_mat(gpp,i,j,n)
g22=zeros(n,n);
is=find(gpp(:,1)==i);
is=is(find(gpp(is,2)==j));
-if ~isempty(is),
+if ~isempty(is)
g22(sub2ind([n,n],gpp(is,3),gpp(is,4)))=gpp(is,5)';
g22(sub2ind([n,n],gpp(is,4),gpp(is,3)))=gpp(is,5)';
end
return
-function g22 = get_all_2nd_derivs(gpp,m,n,npar,fsparse),
+function g22 = get_all_2nd_derivs(gpp,m,n,npar,fsparse)
-if nargin==4 || isempty(fsparse),
+if nargin==4 || isempty(fsparse)
fsparse=0;
end
-if fsparse,
+if fsparse
g22=sparse(m*n,npar*npar);
else
g22=zeros(m,n,npar,npar);
@@ -680,11 +669,11 @@ end
% c=triu(c);
% ic=find(c);
-for is=1:length(gpp),
+for is=1:length(gpp)
% d=zeros(npar,npar);
% d(gpp(is,3),gpp(is,4))=1;
% indx = find(ic==find(d));
- if fsparse,
+ if fsparse
g22(sub2ind([m,n],gpp(is,1),gpp(is,2)),sub2ind([npar,npar],gpp(is,3),gpp(is,4)))=gpp(is,5);
g22(sub2ind([m,n],gpp(is,1),gpp(is,2)),sub2ind([npar,npar],gpp(is,4),gpp(is,3)))=gpp(is,5);
else
@@ -695,14 +684,14 @@ end
return
-function r22 = get_all_resid_2nd_derivs(rpp,m,npar),
+function r22 = get_all_resid_2nd_derivs(rpp,m,npar)
r22=zeros(m,npar,npar);
% c=ones(npar,npar);
% c=triu(c);
% ic=find(c);
-for is=1:length(rpp),
+for is=1:length(rpp)
% d=zeros(npar,npar);
% d(rpp(is,2),rpp(is,3))=1;
% indx = find(ic==find(d));
@@ -712,31 +701,31 @@ end
return
-function h2 = get_all_hess_derivs(hp,r,m,npar),
+function h2 = get_all_hess_derivs(hp,r,m,npar)
h2=zeros(r,m,m,npar);
-for is=1:length(hp),
+for is=1:length(hp)
h2(hp(is,1),hp(is,2),hp(is,3),hp(is,4))=hp(is,5);
h2(hp(is,1),hp(is,3),hp(is,2),hp(is,4))=hp(is,5);
end
return
-function h2 = get_hess_deriv(hp,i,j,m,npar),
+function h2 = get_hess_deriv(hp,i,j,m,npar)
h2=zeros(m,npar);
is1=find(hp(:,1)==i);
is=is1(find(hp(is1,2)==j));
-if ~isempty(is),
+if ~isempty(is)
h2(sub2ind([m,npar],hp(is,3),hp(is,4)))=hp(is,5)';
end
is=is1(find(hp(is1,3)==j));
-if ~isempty(is),
+if ~isempty(is)
h2(sub2ind([m,npar],hp(is,2),hp(is,4)))=hp(is,5)';
end
-return
+return
\ No newline at end of file
diff --git a/matlab/getJJ.m b/matlab/getJJ.m
index b7686a035..e2a90c0bb 100644
--- a/matlab/getJJ.m
+++ b/matlab/getJJ.m
@@ -56,10 +56,10 @@ function [JJ, H, gam, gp, dA, dOm, dYss] = getJJ(A, B, estim_params_, M_,oo_,opt
if nargin<8 || isempty(indx)
% indx = [1:M_.param_nbr];
-end,
+end
if nargin<9 || isempty(indexo)
indexo = [];
-end,
+end
if nargin<11 || isempty(nlags)
nlags=3;
end
@@ -70,7 +70,7 @@ end
% if useautocorr,
warning('off','MATLAB:divideByZero')
% end
-if kronflag == -1,
+if kronflag == -1
fun = 'thet2tau';
params0 = M_.params;
para0 = get_all_parameters(estim_params_, M_);
@@ -87,7 +87,7 @@ if kronflag == -1,
dYss = H(1:M_.endo_nbr,offset+1:end);
dA = reshape(H(M_.orig_endo_nbr+[1:numel(A)],:),[size(A),size(H,2)]);
dOm = dA*0;
- for j=1:size(H,2),
+ for j=1:size(H,2)
dOm(:,:,j) = dyn_unvech(H(M_.endo_nbr+numel(A)+1:end,j));
end
assignin('base','M_', M_);
@@ -115,7 +115,7 @@ else
% BB(:,:,j)= dA(:,:,j)*GAM*A'+A*GAM*dA(:,:,j)'+dOm(:,:,j);
% end
% XX = lyapunov_symm_mr(A,BB,options_.qz_criterium,options_.lyapunov_complex_threshold,0);
- for j=1:length(indexo),
+ for j=1:length(indexo)
dum = lyapunov_symm(A,dOm(:,:,j),options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,2,options_.debug);
% dum = XX(:,:,j);
k = find(abs(dum) < 1e-12);
@@ -130,7 +130,7 @@ else
else
dumm = dyn_vech(dum(mf,mf));
end
- for i=1:nlags,
+ for i=1:nlags
dum1 = A^i*dum;
if useautocorr
dum1 = (dum1.*sy-dsy.*(A^i*GAM))./(sy.*sy);
@@ -140,7 +140,7 @@ else
JJ(:,j) = dumm;
end
nexo = length(indexo);
- for j=1:length(indx),
+ for j=1:length(indx)
dum = lyapunov_symm(A,dA(:,:,j+nexo)*GAM*A'+A*GAM*dA(:,:,j+nexo)'+dOm(:,:,j+nexo),options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,2,options_.debug);
% dum = XX(:,:,j);
k = find(abs(dum) < 1e-12);
@@ -155,9 +155,9 @@ else
else
dumm = dyn_vech(dum(mf,mf));
end
- for i=1:nlags,
+ for i=1:nlags
dum1 = A^i*dum;
- for ii=1:i,
+ for ii=1:i
dum1 = dum1 + A^(ii-1)*dA(:,:,j+nexo)*A^(i-ii)*GAM;
end
if useautocorr
@@ -171,23 +171,23 @@ else
JJ = [ [zeros(length(mf),nexo) dYss(mf,:)]; JJ];
end
-if nargout >2,
+if nargout >2
% sy=sy(mf,mf);
options_.ar=nlags;
nodecomposition = 1;
[GAM,stationary_vars] = th_autocovariances(oo_.dr,oo_.dr.order_var(mf),M_,options_,nodecomposition);
sy=sqrt(diag(GAM{1}));
sy=sy*sy';
- if useautocorr,
+ if useautocorr
sy=sy-diag(diag(sy))+eye(length(mf));
GAM{1}=GAM{1}./sy;
else
- for j=1:nlags,
+ for j=1:nlags
GAM{j+1}=GAM{j+1}.*sy;
end
end
gam = dyn_vech(GAM{1});
- for j=1:nlags,
+ for j=1:nlags
gam = [gam; vec(GAM{j+1})];
end
end
diff --git a/matlab/get_Hessian.m b/matlab/get_Hessian.m
index a42b3c812..a591644ff 100644
--- a/matlab/get_Hessian.m
+++ b/matlab/get_Hessian.m
@@ -128,13 +128,13 @@ function [Hess] = get_Hessian(T,R,Q,H,P,Y,DT,DYss,DOm,DH,DP,D2T,D2Yss,D2Om,D2H,D
t = t+1;
v = Y(:,t)-a(mf);
tmp = (a+K*v);
- for ii = 1:k,
+ for ii = 1:k
Dv(:,ii) = -Da(mf,ii)-DYss(mf,ii);
dKi = DK(:,:,ii);
diFi = -iF*DF(:,:,ii)*iF;
dtmpi = Da(:,ii)+dKi*v+K*Dv(:,ii);
- for jj = 1:ii,
+ for jj = 1:ii
dFj = DF(:,:,jj);
diFj = -iF*DF(:,:,jj)*iF;
dKj = DK(:,:,jj);
@@ -191,7 +191,7 @@ end
% end of computeDKalman
-function [d2K,d2S,d2P1] = computeD2Kalman(A,dA,d2A,d2Om,P0,dP0,d2P0,DH,mf,iF,K0,dK0);
+function [d2K,d2S,d2P1] = computeD2Kalman(A,dA,d2A,d2Om,P0,dP0,d2P0,DH,mf,iF,K0,dK0)
% computes the second derivatives of the Kalman matrices
% note: A=T in main func.
diff --git a/matlab/get_new_or_existing_ei_index.m b/matlab/get_new_or_existing_ei_index.m
index 39bec99a3..e1c71f193 100644
--- a/matlab/get_new_or_existing_ei_index.m
+++ b/matlab/get_new_or_existing_ei_index.m
@@ -38,7 +38,7 @@ global estimation_info
if eval(['isempty(estimation_info.' substructure_name ')'])
indx = 1;
- return;
+ return
end
if isempty(name2) % parameter or std() statement
diff --git a/matlab/graph_decomp.m b/matlab/graph_decomp.m
index 6fae28f3b..2993699cf 100644
--- a/matlab/graph_decomp.m
+++ b/matlab/graph_decomp.m
@@ -52,7 +52,7 @@ fig_name_long = opts_decomp.fig_name;
use_shock_groups = DynareOptions.plot_shock_decomp.use_shock_groups;
screen_shocks = opts_decomp.screen_shocks;
-if use_shock_groups | comp_nbr<=18,
+if use_shock_groups | comp_nbr<=18
screen_shocks=0;
end
if use_shock_groups
@@ -94,20 +94,20 @@ if DynareOptions.TeX && any(strcmp('eps',cellstr(DynareOptions.plot_shock_decomp
fprintf(fidTeX,' \n');
end
-if opts_decomp.vintage && opts_decomp.realtime>1,
+if opts_decomp.vintage && opts_decomp.realtime>1
preamble_txt = 'Shock decomposition';
else
preamble_txt = 'Historical shock decomposition';
end
-if ~(screen_shocks && comp_nbr>18),
+if ~(screen_shocks && comp_nbr>18)
screen_shocks=0;
end
comp_nbr0=comp_nbr;
%%plot decomposition
for j=1:nvar
z1 = squeeze(z(i_var(j),:,:));
- if screen_shocks,
+ if screen_shocks
[junk, isort] = sort(mean(abs(z1(1:end-2,:)')), 'descend');
labels = char(char(shock_names(isort(1:16),:)),'Others', 'Initial values');
zres = sum(z1(isort(17:end),:),1);
@@ -153,14 +153,14 @@ for j=1:nvar
plot(ax,x(2:end),z1(end,:),'k-','LineWidth',2)
if ~isempty(SteadyState)
plot(ax,[xmin xmax],[0 0],'--','linewidth',1,'color',[0.7 0.7 0.7])
- if ymin+SteadyState(i_var(j))<0 && ymax+SteadyState(i_var(j))>0,
+ if ymin+SteadyState(i_var(j))<0 && ymax+SteadyState(i_var(j))>0
plot(ax,[xmin xmax],SteadyState(i_var(j))*[-1 -1],'k--','linewidth',1)
ytick=get(ax,'ytick');
ytick1=ytick-SteadyState(i_var(j));
ind1=min(find(ytick1>=ymin));
ind2=max(find(ytick1<=ymax));
dytick=ytick(2)-ytick(1);
- if ind1>1,
+ if ind1>1
ytick1 = [ytick1(ind1:end) ytick1(end)+dytick:dytick:ymax];
elseif ind2<length(ytick)
ytick1= [sort(ytick1(1)-dytick:-dytick:ymin) ytick1(1:ind2)];
diff --git a/matlab/graph_decomp_detail.m b/matlab/graph_decomp_detail.m
index 077653ea6..5d42d0ce1 100644
--- a/matlab/graph_decomp_detail.m
+++ b/matlab/graph_decomp_detail.m
@@ -52,7 +52,7 @@ if ~isempty(opts_decomp.type)
fig_mode = [fig_mode '_'];
end
screen_shocks = opts_decomp.screen_shocks;
-if DynareOptions.plot_shock_decomp.use_shock_groups | comp_nbr<=18,
+if DynareOptions.plot_shock_decomp.use_shock_groups | comp_nbr<=18
screen_shocks=0;
end
fig_name_long = opts_decomp.fig_name;
@@ -85,7 +85,7 @@ end
ind_yrs = find(floor(x)==x);
dind_tick = 1;
-if floor(length(ind_yrs)/3);
+if floor(length(ind_yrs)/3)
dind_tick = floor(length(ind_yrs)/3);
xind_tick = x(ind_yrs(1)):dind_tick:x(ind_yrs(end))+(length(ind_yrs)-(dind_tick*3+1));
else
@@ -112,7 +112,7 @@ if DynareOptions.TeX && any(strcmp('eps',cellstr(DynareOptions.plot_shock_decomp
fprintf(fidTeX,' \n');
end
-if opts_decomp.vintage && opts_decomp.realtime>1,
+if opts_decomp.vintage && opts_decomp.realtime>1
preamble_txt = 'Shock decomposition';
else
preamble_txt = 'Historical shock decomposition';
@@ -124,7 +124,7 @@ ntotrow = nrow;
nrow = min(ntotrow, 6);
nfigs = ceil(ntotrow/nrow);
labels = char(char(shock_names),'Initial values');
-if ~(screen_shocks && comp_nbr>18),
+if ~(screen_shocks && comp_nbr>18)
screen_shocks=0;
end
comp_nbr0=comp_nbr;
@@ -155,7 +155,7 @@ for j=1:nvar
a0=zeros(1,4);
a0(3)=inf;
a0(4)=-inf;
- for ic=1+nrow*ncol*(jf-1):min(nrow*ncol*jf,comp_nbr),
+ for ic=1+nrow*ncol*(jf-1):min(nrow*ncol*jf,comp_nbr)
i = ic-nrow*ncol*(jf-1);
zz = z1(ic,:);
zz(2,:)=z1(end,:)-zz;
@@ -195,7 +195,7 @@ for j=1:nvar
end
end
end
- for isub=1:i,
+ for isub=1:i
subplot(nrow,ncol,isub),
set(gca,'ylim',a0(3:4))
end
@@ -219,7 +219,7 @@ for j=1:nvar
end
- if nfigs>1,
+ if nfigs>1
suffix = ['_detail_' int2str(jf)];
else
suffix = ['_detail'];
diff --git a/matlab/gsa/Morris_Measure_Groups.m b/matlab/gsa/Morris_Measure_Groups.m
index dfd37bdd1..1aa387f07 100644
--- a/matlab/gsa/Morris_Measure_Groups.m
+++ b/matlab/gsa/Morris_Measure_Groups.m
@@ -44,7 +44,7 @@ function [SAmeas, OutMatrix] = Morris_Measure_Groups(NumFact, Sample, Output, p,
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-if nargin==0,
+if nargin==0
skipline()
disp('[SAmeas, OutMatrix] = Morris_Measure_Groups(NumFact, Sample, Output, p, Group);')
return
@@ -54,7 +54,7 @@ OutMatrix=[];
if nargin < 5, Group=[]; end
NumGroups = size(Group,2);
-if nargin < 4 | isempty(p),
+if nargin < 4 | isempty(p)
p = 4;
end
Delt = p/(2*p-2);
@@ -88,7 +88,7 @@ for k=1:size(Output,2)
% 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;
+ if NumGroups ~ 0
AuxFind (:,1) = A(:,j);
% AuxFind(find(A(:,j)),1)=1;
% Pippo = sum((Group - repmat(AuxFind,1,NumGroups)),1);
@@ -122,7 +122,7 @@ for k=1:size(Output,2)
% Compute Mu AbsMu and StDev
if any(any(isnan(SAmeas)))
- for j=1:NumFact,
+ for j=1:NumFact
SAm = SAmeas(j,:);
SAm = SAm(find(~isnan(SAm)));
rr=length(SAm);
diff --git a/matlab/gsa/cumplot.m b/matlab/gsa/cumplot.m
index 128e209ac..d210c81f9 100644
--- a/matlab/gsa/cumplot.m
+++ b/matlab/gsa/cumplot.m
@@ -1,4 +1,4 @@
-function h = cumplot(x);
+function h = cumplot(x)
%function h =cumplot(x)
% Written by Marco Ratto
@@ -29,6 +29,6 @@ y=[0:n n]./n;
h0 = stairs(x,y);
grid on,
-if nargout,
+if nargout
h=h0;
end
diff --git a/matlab/gsa/filt_mc_.m b/matlab/gsa/filt_mc_.m
index b6c4994d8..bf37c148b 100644
--- a/matlab/gsa/filt_mc_.m
+++ b/matlab/gsa/filt_mc_.m
@@ -57,11 +57,11 @@ skipline(2)
disp('Starting sensitivity analysis')
disp('for the fit of EACH observed series ...')
skipline()
-if ~options_.nograph,
+if ~options_.nograph
disp('Deleting old SA figures...')
a=dir([OutDir,filesep,'*.*']);
tmp1='0';
-if options_.opt_gsa.ppost,
+if options_.opt_gsa.ppost
tmp=['_rmse_post'];
else
if options_.opt_gsa.pprior
@@ -69,40 +69,40 @@ else
else
tmp=['_rmse_mc'];
end
- if options_gsa_.lik_only,
+ 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),
+for j=1:length(a)
+ if strmatch([fname_,tmp],a(j).name)
disp(a(j).name)
delete([OutDir,filesep,a(j).name])
- end,
- if strmatch([fname_,tmp1],a(j).name),
+ end
+ if strmatch([fname_,tmp1],a(j).name)
disp(a(j).name)
delete([OutDir,filesep,a(j).name])
- end,
+ end
end
disp('done !')
end
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'),
+if ~isempty(options_.mode_file)
+ load(options_.mode_file,'xparam1')
end
-if options_.opt_gsa.ppost,
+if options_.opt_gsa.ppost
c=load([fname_,'_mean.mat'],'xparam1');
xparam1_mean=c.xparam1;
clear c
-elseif ~isempty(options_.mode_file) && exist([fname_,'_mean.mat'])==2,
+elseif ~isempty(options_.mode_file) && exist([fname_,'_mean.mat'])==2
c=load([fname_,'_mean.mat'],'xparam1');
xparam1_mean=c.xparam1;
clear c
end
-if options_.opt_gsa.ppost,
+if options_.opt_gsa.ppost
fnamtmp=[fname_,'_post'];
DirectoryName = CheckPath('metropolis',M_.dname);
else
@@ -114,9 +114,9 @@ else
DirectoryName = CheckPath(['gsa' filesep 'mc'],M_.dname);
end
end
-if loadSA,
+if loadSA
tmplist =load([OutDir,filesep,fnamtmp, '.mat'],'vvarvecm');
- if isempty(fieldnames(tmplist)),
+ if isempty(fieldnames(tmplist))
disp('WARNING: cannot load results since the list of variables used is not present in the mat file')
loadSA=0;
elseif ~isequal(tmplist.vvarvecm,vvarvecm)
@@ -124,7 +124,7 @@ if loadSA,
loadSA=0;
end
end
-if ~loadSA,
+if ~loadSA
if exist('xparam1','var')
M_ = set_all_parameters(xparam1,estim_params_,M_);
ys_mode=steady_(M_,options_,oo_);
@@ -147,7 +147,7 @@ if ~loadSA,
filfilt = dir([DirectoryName filesep M_.fname '_filter_step_ahead*.mat']);
temp_smooth_file_list = dir([DirectoryName filesep M_.fname '_smooth*.mat']);
jfile=0;
- for j=1:length(temp_smooth_file_list),
+ for j=1:length(temp_smooth_file_list)
if isempty(strfind(temp_smooth_file_list(j).name,'smoothed')),
jfile=jfile+1;
filsmooth(jfile)=temp_smooth_file_list(j);
@@ -158,7 +158,7 @@ if ~loadSA,
x=[];
logpo2=[];
sto_ys=[];
- for j=1:length(filparam),
+ for j=1:length(filparam)
%load([DirectoryName filesep M_.fname '_param',int2str(j),'.mat']);
if isempty(strmatch([M_.fname '_param_irf'],filparam(j).name))
load([DirectoryName filesep filparam(j).name]);
@@ -173,7 +173,7 @@ if ~loadSA,
if options_.opt_gsa.ppost || (options_.opt_gsa.ppost==0 && options_.opt_gsa.lik_only==0)
skipline()
disp('Computing RMSE''s...')
- for i=1:size(vvarvecm,1),
+ for i=1:size(vvarvecm,1)
vj=deblank(vvarvecm(i,:));
jxj(i) = strmatch(vj,lgy_(dr_.order_var,:),'exact');
@@ -189,7 +189,7 @@ if ~loadSA,
end
y0=-yss;
nbb=0;
- for j=1:length(filfilt),
+ for j=1:length(filfilt)
load([DirectoryName filesep M_.fname '_filter_step_ahead',num2str(j),'.mat']);
nb = size(stock,4);
y0(:,:,nbb+1:nbb+nb)=y0(:,:,nbb+1:nbb+nb)+reshape(stock(1,js,1:gend,:),[length(js) gend nb]);
@@ -198,7 +198,7 @@ if ~loadSA,
end
yobs=-yss;
nbb=0;
- for j=1:length(filupdate),
+ for j=1:length(filupdate)
load([DirectoryName filesep M_.fname '_update',num2str(j),'.mat']);
nb = size(stock,3);
yobs(:,:,nbb+1:nbb+nb)=yobs(:,:,nbb+1:nbb+nb)+reshape(stock(js,1:gend,:),[length(js) gend nb]);
@@ -208,7 +208,7 @@ if ~loadSA,
y0M=mean(y0,2);
rmse_MC=zeros(nruns,length(js));
r2_MC=zeros(nruns,length(js));
- for j=1:nruns,
+ for j=1:nruns
rmse_MC(j,:) = sqrt(mean((yobs(:,istart:end,j)'-y0(:,istart:end,j)').^2));
r2_MC(j,:) = 1-mean((yobs(:,istart:end,j)'-y0(:,istart:end,j)').^2)./mean((yobs(:,istart:end,j)').^2);
end
@@ -222,7 +222,7 @@ if ~loadSA,
end
clear stock_filter;
end
- for j=1:nruns,
+ for j=1:nruns
lnprior(j,1) = priordens(x(j,:)',bayestopt_.pshape,bayestopt_.p6,bayestopt_.p7,bayestopt_.p3,bayestopt_.p4);
end
likelihood=logpo2(:)-lnprior(:);
@@ -338,12 +338,12 @@ if ~options_.opt_gsa.ppost && options_.opt_gsa.lik_only
mcf_analysis(x, ilik(1:nfilt), ilik(nfilt+1:end), options_mcf, options_);
else
- if options_.opt_gsa.ppost,
+ if options_.opt_gsa.ppost
rmse_txt=rmse_pmean;
r2_txt=r2_pmean;
else
- if options_.opt_gsa.pprior || ~exist('rmse_pmean'),
- if exist('rmse_mode'),
+ if options_.opt_gsa.pprior || ~exist('rmse_pmean')
+ if exist('rmse_mode')
rmse_txt=rmse_mode;
r2_txt=r2_mode;
else
@@ -356,28 +356,28 @@ else
r2_txt=r2_pmean;
end
end
- for i=1:size(vvarvecm,1),
+ for i=1:size(vvarvecm,1)
[dum, ixx(:,i)]=sort(rmse_MC(:,i));
end
PP=ones(npar+nshock,size(vvarvecm,1));
PPV=ones(size(vvarvecm,1),size(vvarvecm,1),npar+nshock);
SS=zeros(npar+nshock,size(vvarvecm,1));
- for j=1:npar+nshock,
- for i=1:size(vvarvecm,1),
+ for j=1:npar+nshock
+ for i=1:size(vvarvecm,1)
[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,
+ if H1 & H2==0
SS(j,i)=1;
- elseif H1==0,
+ elseif H1==0
SS(j,i)=-1;
else
SS(j,i)=0;
end
PP(j,i)=P;
end
- for i=1:size(vvarvecm,1),
- for l=1:size(vvarvecm,1),
+ for i=1:size(vvarvecm,1)
+ for l=1:size(vvarvecm,1)
if l~=i && PP(j,i)<alpha && PP(j,l)<alpha
[H,P,KSSTAT] = smirnov(x(ixx(1:nfilt0(i),i),j),x(ixx(1:nfilt0(l),l),j), alpha);
%[H1,P1,KSSTAT1] = smirnov(x(ixx(1:nfilt0(i),i),j),x(:,j), alpha);
@@ -393,9 +393,9 @@ else
end
end
end
- if ~options_.nograph,
+ if ~options_.nograph
ifig=0;
- for i=1:size(vvarvecm,1),
+ for i=1:size(vvarvecm,1)
if options_.opt_gsa.ppost
temp_name='RMSE Posterior: Log Prior';
else
@@ -405,7 +405,7 @@ else
temp_name='RMSE MC: Log Prior';
end
end
- if mod(i,9)==1,
+ if mod(i,9)==1
ifig=ifig+1;
hh=dyn_figure(options_.nodisplay,'name',[temp_name,' ',int2str(ifig)]);
end
@@ -443,7 +443,7 @@ else
end
end
ifig=0;
- for i=1:size(vvarvecm,1),
+ for i=1:size(vvarvecm,1)
if options_.opt_gsa.ppost
temp_name='RMSE Posterior: Log Likelihood';
else
@@ -453,7 +453,7 @@ else
temp_name='RMSE MC: Log Likelihood';
end
end
- if mod(i,9)==1,
+ if mod(i,9)==1
ifig=ifig+1;
hh = dyn_figure(options_.nodisplay,'Name',[temp_name,' ',int2str(ifig)]);
end
@@ -465,7 +465,7 @@ else
h=cumplot(likelihood(ixx(nfilt0(i)+1:end,i)));
set(h,'color','red','linewidth',2)
title(vvarvecm(i,:),'interpreter','none')
- if options_.opt_gsa.ppost==0,
+ 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)
@@ -494,7 +494,7 @@ else
end
end
ifig=0;
- for i=1:size(vvarvecm,1),
+ for i=1:size(vvarvecm,1)
if options_.opt_gsa.ppost
temp_name='RMSE Posterior: Log Posterior';
else
@@ -504,7 +504,7 @@ else
temp_name='RMSE MC: Log Posterior';
end
end
- if mod(i,9)==1,
+ if mod(i,9)==1
ifig=ifig+1;
hh = dyn_figure(options_.nodisplay,'Name',[temp_name,' ',int2str(ifig)]);
end
@@ -516,7 +516,7 @@ else
h=cumplot(logpo2(ixx(nfilt0(i)+1:end,i)));
set(h,'color','red','linewidth',2)
title(vvarvecm(i,:),'interpreter','none')
- if options_.opt_gsa.ppost==0,
+ 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)
@@ -594,7 +594,7 @@ else
skipline(2)
disp('RMSE ranges after filtering:')
title_string='RMSE ranges after filtering:';
- if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior,
+ if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior
headers=strvcat('Variable','min','max','min','max','posterior mode');
headers_tex=strvcat('\text{Variable}','\text{min}','\text{max}','\text{min}','\text{max}','\text{posterior mode}');
else
@@ -602,7 +602,7 @@ else
headers_tex=strvcat('\text{Variable}','\text{min}','\text{max}','\text{min}','\text{max}','\text{posterior mean}');
end
data_mat=NaN(size(vvarvecm,1),5);
- for j=1:size(vvarvecm,1),
+ for j=1:size(vvarvecm,1)
data_mat(j,:)=[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)) ...
@@ -632,14 +632,14 @@ else
value_format = sprintf('%%%d.%df',val_width,val_precis);
header_string_format = sprintf('%%%ds',val_width);
- if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior,
+ if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior
optional_header=sprintf([label_format_leftbound,header_string_format,header_string_format,header_string_format,header_string_format],'','',['best ',num2str(pfilt*100),'% filtered'],'','remaining 90%');
else
optional_header=sprintf([label_format_leftbound,header_string_format,header_string_format,header_string_format,header_string_format],'','','best filtered','','remaining');
end
dyntable(options_,title_string,headers,vvarvecm,data_mat, 0, val_width, val_precis,optional_header);
if options_.TeX
- if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior,
+ if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior
optional_header={[' & \multicolumn{2}{c}{best ',num2str(pfilt*100),' filtered} & \multicolumn{2}{c}{remaining 90\%}\\']};
else
optional_header={[' & \multicolumn{2}{c}{best filtered} & \multicolumn{2}{c}{remaining}\\']};
@@ -668,7 +668,7 @@ else
skipline()
disp('R2 ranges after filtering:')
title_string='R2 ranges after filtering:';
- if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior,
+ if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior
headers=strvcat('Variable','min','max','min','max','posterior mode');
headers_tex=strvcat('\text{Variable}','\text{min}','\text{max}','\text{min}','\text{max}','\text{posterior mode}');
else
@@ -676,7 +676,7 @@ else
headers_tex=strvcat('\text{Variable}','\text{min}','\text{max}','\text{min}','\text{max}','\text{posterior mean}');
end
data_mat=NaN(size(vvarvecm,1),5);
- for j=1:size(vvarvecm,1),
+ for j=1:size(vvarvecm,1)
data_mat(j,:)=[min(r2_MC(ixx(1:nfilt0(j),j),j)) ...
max(r2_MC(ixx(1:nfilt0(j),j),j)) ...
min(r2_MC(ixx(nfilt0(j)+1:end,j),j)) ...
@@ -706,14 +706,14 @@ else
value_format = sprintf('%%%d.%df',val_width,val_precis);
header_string_format = sprintf('%%%ds',val_width);
- if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior,
+ if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior
optional_header=sprintf([label_format_leftbound,header_string_format,header_string_format,header_string_format,header_string_format],'','',['best ',num2str(pfilt*100),'% filtered'],'','remaining 90%');
else
optional_header=sprintf([label_format_leftbound,header_string_format,header_string_format,header_string_format,header_string_format],'','','best filtered','','remaining');
end
dyntable(options_,title_string,headers,vvarvecm,data_mat, 0, val_width, val_precis,optional_header);
if options_.TeX
- if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior,
+ if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior
optional_header={[' & \multicolumn{2}{c}{best ',num2str(pfilt*100),' filtered} & \multicolumn{2}{c}{remaining 90\%}\\']};
else
optional_header={[' & \multicolumn{2}{c}{best filtered} & \multicolumn{2}{c}{remaining}\\']};
@@ -724,13 +724,13 @@ else
%%%% R2 table
SP=zeros(npar+nshock,size(vvarvecm,1));
- for j=1: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,
+ for j=1:npar+nshock %estim_params_.np,
nsp(j)=length(find(SP(j,:)));
end
snam0=param_names(find(nsp==0),:);
@@ -783,7 +783,7 @@ else
options_mcf.param_names_tex = param_names_tex;
options_mcf.fname_ = fname_;
options_mcf.OutputDirectoryName = OutDir;
- for iy=1:size(vvarvecm,1),
+ for iy=1:size(vvarvecm,1)
options_mcf.amcf_name = [asname '_' deblank(vvarvecm(iy,:)) '_map' ];
options_mcf.amcf_title = [atitle ' ' deblank(vvarvecm(iy,:))];
options_mcf.beha_title = ['better fit of ' deblank(vvarvecm(iy,:))];
@@ -791,21 +791,21 @@ else
options_mcf.title = ['the fit of ' deblank(vvarvecm(iy,:))];
mcf_analysis(x, ixx(1:nfilt0(iy),iy), ixx(nfilt0(iy)+1:end,iy), options_mcf, options_);
end
- for iy=1:size(vvarvecm,1),
+ for iy=1:size(vvarvecm,1)
ipar = find(any(squeeze(PPV(iy,:,:))<alpha));
- for ix=1:ceil(length(ipar)/5),
+ for ix=1:ceil(length(ipar)/5)
hh = dyn_figure(options_.nodisplay,'name',[temp_name,' observed variable ',deblank(vvarvecm(iy,:))]);
- for j=1+5*(ix-1):min(length(ipar),5*ix),
+ for j=1+5*(ix-1):min(length(ipar),5*ix)
subplot(2,3,j-5*(ix-1))
%h0=cumplot(x(:,nsnam(j)+nshock));
h0=cumplot(x(:,ipar(j)));
set(h0,'color',[0 0 0])
hold on,
iobs=find(squeeze(PPV(iy,:,ipar(j)))<alpha);
- for i=1:size(vvarvecm,1),
+ for i=1: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)));
- if any(iobs==i) || i==iy,
+ if any(iobs==i) || i==iy
h0=cumplot(x(ixx(1:nfilt0(i),i),ipar(j)));
if ~isoctave
hcmenu = uicontextmenu;
@@ -858,9 +858,9 @@ else
end
% now I plot by individual parameters
- for ix=1:ceil(length(nsnam)/5),
+ for ix=1:ceil(length(nsnam)/5)
hh = dyn_figure(options_.nodisplay,'name',[temp_name,' estimated params and shocks ',int2str(ix)]);
- for j=1+5*(ix-1):min(size(snam2,1),5*ix),
+ 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)));
@@ -869,10 +869,10 @@ else
npx=find(SP(nsnam(j),:)==0);
%a0=jet(nsp(nsnam(j)));
% a0=a00(np,:);
- for i=1:size(vvarvecm,1),
+ for i=1: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)));
- if any(npx==i),
+ if any(npx==i)
h0=cumplot(x(ixx(1:nfilt0(i),i),nsnam(j))*NaN);
else
h0=cumplot(x(ixx(1:nfilt0(i),i),nsnam(j)));
diff --git a/matlab/gsa/gsa_plotmatrix.m b/matlab/gsa/gsa_plotmatrix.m
index 9c9aee99f..7b6e44ded 100644
--- a/matlab/gsa/gsa_plotmatrix.m
+++ b/matlab/gsa/gsa_plotmatrix.m
@@ -65,18 +65,18 @@ switch type
end
-if isempty(x),
+if isempty(x)
disp('Empty parameter set!')
return
end
-for j=1:length(varargin),
+for j=1:length(varargin)
jcol(j)=strmatch(varargin{j},bayestopt_.name,'exact');
end
[H,AX,BigA,P,PAx]=plotmatrix(x(:,jcol));
-for j=1:length(varargin),
+for j=1:length(varargin)
% axes(AX(1,j)), title(varargin{j})
% axes(AX(j,1)), ylabel(varargin{j})
% set(AX(1,j),'title',varargin{j}),
@@ -84,15 +84,15 @@ for j=1:length(varargin),
set(get(AX(end,j),'xlabel'),'string',varargin{j})
end
-if options_.opt_gsa.pprior==0,
+if options_.opt_gsa.pprior==0
xparam1=xparam1(jcol);
- for j=1:length(varargin),
- for i=1:j-1,
- axes(AX(j,i)),
+ for j=1:length(varargin)
+ for i=1:j-1
+ axes(AX(j,i))
hold on, plot(xparam1(i),xparam1(j),'*r')
end
- for i=j+1:length(varargin),
- axes(AX(j,i)),
+ for i=j+1:length(varargin)
+ axes(AX(j,i))
hold on, plot(xparam1(i),xparam1(j),'*r')
end
end
diff --git a/matlab/gsa/gsa_skewness.m b/matlab/gsa/gsa_skewness.m
index b5af1c6ce..24ced8013 100644
--- a/matlab/gsa/gsa_skewness.m
+++ b/matlab/gsa/gsa_skewness.m
@@ -1,4 +1,4 @@
-function s=gsa_skewness(y),
+function s=gsa_skewness(y)
% Written by Marco Ratto
% Joint Research Centre, The European Commission,
diff --git a/matlab/gsa/gsa_speed.m b/matlab/gsa/gsa_speed.m
index 9fce2e94b..fbbf58e74 100644
--- a/matlab/gsa/gsa_speed.m
+++ b/matlab/gsa/gsa_speed.m
@@ -1,4 +1,4 @@
-function [tadj, iff] = gsa_speed(A,B,mf,p),
+function [tadj, iff] = gsa_speed(A,B,mf,p)
% [tadj, iff] = gsa_speed(A,B,mf,p),
%
% Written by Marco Ratto
@@ -33,7 +33,7 @@ tadj=iff;
disp('Computing speed of adjustement ...')
h = dyn_waitbar(0,'Speed of adjustement...');
-for i=1:nrun,
+for i=1:nrun
irf=zeros(nvar,nshock);
a=squeeze(A(:,:,i));
b=squeeze(B(:,:,i));
diff --git a/matlab/gsa/log_trans_.m b/matlab/gsa/log_trans_.m
index d1a028e65..f31b434d3 100644
--- a/matlab/gsa/log_trans_.m
+++ b/matlab/gsa/log_trans_.m
@@ -22,13 +22,13 @@ function [yy, xdir, isig, lam]=log_trans_(y0,xdir0,isig,lam)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-if nargin==4,
+if nargin==4
% inverse transformation
yy = (exp(y0)-lam)*isig;
return
end
-if nargin==1,
+if nargin==1
xdir0='';
end
f=@(lam,y)gsa_skewness(log(y+lam));
@@ -39,8 +39,9 @@ if ~(max(y0)<0 | min(y0)>0)
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);
+ 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);
@@ -68,7 +69,8 @@ else
%yy=log(y0);
xdir=[xdir0,'_log'];
end
- try lam=fzero(f,[-min(y0)+10*eps -min(y0)+median(y0)],[],y0);
+ 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);
diff --git a/matlab/gsa/map_calibration.m b/matlab/gsa/map_calibration.m
index 712d4572f..8a1729f0f 100644
--- a/matlab/gsa/map_calibration.m
+++ b/matlab/gsa/map_calibration.m
@@ -58,10 +58,10 @@ options_mcf.OutputDirectoryName = OutputDirectoryName;
skipline()
disp('Sensitivity analysis for calibration criteria')
-if DynareOptions.opt_gsa.ppost,
+if DynareOptions.opt_gsa.ppost
filetoload=dir([Model.dname filesep 'metropolis' filesep fname_ '_param_irf*.mat']);
lpmat=[];
- for j=1:length(filetoload),
+ for j=1:length(filetoload)
load([Model.dname filesep 'metropolis' filesep fname_ '_param_irf',int2str(j),'.mat'])
lpmat = [lpmat; stock];
clear stock
@@ -89,34 +89,34 @@ nbr_moment_restrictions = size(DynareOptions.endogenous_prior_restrictions.momen
if init
mat_irf=cell(nbr_irf_restrictions,1);
- for ij=1:nbr_irf_restrictions,
+ for ij=1:nbr_irf_restrictions
mat_irf{ij}=NaN(Nsam,length(DynareOptions.endogenous_prior_restrictions.irf{ij,3}));
end
mat_moment=cell(nbr_moment_restrictions,1);
- for ij=1:nbr_moment_restrictions,
+ for ij=1:nbr_moment_restrictions
mat_moment{ij}=NaN(Nsam,length(DynareOptions.endogenous_prior_restrictions.moment{ij,3}));
end
irestrictions = [1:Nsam];
h = dyn_waitbar(0,'Please wait...');
- for j=1:Nsam,
+ for j=1:Nsam
Model = set_all_parameters(lpmat(j,:)',EstimatedParameters,Model);
- if nbr_moment_restrictions,
+ if nbr_moment_restrictions
[Tt,Rr,SteadyState,info,Model,DynareOptions,DynareResults] = dynare_resolve(Model,DynareOptions,DynareResults);
else
[Tt,Rr,SteadyState,info,Model,DynareOptions,DynareResults] = dynare_resolve(Model,DynareOptions,DynareResults,'restrict');
end
- if info(1)==0,
+ if info(1)==0
[info, info_irf, info_moment, data_irf, data_moment]=endogenous_prior_restrictions(Tt,Rr,Model,DynareOptions,DynareResults);
if ~isempty(info_irf)
- for ij=1:nbr_irf_restrictions,
+ for ij=1:nbr_irf_restrictions
mat_irf{ij}(j,:)=data_irf{ij}(:,2)';
end
indx_irf(j,:)=info_irf(:,1);
end
if ~isempty(info_moment)
- for ij=1:nbr_moment_restrictions,
+ for ij=1:nbr_moment_restrictions
mat_moment{ij}(j,:)=data_moment{ij}(:,2)';
end
indx_moment(j,:)=info_moment(:,1);
@@ -136,31 +136,31 @@ if init
else
load([OutputDirectoryName,filesep,fname_,'_',type,'_restrictions'],'xmat','mat_irf','mat_moment','irestrictions','indx_irf','indx_moment','endo_prior_restrictions');
end
-if ~isempty(indx_irf),
+if ~isempty(indx_irf)
skipline()
disp('Deleting old IRF calibration plots ...')
a=dir([OutputDirectoryName,filesep,fname_,'_',type,'_irf_calib*.eps']);
- for j=1:length(a),
+ for j=1:length(a)
delete([OutputDirectoryName,filesep,a(j).name]);
end
a=dir([OutputDirectoryName,filesep,fname_,'_',type,'_irf_calib*.fig']);
- for j=1:length(a),
+ for j=1:length(a)
delete([OutputDirectoryName,filesep,a(j).name]);
end
a=dir([OutputDirectoryName,filesep,fname_,'_',type,'_irf_calib*.pdf']);
- for j=1:length(a),
+ for j=1:length(a)
delete([OutputDirectoryName,filesep,a(j).name]);
end
a=dir([OutputDirectoryName,filesep,fname_,'_',type,'_irf_restrictions.eps']);
- for j=1:length(a),
+ for j=1:length(a)
delete([OutputDirectoryName,filesep,a(j).name]);
end
a=dir([OutputDirectoryName,filesep,fname_,'_',type,'_irf_restrictions.fig']);
- for j=1:length(a),
+ for j=1:length(a)
delete([OutputDirectoryName,filesep,a(j).name]);
end
a=dir([OutputDirectoryName,filesep,fname_,'_',type,'_irf_restrictions.pdf']);
- for j=1:length(a),
+ for j=1:length(a)
delete([OutputDirectoryName,filesep,a(j).name]);
end
disp('done !')
@@ -190,19 +190,19 @@ if ~isempty(indx_irf),
iplot_indx = ones(size(plot_indx));
indx_irf = indx_irf(irestrictions,:);
- if ~DynareOptions.nograph,
+ if ~DynareOptions.nograph
h1=dyn_figure(DynareOptions.nodisplay,'name',[type ' evaluation of irf restrictions']);
nrow=ceil(sqrt(nbr_irf_couples));
ncol=nrow;
- if nrow*(nrow-1)>nbr_irf_couples,
+ if nrow*(nrow-1)>nbr_irf_couples
ncol=nrow-1;
end
end
- for ij=1:nbr_irf_restrictions,
+ for ij=1:nbr_irf_restrictions
mat_irf{ij}=mat_irf{ij}(irestrictions,:);
irf_matrix{plot_indx(ij)} = [irf_matrix{plot_indx(ij)} mat_irf{ij}];
indx_irf_matrix(:,plot_indx(ij)) = indx_irf_matrix(:,plot_indx(ij)) + indx_irf(:,ij);
- for ik=1:size(mat_irf{ij},2),
+ for ik=1:size(mat_irf{ij},2)
[Mean,Median,Var,HPD,Distrib] = ...
posterior_moments(mat_irf{ij}(:,ik),0,DynareOptions.mh_conf_sig);
irf_mean{plot_indx(ij)} = [irf_mean{plot_indx(ij)}; Mean];
@@ -213,12 +213,12 @@ if ~isempty(indx_irf),
end
leg = num2str(endo_prior_restrictions.irf{ij,3}(1));
aleg = num2str(endo_prior_restrictions.irf{ij,3}(1));
- if size(mat_irf{ij},2)>1,
+ if size(mat_irf{ij},2)>1
leg = [leg,':' ,num2str(endo_prior_restrictions.irf{ij,3}(end))];
aleg = [aleg,'-' ,num2str(endo_prior_restrictions.irf{ij,3}(end))];
iplot_indx(ij)=0;
end
- if ~DynareOptions.nograph && length(time_matrix{plot_indx(ij)})==1,
+ if ~DynareOptions.nograph && length(time_matrix{plot_indx(ij)})==1
set(0,'currentfigure',h1),
subplot(nrow,ncol, plot_indx(ij)),
hc = cumplot(mat_irf{ij}(:,ik));
@@ -267,9 +267,9 @@ if ~isempty(indx_irf),
% stab_map_1(xmat, indx1, indx2, aname, 1, indplot, OutputDirectoryName,[],atitle);
% end
end
- for ij=1:nbr_irf_couples,
- if length(time_matrix{ij})>1,
- if ~DynareOptions.nograph,
+ for ij=1:nbr_irf_couples
+ if length(time_matrix{ij})>1
+ if ~DynareOptions.nograph
set(0,'currentfigure',h1);
subplot(nrow,ncol, ij)
itmp = (find(plot_indx==ij));
@@ -277,7 +277,7 @@ if ~isempty(indx_irf),
a=axis;
delete(htmp);
tmp=[];
- for ir=1:length(itmp),
+ for ir=1:length(itmp)
for it=1:length(endo_prior_restrictions.irf{itmp(ir),3})
temp_index = find(time_matrix{ij}==endo_prior_restrictions.irf{itmp(ir),3}(it));
tmp(temp_index,:) = endo_prior_restrictions.irf{itmp(ir),4};
@@ -293,14 +293,14 @@ if ~isempty(indx_irf),
plot(time_matrix{ij},irf_median{ij},'k','linewidth',2)
plot(time_matrix{ij},[irf_distrib{ij}],'k-')
plot(a(1:2),[0 0],'r')
- hold off,
+ hold off
axis([max(1,a(1)) a(2:4)])
- box on,
+ box on
%set(gca,'xtick',sort(time_matrix{ij}))
itmp = min(itmp);
title([endo_prior_restrictions.irf{itmp,1},' vs ',endo_prior_restrictions.irf{itmp,2}],'interpreter','none'),
end
- if any(iplot_indx.*plot_indx==ij),
+ if any(iplot_indx.*plot_indx==ij)
% MCF of the couples with logical AND
itmp = min(find(plot_indx==ij));
indx1 = find(indx_irf_matrix(:,ij)==0);
@@ -324,7 +324,7 @@ if ~isempty(indx_irf),
end
end
end
- if ~DynareOptions.nograph,
+ if ~DynareOptions.nograph
dyn_saveas(h1,[OutputDirectoryName,filesep,fname_,'_',type,'_irf_restrictions'],DynareOptions.nodisplay,DynareOptions.graph_format);
create_TeX_loader(DynareOptions,[OutputDirectoryName,filesep,fname_,'_',type,'_irf_restrictions'],[type ' evaluation of irf restrictions'],'irf_restrictions',type,DynareOptions.figures.textwidth*min(ij/ncol,1))
end
@@ -335,27 +335,27 @@ if ~isempty(indx_moment)
skipline()
disp('Deleting old MOMENT calibration plots ...')
a=dir([OutputDirectoryName,filesep,fname_,'_',type,'_moment_calib*.eps']);
- for j=1:length(a),
+ for j=1:length(a)
delete([OutputDirectoryName,filesep,a(j).name]);
end
a=dir([OutputDirectoryName,filesep,fname_,'_',type,'_moment_calib*.fig']);
- for j=1:length(a),
+ for j=1:length(a)
delete([OutputDirectoryName,filesep,a(j).name]);
end
a=dir([OutputDirectoryName,filesep,fname_,'_',type,'_moment_calib*.pdf']);
- for j=1:length(a),
+ for j=1:length(a)
delete([OutputDirectoryName,filesep,a(j).name]);
end
a=dir([OutputDirectoryName,filesep,fname_,'_',type,'_moment_restrictions.eps']);
- for j=1:length(a),
+ for j=1:length(a)
delete([OutputDirectoryName,filesep,a(j).name]);
end
a=dir([OutputDirectoryName,filesep,fname_,'_',type,'_moment_restrictions.fig']);
- for j=1:length(a),
+ for j=1:length(a)
delete([OutputDirectoryName,filesep,a(j).name]);
end
a=dir([OutputDirectoryName,filesep,fname_,'_',type,'_moment_restrictions.pdf']);
- for j=1:length(a),
+ for j=1:length(a)
delete([OutputDirectoryName,filesep,a(j).name]);
end
disp('done !')
@@ -404,20 +404,20 @@ if ~isempty(indx_moment)
iplot_indx = ones(size(plot_indx));
indx_moment = indx_moment(irestrictions,:);
- if ~DynareOptions.nograph,
+ if ~DynareOptions.nograph
h2=dyn_figure(DynareOptions.nodisplay,'name',[type ' evaluation of moment restrictions']);
nrow=ceil(sqrt(nbr_moment_couples));
ncol=nrow;
- if nrow*(nrow-1)>nbr_moment_couples,
+ if nrow*(nrow-1)>nbr_moment_couples
ncol=nrow-1;
end
end
- for ij=1:nbr_moment_restrictions,
+ for ij=1:nbr_moment_restrictions
mat_moment{ij}=mat_moment{ij}(irestrictions,:);
moment_matrix{plot_indx(ij)} = [moment_matrix{plot_indx(ij)} mat_moment{ij}];
indx_moment_matrix(:,plot_indx(ij)) = indx_moment_matrix(:,plot_indx(ij)) + indx_moment(:,ij);
- for ik=1:size(mat_moment{ij},2),
+ for ik=1:size(mat_moment{ij},2)
[Mean,Median,Var,HPD,Distrib] = ...
posterior_moments(mat_moment{ij}(:,ik),0,DynareOptions.mh_conf_sig);
moment_mean{plot_indx(ij)} = [moment_mean{plot_indx(ij)}; Mean];
@@ -428,12 +428,12 @@ if ~isempty(indx_moment)
end
leg = num2str(endo_prior_restrictions.moment{ij,3}(1));
aleg = num2str(endo_prior_restrictions.moment{ij,3}(1));
- if size(mat_moment{ij},2)>1,
+ if size(mat_moment{ij},2)>1
leg = [leg,':' ,num2str(endo_prior_restrictions.moment{ij,3}(end))];
aleg = [aleg,'_' ,num2str(endo_prior_restrictions.moment{ij,3}(end))];
iplot_indx(ij)=0;
end
- if ~DynareOptions.nograph && length(time_matrix{plot_indx(ij)})==1,
+ if ~DynareOptions.nograph && length(time_matrix{plot_indx(ij)})==1
set(0,'currentfigure',h2);
subplot(nrow,ncol,plot_indx(ij)),
hc = cumplot(mat_moment{ij}(:,ik));
@@ -443,10 +443,10 @@ if ~isempty(indx_moment)
x2val=min(endo_prior_restrictions.moment{ij,4}(2),a(2));
hp = patch([x1val x2val x2val x1val],a([3 3 4 4]),'b');
set(hp,'FaceColor', [0.7 0.8 1])
- hold all,
+ hold all
hc = cumplot(mat_moment{ij}(:,ik));
set(hc,'color','k','linewidth',2)
- hold off,
+ hold off
title([endo_prior_restrictions.moment{ij,1},' vs ',endo_prior_restrictions.moment{ij,2},'(',leg,')'],'interpreter','none'),
% if ij==maxij
% leg1 = num2str(endo_prior_restrictions.moment{ij,3}(:));
@@ -477,8 +477,8 @@ if ~isempty(indx_moment)
% stab_map_1(xmat, indx1, indx2, aname, 1, indplot, OutputDirectoryName,[],atitle);
% end
end
- for ij=1:nbr_moment_couples,
- if length(time_matrix{ij})>1,
+ for ij=1:nbr_moment_couples
+ if length(time_matrix{ij})>1
if ~DynareOptions.nograph
itmp = (find(plot_indx==ij));
set(0,'currentfigure',h2);
@@ -487,7 +487,7 @@ if ~isempty(indx_moment)
a=axis;
delete(htmp);
tmp=[];
- for ir=1:length(itmp),
+ for ir=1:length(itmp)
for it=1:length(endo_prior_restrictions.moment{itmp(ir),3})
temp_index = find(time_matrix{ij}==endo_prior_restrictions.moment{itmp(ir),3}(it));
tmp(temp_index,:) = endo_prior_restrictions.moment{itmp(ir),4};
@@ -498,19 +498,19 @@ if ~isempty(indx_moment)
tmp(isinf(tmp(:,2)),2)=a(4);
hp = patch([time_matrix{ij} time_matrix{ij}(end:-1:1)],[tmp(:,1); tmp(end:-1:1,2)],'b');
set(hp,'FaceColor',[0.7 0.8 1])
- hold on,
+ hold on
plot(time_matrix{ij},[max(moment_matrix{ij})' min(moment_matrix{ij})'],'k--','linewidth',2)
plot(time_matrix{ij},moment_median{ij},'k','linewidth',2)
plot(time_matrix{ij},[moment_distrib{ij}],'k-')
plot(a(1:2),[0 0],'r')
- hold off,
+ hold off
axis(a)
- box on,
+ box on
set(gca,'xtick',sort(time_matrix{ij}))
itmp = min(itmp);
title([endo_prior_restrictions.moment{itmp,1},' vs ',endo_prior_restrictions.moment{itmp,2}],'interpreter','none'),
end
- if any(iplot_indx.*plot_indx==ij),
+ if any(iplot_indx.*plot_indx==ij)
% MCF of the couples with logical AND
itmp = min(find(plot_indx==ij));
indx1 = find(indx_moment_matrix(:,ij)==0);
@@ -534,7 +534,7 @@ if ~isempty(indx_moment)
end
end
end
- if ~DynareOptions.nograph,
+ if ~DynareOptions.nograph
dyn_saveas(h2,[OutputDirectoryName,filesep,fname_,'_',type,'_moment_restrictions'],DynareOptions.nodisplay,DynareOptions.graph_format);
create_TeX_loader(DynareOptions,[OutputDirectoryName,filesep,fname_,'_',type,'_moment_restrictions'],[type ' evaluation of moment restrictions'],'moment_restrictions',type,DynareOptions.figures.textwidth*min(ij/ncol,1))
end
diff --git a/matlab/gsa/map_ident_.m b/matlab/gsa/map_ident_.m
index 94e69f7fd..50f27cc2d 100644
--- a/matlab/gsa/map_ident_.m
+++ b/matlab/gsa/map_ident_.m
@@ -31,21 +31,21 @@ ntra = opt_gsa.morris_ntra;
itrans = opt_gsa.trans_ident;
np = estim_params_.np;
-if opt_gsa.load_ident_files,
+if opt_gsa.load_ident_files
gsa_flag=0;
else
gsa_flag=-2;
end
pnames = M_.param_names(estim_params_.param_vals(:,1),:);
- if opt_gsa.pprior,
+ if opt_gsa.pprior
filetoload=[OutputDirectoryName '/' fname_ '_prior'];
else
filetoload=[OutputDirectoryName '/' fname_ '_mc'];
end
load(filetoload,'lpmat','lpmat0','istable','T','yys','nspred','nboth','nfwrd')
-if ~isempty(lpmat0),
+if ~isempty(lpmat0)
lpmatx=lpmat0(istable,:);
else
lpmatx=[];
@@ -56,24 +56,24 @@ npT = np+nshock;
fname_ = M_.fname;
-if opt_gsa.load_ident_files==0,
+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);
- if exist('T'),
+ if exist('T')
[vdec, cc, ac] = mc_moments(T, lpmatx, oo_.dr);
else
- return,
+ return
end
- if opt_gsa.morris==2,
+ if opt_gsa.morris==2
pdraws = dynare_identification(options_.options_ident,[lpmatx lpmat(istable,:)]);
% [pdraws, TAU, GAM] = dynare_identification(options_.options_ident,[lpmatx lpmat(istable,:)]);
- if ~isempty(pdraws) && max(max(abs(pdraws-[lpmatx lpmat(istable,:)])))==0,
+ if ~isempty(pdraws) && max(max(abs(pdraws-[lpmatx lpmat(istable,:)])))==0
disp(['Sample check OK ', num2str(max(max(abs(pdraws-[lpmatx lpmat(istable,:)]))))]),
clear pdraws;
end
@@ -86,9 +86,9 @@ if opt_gsa.load_ident_files==0,
clear GAM gas
% end
end
- if opt_gsa.morris~=1 & M_.exo_nbr>1,
+ if opt_gsa.morris~=1 & M_.exo_nbr>1
ifig=0;
- for j=1:M_.exo_nbr,
+ for j=1:M_.exo_nbr
if mod(j,6)==1
hh=dyn_figure(options_.nodisplay,'name',['Variance decomposition shocks']);
ifig=ifig+1;
@@ -101,13 +101,13 @@ if opt_gsa.load_ident_files==0,
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),
+ 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,
+ if mod(j,6)==0 | j==M_.exo_nbr
dyn_saveas(hh,[OutputDirectoryName,'/',fname_,'_vdec_exo_',int2str(ifig)],options_.nodisplay,options_.graph_format);
create_TeX_loader(options_,[OutputDirectoryName,'/',fname_,'_vdec_exo_',int2str(ifig)],ifig,['Variance decomposition shocks'],'vdec_exo',options_.figures.textwidth*min(iplo/3,1))
end
@@ -135,24 +135,24 @@ if opt_gsa.load_ident_files==0,
% 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;
- if ~isempty(lpmatx),
+ if ~isempty(lpmatx)
set_shocks_param(lpmatx(1,:));
end
A(:,:,1)=[Aa, triu(Bb*M_.Sigma_e*Bb')];
- for j=2:length(istable),
+ 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, M_.exo_nbr);
% bayestopt_.restrict_var_list, ...
% bayestopt_.restrict_columns, ...
% bayestopt_.restrict_aux, M_.exo_nbr);
- if ~isempty(lpmatx),
+ if ~isempty(lpmatx)
set_shocks_param(lpmatx(j,:));
end
A(:,:,j)=[Aa, triu(Bb*M_.Sigma_e*Bb')];
end
- clear T;
- clear lpmatx;
+ clear T
+ clear lpmatx
[nr,nc,nn]=size(A);
io=bayestopt_.mf2;
@@ -167,7 +167,7 @@ if opt_gsa.load_ident_files==0,
[yt, j0]=teff(A,Nsam,istable);
yt = [yys yt];
- if opt_gsa.morris==2,
+ 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)')));
@@ -175,7 +175,7 @@ if opt_gsa.load_ident_files==0,
clear TAU A
% end
else
- clear A,
+ clear A
end
% [yt1, j01]=teff(T1,Nsam,istable);
% [yt2, j02]=teff(T2,Nsam,istable);
@@ -184,7 +184,7 @@ if opt_gsa.load_ident_files==0,
% yt=[yt1 yt2 ytr];
save([OutputDirectoryName,'/',fname_,'_main_eff.mat'],'ac','cc','vdec','yt','mss')
else
- if opt_gsa.morris==2,
+ if opt_gsa.morris==2
% [pdraws, TAU, GAM] = dynare_identification([1:npT]); %,[lpmatx lpmat(istable,:)]);
% [pdraws, TAU, GAM] = dynare_identification(options_.options_ident);
pdraws = dynare_identification(options_.options_ident);
@@ -205,12 +205,12 @@ end
% end
% yt = yt(:,j0);
-if opt_gsa.morris==1,
+if opt_gsa.morris==1
%OutputDir = CheckPath('gsa/screen');
- if ~isempty(vdec),
- if opt_gsa.load_ident_files==0,
+ if ~isempty(vdec)
+ if opt_gsa.load_ident_files==0
SAMorris = [];
- for i=1:size(vdec,2),
+ for i=1:size(vdec,2)
[SAmeas, SAMorris(:,:,i)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], vdec(:,i),nliv);
end
SAvdec = squeeze(SAMorris(:,1,:))';
@@ -227,7 +227,7 @@ if opt_gsa.morris==1,
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,
+ for ip=1:npT
text(ip,-2,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
end
xlabel(' ')
@@ -310,10 +310,10 @@ if opt_gsa.morris==1,
% end
- if opt_gsa.load_ident_files==0,
+ if opt_gsa.load_ident_files==0
SAMorris = [];
ccac = [mss cc ac];
- for i=1:size(ccac,2),
+ for i=1:size(ccac,2)
[SAmeas, SAMorris(:,:,i)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], [ccac(:,i)],nliv);
end
SAcc = squeeze(SAMorris(:,1,:))';
@@ -333,7 +333,7 @@ if opt_gsa.morris==1,
ydum = get(gca,'ylim');
set(gca,'ylim',[0 1])
set(gca,'position',[0.13 0.2 0.775 0.7])
- for ip=1:npT,
+ for ip=1:npT
text(ip,-0.02,bayestopt_.name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
end
xlabel(' ')
@@ -694,9 +694,9 @@ if opt_gsa.morris==1,
% end
- if opt_gsa.load_ident_files==0,
+ if opt_gsa.load_ident_files==0
SAMorris = [];
- for j=1:j0,
+ for j=1:j0
[SAmeas, SAMorris(:,:,j)] = Morris_Measure_Groups(npT, [lpmat0 lpmat], yt(:,j),nliv);
end
@@ -730,7 +730,7 @@ if opt_gsa.morris==1,
set(gca,'ylim',[0 1])
set(gca,'position',[0.13 0.2 0.775 0.7])
xlabel(' ')
- for ip=1:npT,
+ 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
@@ -777,12 +777,12 @@ if opt_gsa.morris==1,
% eval(['print -depsc2 ' OutputDirectoryName '/' fname_ '_morris_redform']);
% eval(['print -dpdf ' OutputDirectoryName '/' fname_ '_morris_redform']);
-elseif opt_gsa.morris==3,
+elseif opt_gsa.morris==3
return
np=estim_params_.np;
na=(4*np+1)*opt_gsa.Nsam;
- for j=1:j0,
+ 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)));
@@ -793,10 +793,9 @@ elseif opt_gsa.morris==3,
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),
+ 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,:));
@@ -811,10 +810,10 @@ elseif opt_gsa.morris==3,
ee=ee([end:-1:1])./j0;
i0=length(find(ee>0.01));
v0=v0(:,[end:-1:1]);
- for j=1:i0,
+ 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,
+ 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')
@@ -825,24 +824,24 @@ elseif opt_gsa.morris==3,
er=er([end:-1:1])./j0;
ir0=length(find(er>0.01));
vr=vr(:,[end:-1:1]);
- for j=1:ir0,
+ 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,
+ for j=1:ir0
ys_pcr(j,:)=yd_pcr(j,:)./max(yd_pcr(j,:));
- end,
+ 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,
+elseif opt_gsa.morris==2 % ISKREV staff
+ return
-else, % main effects analysis
+else % main effects analysis
- if itrans==0,
+ if itrans==0
fsuffix = '';
- elseif itrans==1,
+ elseif itrans==1
fsuffix = '_log';
else
fsuffix = '_rank';
@@ -850,7 +849,7 @@ else, % main effects analysis
imap=[1:npT];
- if isempty(lpmat0),
+ if isempty(lpmat0)
x0=lpmat(istable,:);
else
@@ -989,7 +988,7 @@ else, % main effects analysis
% end
% end
- if opt_gsa.load_ident_files==0,
+ if opt_gsa.load_ident_files==0
try
EET=load([OutputDirectoryName,'/SCREEN/',fname_,'_morris_IDE'],'SAcc','ir_cc','ic_cc');
catch
@@ -1011,15 +1010,15 @@ else, % main effects analysis
% siPCA = sum(siPCA,1);
% siPCA = siPCA./max(siPCA);
SAcc=zeros(size(ccac,2),npT);
- for j=1:npca, %size(ccac,2),
- if itrans==0,
+ for j=1:npca %size(ccac,2),
+ if itrans==0
y0 = ccac(istable,j);
- elseif itrans==1,
+ elseif itrans==1
y0 = log_trans_(ccac(istable,j));
else
y0 = trank(ccac(istable,j));
end
- if ~isempty(EET),
+ if ~isempty(EET)
% imap=find(EET.SAvdec(j,:));
% [dum, isort]=sort(-EET.SAvdec(j,:));
imap=find(siPCA(j,:) >= (0.1.*max(siPCA(j,:))) );
@@ -1523,13 +1522,13 @@ else, % main effects analysis
% figure, bar(latent'*SAcc),
hh=dyn_figure(options_.nodisplay,'Name',['Identifiability indices in the ',fsuffix,' moments.']);
- bar(sum(SAcc)),
+ 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,
+ 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
diff --git a/matlab/gsa/mc_moments.m b/matlab/gsa/mc_moments.m
index b2ea93538..4fe89cee9 100644
--- a/matlab/gsa/mc_moments.m
+++ b/matlab/gsa/mc_moments.m
@@ -27,10 +27,10 @@ global options_ M_ estim_params_ oo_
cc = zeros(nobs,nobs,nsam);
ac = zeros(nobs,nobs*options_.ar,nsam);
- for j=1:nsam,
+ for j=1:nsam
oo_.dr.ghx = mm(:, [1:(nc1-M_.exo_nbr)],j);
oo_.dr.ghu = mm(:, [(nc1-M_.exo_nbr+1):end], j);
- if ~isempty(ss),
+ if ~isempty(ss)
set_shocks_param(ss(j,:));
end
[vdec(:,:,j), corr, autocorr, z, zz] = th_moments(oo_.dr,options_.varobs);
diff --git a/matlab/gsa/mcf_analysis.m b/matlab/gsa/mcf_analysis.m
index e15bdea55..a8661722c 100644
--- a/matlab/gsa/mcf_analysis.m
+++ b/matlab/gsa/mcf_analysis.m
@@ -42,7 +42,7 @@ nobeha_title = options_mcf.nobeha_title;
title = options_mcf.title;
fname_ = options_mcf.fname_;
xparam1=[];
-if isfield(options_mcf,'xparam1'),
+if isfield(options_mcf,'xparam1')
xparam1=options_mcf.xparam1;
end
OutputDirectoryName = options_mcf.OutputDirectoryName;
@@ -67,14 +67,14 @@ if ~isempty(indmcf)
end
-if length(ibeha)>10 && length(inobeha)>10,
+if length(ibeha)>10 && length(inobeha)>10
indcorr1 = stab_map_2(lpmat(ibeha,:),alpha2, pvalue_corr, beha_title);
indcorr2 = stab_map_2(lpmat(inobeha,:),alpha2, pvalue_corr, nobeha_title);
indcorr = union(indcorr1(:), indcorr2(:));
indcorr = indcorr(~ismember(indcorr(:),indmcf));
indmcf = [indmcf(:); indcorr(:)];
end
-if ~isempty(indmcf) && ~DynareOptions.nograph,
+if ~isempty(indmcf) && ~DynareOptions.nograph
skipline()
xx=[];
if ~ isempty(xparam1), xx=xparam1(indmcf); end
diff --git a/matlab/gsa/myboxplot.m b/matlab/gsa/myboxplot.m
index b71ad169e..39eba8960 100644
--- a/matlab/gsa/myboxplot.m
+++ b/matlab/gsa/myboxplot.m
@@ -35,7 +35,7 @@ if notched==1, notched=0.25; end
a=1-notched;
% ## figure out how many data sets we have
-if iscell(data),
+if iscell(data)
nc = length(data);
else
% if isvector(data), data = data(:); end
@@ -172,7 +172,7 @@ else
% % % % % outliers2_y, outliers2_x, [symbol(2),"r;;"]);
end
-if nargout,
+if nargout
sout=s;
end
% % % endfunction
\ No newline at end of file
diff --git a/matlab/gsa/myprctilecol.m b/matlab/gsa/myprctilecol.m
index a71d21687..21c139d6b 100644
--- a/matlab/gsa/myprctilecol.m
+++ b/matlab/gsa/myprctilecol.m
@@ -1,4 +1,4 @@
-function y = myprctilecol(x,p);
+function y = myprctilecol(x,p)
% Written by Marco Ratto
% Joint Research Centre, The European Commission,
@@ -27,9 +27,9 @@ xx = sort(x);
if m==1 | n==1
m = max(m,n);
- if m == 1,
+ if m == 1
y = x*ones(length(p),1);
- return;
+ return
end
n = 1;
q = 100*(0.5:m - 0.5)./m;
diff --git a/matlab/gsa/pick.m b/matlab/gsa/pick.m
index 87838acc5..8a3f53a55 100644
--- a/matlab/gsa/pick.m
+++ b/matlab/gsa/pick.m
@@ -55,7 +55,7 @@ dy=get(gca,'ylim');
pos=get(gca,'position');
scalex=dx(2)-dx(1);
scaley=dy(2)-dy(1);
-if length(X)>1,
+if length(X)>1
K = dsearchn([(Y./scaley)' (X./scalex)'],[y/scaley x/scalex]);
else
az=get(gca,'children');
@@ -68,7 +68,7 @@ KK=K;
set(button1,'Label',['Save ',num2str(K)],'Callback',['scatter_callback(',num2str(KK),',''save'')']);
set(button2,'Label',['Eval ',num2str(K)],'Callback',['scatter_callback(',num2str(KK),',''eval'')']);
hh=findobj(gcf,'type','axes','Tag','scatter');
-for k=1:length(hh),
+for k=1:length(hh)
axes(hh(k));
dum=get(gca,'children');
dumx=get(dum(end),'xdata');
@@ -76,7 +76,7 @@ for k=1:length(hh),
xmid=min(dumx) + 0.5*(max(dumx)-min(dumx));
hold on
plot(dumx(KK),dumy(KK),'or');
- if dumx(KK) < xmid,
+ if dumx(KK) < xmid
text(dumx(KK),dumy(KK),[' ',num2str(K)], ...
'FontWeight','Bold',...
'Color','r');
diff --git a/matlab/gsa/redform_map.m b/matlab/gsa/redform_map.m
index c7b257325..7d1b3787d 100644
--- a/matlab/gsa/redform_map.m
+++ b/matlab/gsa/redform_map.m
@@ -70,7 +70,7 @@ fname_ = M_.fname;
bounds = prior_bounds(bayestopt_, options_.prior_trunc);
-if nargin==0,
+if nargin==0
dirname='';
end
@@ -100,7 +100,7 @@ if ~exist('T')
else
load([dirname,filesep,M_.fname,'_mc'],'T');
end
- if ~exist('T'),
+ if ~exist('T')
disp('The model is too large!')
disp('Reduced form mapping stopped!')
return
@@ -114,7 +114,7 @@ adir0=pwd;
nspred=size(T,2)-M_.exo_nbr;
x0=lpmat(istable,:);
-if isempty(lpmat0),
+if isempty(lpmat0)
xx0=[];
nshocks=0;
else
@@ -123,7 +123,7 @@ else
end
[kn, np]=size(x0);
offset = length(bayestopt_.pshape)-np;
-if options_gsa_.prior_range,
+if options_gsa_.prior_range
pshape=5*(ones(np,1));
pd = [NaN(np,1) NaN(np,1) bounds.lb(offset+1:end) bounds.ub(offset+1:end)];
else
@@ -159,11 +159,11 @@ for j=1:size(anamendo,1)
disp(['[', namendo,' vs ',namexo,']'])
- if ~isempty(iexo),
+ 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 && isempty(threshold) && ~options_.nograph,
+ if (max(y0)-min(y0))>1.e-10
+ if mod(iplo,9)==0 && isempty(threshold) && ~options_.nograph
ifig=ifig+1;
hfig = dyn_figure(options_.nodisplay,'name',['Reduced Form Mapping: ', namendo,' vs shocks ',int2str(ifig)]);
iplo=0;
@@ -171,7 +171,7 @@ for j=1:size(anamendo,1)
iplo=iplo+1;
js=js+1;
xdir0 = [adir,filesep,namendo,'_vs_', namexo];
- if ilog==0 || ~isempty(threshold),
+ if ilog==0 || ~isempty(threshold)
if isempty(threshold)
if isempty(dir(xdir0))
mkdir(xdir0)
@@ -192,7 +192,7 @@ for j=1:size(anamendo,1)
if isempty(dir(xdir))
mkdir(xdir)
end
- if ~options_.nograph,
+ if ~options_.nograph
hf=dyn_figure(options_.nodisplay,'name',['Reduced Form Mapping (Monte Carlo Filtering): ',namendo,' vs ', namexo]);
hc = cumplot(y0);
a=axis; delete(hc);
@@ -226,7 +226,7 @@ for j=1:size(anamendo,1)
icheck = mcf_analysis(x0, iy, iyc, options_mcf, options_);
lpmat=x0(iy,:);
- if nshocks,
+ if nshocks
lpmat0=xx0(iy,:);
end
istable=[1:length(iy)];
@@ -235,7 +235,7 @@ for j=1:size(anamendo,1)
else
icheck=[];
end
- if isempty(icheck),
+ if isempty(icheck)
atitle0=['Monte Carlo Filtering for ',namendo,' vs ', namexo];
options_mcf.title = atitle0;
indmcf = redform_mcf(y0, x0, options_mcf, options_);
@@ -255,10 +255,10 @@ for j=1:size(anamendo,1)
silog(:,js) = redform_private(x0, y0, options_map, options_);
end
- if isempty(threshold) && ~options_.nograph,
+ if isempty(threshold) && ~options_.nograph
figure(hfig)
subplot(3,3,iplo),
- if ilog,
+ if ilog
[saso, iso] = sort(-silog(:,js));
bar([silog(iso(1:min(np,10)),js)])
logflag='log';
@@ -270,7 +270,7 @@ for j=1:size(anamendo,1)
%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),
+ 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')
@@ -283,7 +283,7 @@ for j=1:size(anamendo,1)
end
end
end
- if iplo<9 && iplo>0 && ifig && ~options_.nograph,
+ if iplo<9 && iplo>0 && ifig && ~options_.nograph
dyn_saveas(hfig,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)],options_.nodisplay,options_.graph_format);
create_TeX_loader(options_,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)],[logflag,' ',strrep(namendo,'_','\_'),' vs ',strrep(namexo,'_','\_')],['redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)],options_.figures.textwidth*min(iplo/3,1))
end
@@ -295,11 +295,11 @@ for j=1:size(anamendo,1)
skipline()
disp(['[', namendo,' vs lagged ',namlagendo,']'])
- if ~isempty(ilagendo),
+ 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 && isempty(threshold) && ~options_.nograph,
+ if (max(y0)-min(y0))>1.e-10
+ if mod(iplo,9)==0 && isempty(threshold) && ~options_.nograph
ifig=ifig+1;
hfig = dyn_figure(options_.nodisplay,'name',['Reduced Form Mapping: ' namendo,' vs lags ',int2str(ifig)]);
iplo=0;
@@ -307,7 +307,7 @@ for j=1:size(anamendo,1)
iplo=iplo+1;
js=js+1;
xdir0 = [adir,filesep,namendo,'_vs_', namlagendo];
- if ilog==0 || ~isempty(threshold),
+ if ilog==0 || ~isempty(threshold)
if isempty(threshold)
if isempty(dir(xdir0))
mkdir(xdir0)
@@ -328,7 +328,7 @@ for j=1:size(anamendo,1)
if isempty(dir(xdir))
mkdir(xdir)
end
- if ~options_.nograph,
+ if ~options_.nograph
hf=dyn_figure(options_.nodisplay,'name',['Reduced Form Mapping (Monte Carlo Filtering): ',namendo,' vs lagged ', namlagendo]);
hc = cumplot(y0);
a=axis; delete(hc);
@@ -363,7 +363,7 @@ for j=1:size(anamendo,1)
icheck = mcf_analysis(x0, iy, iyc, options_mcf, options_);
lpmat=x0(iy,:);
- if nshocks,
+ if nshocks
lpmat0=xx0(iy,:);
end
istable=[1:length(iy)];
@@ -373,7 +373,7 @@ for j=1:size(anamendo,1)
else
icheck = [];
end
- if isempty(icheck),
+ if isempty(icheck)
atitle0=['Monte Carlo Filtering for ',namendo,' vs ', namlagendo];
options_mcf.title = atitle0;
indmcf = redform_mcf(y0, x0, options_mcf, options_);
@@ -395,7 +395,7 @@ for j=1:size(anamendo,1)
if isempty(threshold) && ~options_.nograph
figure(hfig),
subplot(3,3,iplo),
- if ilog,
+ if ilog
[saso, iso] = sort(-silog(:,js));
bar([silog(iso(1:min(np,10)),js)])
logflag='log';
@@ -407,11 +407,11 @@ for j=1:size(anamendo,1)
%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),
+ 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,
+ if iplo==9
dyn_saveas(hfig,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)],options_.nodisplay,options_.graph_format);
create_TeX_loader(options_,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)],[logflag,' ',strrep(namendo,'_','\_'),' vs ',strrep(namlagendo,'_','\_'),'(-1)'],['redform_', namendo,'_vs_lags_',logflag,':',num2str(ifig)],1)
end
@@ -420,14 +420,14 @@ for j=1:size(anamendo,1)
end
end
end
- if iplo<9 && iplo>0 && ifig && ~options_.nograph,
+ if iplo<9 && iplo>0 && ifig && ~options_.nograph
dyn_saveas(hfig,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)],options_.nodisplay,options_.graph_format);
create_TeX_loader(options_,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)],[logflag,' ',strrep(namendo,'_','\_'),' vs ',strrep(namlagendo,'_','\_'),'(-1)'],['redform_', namendo,'_vs_lags_',logflag,':',num2str(ifig)],options_.figures.textwidth*min(iplo/3,1));
end
end
-if isempty(threshold) && ~options_.nograph,
- if ilog==0,
+if isempty(threshold) && ~options_.nograph
+ if ilog==0
hfig=dyn_figure(options_.nodisplay,'name','Reduced Form GSA'); %bar(si)
% boxplot(si','whis',10,'symbol','r.')
myboxplot(si',[],'.',[],10)
@@ -436,7 +436,7 @@ if isempty(threshold) && ~options_.nograph,
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,
+ for ip=1:np
text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
end
title('Reduced form GSA')
@@ -452,7 +452,7 @@ if isempty(threshold) && ~options_.nograph,
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,
+ 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')
@@ -472,20 +472,20 @@ pnames = options_map.param_names;
pd = options_map.pd;
pshape = options_map.pshape;
xdir = options_map.OutputDirectoryName;
-if options_map.prior_range,
- for j=1:np,
+if options_map.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
-if ilog,
+if ilog
fname=[xdir filesep options_map.fname_ '_' options_map.amap_name '_log'];
else
fname=[xdir filesep options_map.fname_ '_' options_map.amap_name];
end
-if iload==0,
+if iload==0
if isempty(dir(xdir))
mkdir(xdir)
end
@@ -497,7 +497,7 @@ if iload==0,
% gsa_ = gsa_sdp(y0(1:nest), x0(1:nest,:), 2, [],[-1 -1 -1 -1 -1 0],[],0,[fname,'_est'], pnames);
[ys,is] = sort(y0);
istep = ceil(nrun/nest);
- if istep>1,
+ if istep>1
iest = is(floor(istep/2):istep:end);
nest = length(iest);
irest = is(setdiff([1:nrun],[floor(istep/2):istep:nrun]));
@@ -508,7 +508,7 @@ if iload==0,
si=nan(np,1);
return
end
- if ~ismember(irest(end),ifit),
+ if ~ismember(irest(end),ifit)
ifit = union(ifit, irest(end));
end
nfit=length(ifit);
@@ -517,21 +517,21 @@ if iload==0,
% nfit=nest;
ipred = setdiff([1:nrun],ifit);
- if ilog,
+ if ilog
[y1, tmp, isig, lam] = log_trans_(y0(iest));
y1 = log(y0*isig+lam);
end
- if ~options_.nograph,
+ if ~options_.nograph
hfig=dyn_figure(options_.nodisplay,'name',options_map.figtitle);
subplot(221)
- if ilog,
- hist(y1,30),
+ if ilog
+ hist(y1,30)
else
- hist(y0,30),
+ hist(y0,30)
end
title(options_map.title,'interpreter','none')
subplot(222)
- if ilog,
+ if ilog
hc = cumplot(y1);
else
hc = cumplot(y0);
@@ -541,7 +541,7 @@ if iload==0,
end
gsa0 = ss_anova(y0(iest), x0(iest,:), 1);
- if ilog,
+ if ilog
[gsa22, gsa1, gsax] = ss_anova_log(y1(iest), x0(iest,:), isig, lam, gsa0);
end
% if (gsa1.out.bic-gsa0.out.bic) < 10,
@@ -551,7 +551,7 @@ if iload==0,
% y0=y1;
% ilog=1;
% end
-if nfit>nest,
+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);
nvr = gsa0.nvr*nest^3/nfit^3;
nvr(gsa0.stat<2) = gsa0.nvr(gsa0.stat<2)*nest^5/nfit^5;
@@ -602,13 +602,13 @@ end
save([fname,'_map.mat'],'gsa_')
[sidum, iii]=sort(-gsa_.si);
gsa_.x0=x00(ifit,:);
- if ~options_.nograph,
+ if ~options_.nograph
hmap=gsa_sdp_plot(gsa_,[fname '_map'],pnames,iii(1:min(12,np)));
set(hmap,'name',options_map.amap_title);
end
gsa_.x0=x0(ifit,:);
% copyfile([fname,'_est.mat'],[fname,'.mat'])
- if ~options_.nograph,
+ if ~options_.nograph
figure(hfig);
subplot(223),
plot(y0(ifit),[gsa_.fit y0(ifit)],'.'),
@@ -621,8 +621,8 @@ end
% r2 = gsa_.r2;
% end
title(['Learning sample fit - R2=' num2str(r2,2)],'interpreter','none')
- if nfit<nrun,
- if ilog,
+ if nfit<nrun
+ if ilog
yf = ss_anova_fcast(x0(ipred,:), gsa1);
yf = log_trans_(yf,'',isig,lam)+ss_anova_fcast(x0(ipred,:), gsax);
else
@@ -645,7 +645,7 @@ else
% gsa_ = gsa_sdp_dyn(y0, x0, 0, [],[],[],0,fname, pnames);
% gsa_ = gsa_sdp(y0, x0, 0, [],[],[],0,fname, pnames);
load([fname,'_map.mat'],'gsa_')
- if ~options_.nograph,
+ if ~options_.nograph
yf = ss_anova_fcast(x0, gsa_);
hfig=dyn_figure(options_.nodisplay,'name',options_map.title);
plot(y0,[yf y0],'.'),
@@ -671,7 +671,7 @@ gsa2.f0 = mean(gsa2.fit);
gsa2.out.SSE = sum((gsa2.fit-gsa2.y).^2);
gsa2.out.bic = gsa2.out.bic-nest*log(gsa1.out.SSE)+nest*log(gsa2.out.SSE);
gsa2.r2 = 1-cov(gsa2.fit-gsa2.y)/cov(gsa2.y);
-for j=1:np,
+for j=1:np
gsa2.fs(:,j) = exp(gsa1.fs(:,j)).*mean(exp(gsa1.fit-gsa1.f(:,j)))*isig-lam*isig-gsa2.f0;
gsa2.fses(:,j) = exp(gsa1.fs(:,j)+gsa1.fses(:,j)).*mean(exp(gsa1.fit-gsa1.f(:,j)))*isig-lam*isig-gsa2.f0-gsa2.fs(:,j);
gsa2.f(:,j) = exp(gsa1.f(:,j)).*mean(exp(gsa1.fit-gsa1.f(:,j)))*isig-lam*isig-gsa2.f0;
@@ -685,14 +685,14 @@ function [gsa22, gsa1, gsax] = ss_anova_log(y,x,isig,lam,gsa0,nvrs)
[nest, np]=size(x);
-if nargin==6,
+if nargin==6
gsa1 = ss_anova(y, x, 1, 0, 2, nvrs(:,1));
else
gsa1 = ss_anova(y, x, 1);
end
gsa2 = log2level_map(gsa1, isig, lam);
-if nargin >=5 && ~isempty(gsa0),
- for j=1:np,
+if nargin >=5 && ~isempty(gsa0)
+ for j=1:np
nvr2(j) = var(diff(gsa2.fs(:,j),2));
nvr0(j) = var(diff(gsa0.fs(:,j),2));
end
@@ -702,7 +702,7 @@ if nargin >=5 && ~isempty(gsa0),
gsa1 = ss_anova(y, x, 1, 0, 2, gsa1.nvr);
gsa2 = log2level_map(gsa1, isig, lam);
end
-if nargin==6,
+if nargin==6
gsax = ss_anova(gsa2.y-gsa2.fit, x, 1, 0, 2, nvrs(:,2));
else
gsax = ss_anova(gsa2.y-gsa2.fit, x, 1);
@@ -713,7 +713,7 @@ gsa22.f0 = mean(gsa22.fit);
gsa22.out.SSE = sum((gsa22.fit-gsa22.y).^2);
gsa22.out.bic = nest*log(gsa22.out.SSE/nest) + (gsax.out.df+gsa2.out.df-1)*log(nest);
gsa22.r2 = 1-sum((gsa22.fit-gsa22.y).^2)/sum((gsa22.y-mean(gsa22.y)).^2);
-for j=1:np,
+for j=1:np
gsa22.fs(:,j) = gsa2.fs(:,j)+gsax.fs(:,j);
gsa22.fses(:,j) = gsax.fses(:,j);
gsa22.f(:,j) = gsa2.f(:,j)+gsax.f(:,j);
@@ -730,7 +730,7 @@ hfig=dyn_figure(options_.nodisplay,'name',options_mcf.amcf_title);
density] = posterior_moments(y0,1,0.9);
post_deciles = [-inf; post_deciles; inf];
-for jt=1:10,
+for jt=1:10
indy{jt}=find( (y0>post_deciles(jt)) & (y0<=post_deciles(jt+1)));
leg{jt}=[int2str(jt) '-dec'];
end
@@ -741,18 +741,18 @@ indmcf = indmcf(jtmp);
nbr_par = length(indmcf);
nrow=ceil(sqrt(nbr_par+1));
ncol=nrow;
-if nrow*(nrow-1)>nbr_par,
+if nrow*(nrow-1)>nbr_par
ncol=nrow-1;
end
cmap = colormap(jet(10));
-for jx=1:nbr_par,
+for jx=1:nbr_par
subplot(nrow,ncol,jx)
hold off
- for jt=1:10,
+ for jt=1:10
h=cumplot(x0(indy{jt},indmcf(jx)));
set(h,'color', cmap(jt,:), 'linewidth', 2)
- hold all,
+ hold all
end
title(options_mcf.param_names(indmcf(jx),:),'interpreter','none')
end
diff --git a/matlab/gsa/redform_screen.m b/matlab/gsa/redform_screen.m
index 311c6b520..1a53b7e53 100644
--- a/matlab/gsa/redform_screen.m
+++ b/matlab/gsa/redform_screen.m
@@ -39,7 +39,7 @@ iload = options_gsa_.load_redform;
nliv = options_gsa_.morris_nliv;
pnames = M_.param_names(estim_params_.param_vals(:,1),:);
-if nargin==0,
+if nargin==0
dirname='';
end
@@ -53,7 +53,7 @@ nshock = length(bayestopt_.pshape)-np;
nsok = length(find(M_.lead_lag_incidence(M_.maximum_lag,:)));
js=0;
-for j=1:size(anamendo,1),
+for j=1:size(anamendo,1)
namendo=deblank(anamendo(j,:));
iendo=strmatch(namendo,M_.endo_names(oo_.dr.order_var,:),'exact');
@@ -63,10 +63,10 @@ for j=1:size(anamendo,1),
namexo=deblank(anamexo(jx,:));
iexo=strmatch(namexo,M_.exo_names,'exact');
- if ~isempty(iexo),
+ if ~isempty(iexo)
y0=teff(T(iendo,iexo+nspred,:),kn,istable);
- if ~isempty(y0),
- if mod(iplo,9)==0,
+ if ~isempty(y0)
+ if mod(iplo,9)==0
ifig=ifig+1;
hh=dyn_figure(options_.nodisplay,'name',[namendo,' vs. shocks ',int2str(ifig)]);
iplo=0;
@@ -82,11 +82,11 @@ for j=1:size(anamendo,1),
%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),
+ 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,
+ if iplo==9
dyn_saveas(hh,[dirname,'/',M_.fname,'_', namendo,'_vs_shock_',num2str(ifig)],options_.nodisplay,options_.graph_format);
create_TeX_loader(options_,[dirname,'/',M_.fname,'_', namendo,'_vs_shock_',num2str(ifig)],ifig,[namendo,' vs. shocks ',int2str(ifig)],[namendo,'_vs_shock'],1)
end
@@ -94,7 +94,7 @@ for j=1:size(anamendo,1),
end
end
end
- if iplo<9 && iplo>0 && ifig,
+ if iplo<9 && iplo>0 && ifig
dyn_saveas(hh,[dirname,'/',M_.fname,'_', namendo,'_vs_shocks_',num2str(ifig)],options_.nodisplay,options_.graph_format);
create_TeX_loader(options_,[dirname,'/',M_.fname,'_', namendo,'_vs_shock_',num2str(ifig)],ifig,[namendo,' vs. shocks ',int2str(ifig)],[namendo,'_vs_shock'],options_.figures.textwidth*min(iplo/3))
end
@@ -105,10 +105,10 @@ for j=1:size(anamendo,1),
namlagendo=deblank(anamlagendo(je,:));
ilagendo=strmatch(namlagendo,M_.endo_names(oo_.dr.order_var(M_.nstatic+1:M_.nstatic+nsok),:),'exact');
- if ~isempty(ilagendo),
+ if ~isempty(ilagendo)
y0=teff(T(iendo,ilagendo,:),kn,istable);
- if ~isempty(y0),
- if mod(iplo,9)==0,
+ if ~isempty(y0)
+ if mod(iplo,9)==0
ifig=ifig+1;
hh=dyn_figure(options_.nodisplay,'name',[namendo,' vs. lagged endogenous ',int2str(ifig)]);
iplo=0;
@@ -124,19 +124,19 @@ for j=1:size(anamendo,1),
%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),
+ 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,
+ if iplo==9
dyn_saveas(hh,[dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)],options_.nodisplay,options_.graph_format);
create_TeX_loader(options_,[dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)],ifig,[namendo,' vs. lagged endogenous ',int2str(ifig)],[namendo,'_vs_lags'],1)
end
end
end
end
- if iplo<9 && iplo>0 && ifig,
+ if iplo<9 && iplo>0 && ifig
dyn_saveas(hh,[dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)],options_.nodisplay,options_.graph_format);
create_TeX_loader(options_,[dirname,'/',M_.fname,'_', namendo,'_vs_lags_',num2str(ifig)],ifig,[namendo,' vs. lagged endogenous ',int2str(ifig)],[namendo,'_vs_lags'],options_.figures.textwidth*min(iplo/3))
end
@@ -150,7 +150,7 @@ 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,
+for ip=1:np
text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
end
xlabel(' ')
diff --git a/matlab/gsa/scatter_analysis.m b/matlab/gsa/scatter_analysis.m
index ddd4fec3a..4550e5878 100644
--- a/matlab/gsa/scatter_analysis.m
+++ b/matlab/gsa/scatter_analysis.m
@@ -37,12 +37,12 @@ amcf_title = options_scatter.amcf_title;
title = options_scatter.title;
fname_ = options_scatter.fname_;
xparam1=[];
-if isfield(options_scatter,'xparam1'),
+if isfield(options_scatter,'xparam1')
xparam1=options_scatter.xparam1;
end
OutputDirectoryName = options_scatter.OutputDirectoryName;
-if ~DynareOptions.nograph,
+if ~DynareOptions.nograph
skipline()
xx=[];
if ~isempty(xparam1)
diff --git a/matlab/gsa/scatter_mcf.m b/matlab/gsa/scatter_mcf.m
index fa4229375..0f48f636b 100644
--- a/matlab/gsa/scatter_mcf.m
+++ b/matlab/gsa/scatter_mcf.m
@@ -49,7 +49,7 @@ clear Z;
nflag = 0;
if nargin >=3
nflag = 1;
-end;
+end
if nargin<4 || isempty(plotsymbol)
if n*p<100, plotsymbol = 'o';
@@ -60,37 +60,37 @@ end
if nargin<5
fnam='';
end
-if nargin<6,
+if nargin<6
dirname='';
nograph=1;
else
nograph=0;
end
-if nargin<7,
+if nargin<7
figtitle=fnam;
end
-if nargin<8,
+if nargin<8
xparam1=[];
end
-if nargin<10,
+if nargin<10
beha_name = 'BEHAVIOUR';
non_beha_name = 'NON-BEHAVIOUR';
end
-if nargin==10,
+if nargin==10
non_beha_name = ['NON-' beha_name];
end
figtitle_tex=strrep(figtitle,'_','\_');
fig_nam_=[fnam];
-if ~nograph,
+if ~nograph
hh=dyn_figure(DynareOptions.nodisplay,'name',figtitle);
end
bf = 0.1;
ffs = 0.05/(p-1);
ffl = (1-2*bf-0.05)/p;
-if p>1,
+if p>1
fL = linspace(bf,1-bf+ffs,p+1);
else
fL = bf;
@@ -129,7 +129,7 @@ for i = 1:p
end
hold off;
% axis([-0.1 1.1 -0.1 1.1])
- if i<p,
+ if i<p
set(gca,'YTickLabel',[],'YTick',[]);
else
set(gca,'yaxislocation','right');
@@ -140,14 +140,14 @@ for i = 1:p
end
if nflag == 1
set(gca,'fontsize',9);
- end;
+ end
if i==1
if nflag == 1
ylabel(vnames(j,:),'Rotation',45,'interpreter','none', ...
'HorizontalAlignment','right','VerticalAlignment','middle');
else
ylabel([num2str(j),' '],'Rotation',90)
- end;
+ end
end
if j==1
if nflag == 1
@@ -155,7 +155,7 @@ for i = 1:p
'HorizontalAlignment','left','VerticalAlignment','bottom')
else
title(num2str(i))
- end;
+ end
end
drawnow
end
@@ -165,7 +165,7 @@ if ~isoctave
annotation('textbox', [0.55,0,0.35,0.05],'String', non_beha_name,'Color','Red','horizontalalignment','center','interpreter','none');
end
-if ~nograph,
+if ~nograph
dyn_saveas(hh,[dirname,filesep,fig_nam_],DynareOptions.nodisplay,DynareOptions.graph_format);
if DynareOptions.TeX && any(strcmp('eps',cellstr(DynareOptions.graph_format)))
fidTeX = fopen([dirname,'/',fig_nam_ '.tex'],'w');
diff --git a/matlab/gsa/scatter_plots.m b/matlab/gsa/scatter_plots.m
index e64195464..852ae5b40 100644
--- a/matlab/gsa/scatter_plots.m
+++ b/matlab/gsa/scatter_plots.m
@@ -44,7 +44,7 @@ function scatter_plots(X,xp,vnames,plotsymbol, fnam, dirname, figtitle, xparam1,
nflag = 0;
if nargin >=3
nflag = 1;
-end;
+end
if nargin<4 || isempty(plotsymbol)
if n*p<100, plotsymbol = 'o';
@@ -55,17 +55,17 @@ end
if nargin<5 || isempty(fnam)
fnam='scatter_plot';
end
-if nargin<6 || isempty(dirname),
+if nargin<6 || isempty(dirname)
dirname='';
nograph=1;
DynareOptions.nodisplay=0;
else
nograph=0;
end
-if nargin<7 || isempty(figtitle),
+if nargin<7 || isempty(figtitle)
figtitle=fnam;
end
-if nargin<8,
+if nargin<8
xparam1=[];
end
@@ -79,7 +79,7 @@ fig_nam_=[fnam];
bf = 0.1;
ffs = 0.05/(p-1);
ffl = (1-2*bf-0.05)/p;
-if p>1,
+if p>1
fL = linspace(bf,1-bf+ffs,p+1);
else
fL = bf;
@@ -135,7 +135,7 @@ for i = 1:p
end
hold off;
% axis([-0.1 1.1 -0.1 1.1])
- if i<p,
+ if i<p
set(gca,'YTickLabel',[],'YTick',[]);
else
set(gca,'yaxislocation','right');
@@ -146,14 +146,14 @@ for i = 1:p
end
if nflag == 1
set(gca,'fontsize',9);
- end;
+ end
if i==1
if nflag == 1
ylabel(vnames(j,:),'Rotation',45,'interpreter','none', ...
'HorizontalAlignment','right','VerticalAlignment','middle');
else
ylabel([num2str(j),' '],'Rotation',90)
- end;
+ end
end
if j==1
if nflag == 1
@@ -161,7 +161,7 @@ for i = 1:p
'HorizontalAlignment','left','VerticalAlignment','bottom')
else
title(num2str(i))
- end;
+ end
end
drawnow
end
@@ -171,7 +171,7 @@ end
% annotation('textbox', [0.55,0,0.35,0.05],'String', non_beha_name,'Color','Red','horizontalalignment','center','interpreter','none');
% end
-if ~nograph,
+if ~nograph
dyn_saveas(hh,[dirname,filesep,fig_nam_],DynareOptions.nodisplay,DynareOptions.graph_format);
if DynareOptions.TeX && any(strcmp('eps',cellstr(DynareOptions.graph_format)))
fidTeX = fopen([dirname,'/',fig_nam_ '.tex'],'w');
diff --git a/matlab/gsa/smirnov.m b/matlab/gsa/smirnov.m
index ed3b17397..2a96a2a7d 100644
--- a/matlab/gsa/smirnov.m
+++ b/matlab/gsa/smirnov.m
@@ -27,7 +27,7 @@ function [H,prob,d] = smirnov(x1 , x2 , alpha, iflag )
if nargin<3
alpha = 0.05;
end
-if nargin<4,
+if nargin<4
iflag=0;
end
@@ -52,7 +52,7 @@ n = n1*n2 /(n1+n2);
% Compute the d(n1,n2) statistics.
-if iflag==0,
+if iflag==0
d = max(abs(cum1 - cum2));
elseif iflag==-1
d = max(cum2 - cum1);
diff --git a/matlab/gsa/stab_map_.m b/matlab/gsa/stab_map_.m
index 78ab1a368..20a61b844 100644
--- a/matlab/gsa/stab_map_.m
+++ b/matlab/gsa/stab_map_.m
@@ -109,7 +109,7 @@ else % estimated parameters but no declared priors
end
end
-if nargin==0,
+if nargin==0
OutputDirectoryName='';
end
@@ -143,12 +143,12 @@ options_.periods=0;
options_.nomoments=1;
options_.irf=0;
options_.noprint=1;
-if fload==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'),
+ if isfield(dr_,'ghx')
egg=zeros(length(dr_.eigval),Nsam);
end
yys=zeros(length(dr_.ys),Nsam);
@@ -163,16 +163,16 @@ if fload==0,
% lpmat = prep_ide(Nsam,np,5);
% Nsam=size(lpmat,1);
else
- if np<52 && ilptau>0,
+ if np<52 && ilptau>0
[lpmat] = qmc_sequence(np, int64(1), 0, Nsam)';
- if np>30 || ilptau==2, % scrambled lptau
- for j=1:np,
+ if np>30 || ilptau==2 % scrambled lptau
+ for j=1:np
lpmat(:,j)=lpmat(randperm(Nsam),j);
end
end
else %ilptau==0
[lpmat] = NaN(Nsam,np);
- for j=1:np,
+ for j=1:np
lpmat(:,j) = randperm(Nsam)'./(Nsam+1); %latin hypercube
end
@@ -188,9 +188,9 @@ if fload==0,
% end
%
% end
- if pprior,
- for j=1:nshock,
- if opt_gsa.morris~=1,
+ 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
@@ -204,7 +204,7 @@ if fload==0,
% xdelt(:,:,j)=prior_draw_gsa(0,[lpmat0 lpmat]+deltx);
% end
% end
- for j=1:np,
+ for j=1:np
lpmat(:,j)=lpmat(:,j).*(bounds.ub(j+nshock)-bounds.lb(j+nshock))+bounds.lb(j+nshock);
end
else
@@ -254,13 +254,13 @@ if fload==0,
% end
% end
%load([fname_,'_mode'])
- if neighborhood_width>0 && isempty(options_.mode_file),
+ if neighborhood_width>0 && isempty(options_.mode_file)
xparam1 = get_all_parameters(estim_params_,M_);
else
eval(['load ' options_.mode_file '.mat;']);
end
- if neighborhood_width>0,
- for j=1:nshock,
+ if neighborhood_width>0
+ for j=1:nshock
if opt_gsa.morris ~= 1
lpmat0(:,j) = randperm(Nsam)'./(Nsam+1); %latin hypercube
end
@@ -268,10 +268,10 @@ if fload==0,
lb=max([bounds.lb(j) xparam1(j)*(1-neighborhood_width)]);
lpmat0(:,j)=lpmat0(:,j).*(ub-lb)+lb;
end
- for j=1:np,
+ for j=1:np
ub=xparam1(j+nshock)*(1+sign(xparam1(j+nshock))*neighborhood_width);
lb=xparam1(j+nshock)*(1-sign(xparam1(j+nshock))*neighborhood_width);
- if bounds.ub(j+nshock)>=xparam1(j) && bounds.lb(j)<=xparam1(j+nshock),
+ if bounds.ub(j+nshock)>=xparam1(j) && bounds.lb(j)<=xparam1(j+nshock)
ub=min([bounds.ub(j+nshock) ub]);
lb=max([bounds.lb(j+nshock) lb]);
else
@@ -283,7 +283,7 @@ if fload==0,
d = chol(inv(hh));
lp=randn(Nsam*2,nshock+np)*d+kron(ones(Nsam*2,1),xparam1');
lnprior=zeros(1,Nsam*2);
- for j=1:Nsam*2,
+ for j=1:Nsam*2
lnprior(j) = any(lp(j,:)'<=bounds.lb | lp(j,:)'>=bounds.ub);
end
ireal=[1:2*Nsam];
@@ -305,7 +305,7 @@ if fload==0,
inorestriction=zeros(1,Nsam);
irestriction=zeros(1,Nsam);
infox=zeros(Nsam,1);
- for j=1:Nsam,
+ for j=1:Nsam
M_ = set_all_parameters([lpmat0(j,:) lpmat(j,:)]',estim_params_,M_);
%try stoch_simul([]);
try
@@ -315,14 +315,14 @@ if fload==0,
[Tt,Rr,SteadyState,info,M_,options_,oo_] = dynare_resolve(M_,options_,oo_,'restrict');
end
infox(j,1)=info(1);
- if infox(j,1)==0 && ~exist('T','var'),
+ if infox(j,1)==0 && ~exist('T','var')
dr_=oo_.dr;
- if prepSA,
+ if prepSA
try
T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),Nsam);
catch
ME = lasterror();
- if strcmp('MATLAB:nomem',ME.identifier),
+ if strcmp('MATLAB:nomem',ME.identifier)
prepSA=0;
disp('The model is too large for storing state space matrices ...')
disp('for mapping reduced form or for identification')
@@ -334,26 +334,26 @@ if fload==0,
end
egg=zeros(length(dr_.eigval),Nsam);
end
- if infox(j,1),
+ if infox(j,1)
% disp('no solution'),
- if isfield(oo_.dr,'ghx'),
+ if isfield(oo_.dr,'ghx')
oo_.dr=rmfield(oo_.dr,'ghx');
end
- if (infox(j,1)<3 || infox(j,1)>5) && isfield(oo_.dr,'eigval'),
+ if (infox(j,1)<3 || infox(j,1)>5) && isfield(oo_.dr,'eigval')
oo_.dr=rmfield(oo_.dr,'eigval');
end
end
catch ME
- if isfield(oo_.dr,'eigval'),
+ if isfield(oo_.dr,'eigval')
oo_.dr=rmfield(oo_.dr,'eigval');
end
- if isfield(oo_.dr,'ghx'),
+ if isfield(oo_.dr,'ghx')
oo_.dr=rmfield(oo_.dr,'ghx');
end
- disp('No solution could be found'),
+ disp('No solution could be found')
end
dr_ = oo_.dr;
- if isfield(dr_,'ghx'),
+ if isfield(dr_,'ghx')
egg(:,j) = sort(dr_.eigval);
if prepSA
jstab=jstab+1;
@@ -363,14 +363,14 @@ if fload==0,
% bayestopt_.restrict_columns, ...
% bayestopt_.restrict_aux);
end
- if ~exist('nspred','var'),
+ if ~exist('nspred','var')
nspred = dr_.nspred; %size(dr_.ghx,2);
nboth = dr_.nboth;
nfwrd = dr_.nfwrd;
end
info=endogenous_prior_restrictions(Tt,Rr,M_,options_,oo_);
infox(j,1)=info(1);
- if info(1),
+ if info(1)
inorestriction(j)=j;
else
iunstable(j)=0;
@@ -384,13 +384,13 @@ if fload==0,
if any(isnan(egg(1:nspred,j)))
iwrong(j)=j;
else
- if (nboth || nfwrd) && abs(egg(nspred+1,j))<=options_.qz_criterium,
+ if (nboth || nfwrd) && abs(egg(nspred+1,j))<=options_.qz_criterium
iindeterm(j)=j;
end
end
end
else
- if exist('egg','var'),
+ if exist('egg','var')
egg(:,j)=ones(size(egg,1),1).*NaN;
end
iwrong(j)=j;
@@ -402,7 +402,7 @@ if fload==0,
dyn_waitbar(j/Nsam,h,['MC iteration ',int2str(j),'/',int2str(Nsam)])
end
dyn_waitbar_close(h);
- if prepSA && jstab,
+ if prepSA && jstab
T=T(:,:,1:jstab);
else
T=[];
@@ -454,7 +454,7 @@ if fload==0,
bkpprior.p2=bayestopt_.p2;
bkpprior.p3=bayestopt_.p3;
bkpprior.p4=bayestopt_.p4;
- if pprior,
+ if pprior
if ~prepSA
save([OutputDirectoryName filesep fname_ '_prior.mat'], ...
'bkpprior','lpmat','lpmat0','irestriction','iunstable','istable','iindeterm','iwrong','ixun', ...
@@ -477,19 +477,19 @@ if fload==0,
end
end
else
- if pprior,
+ if pprior
filetoload=[OutputDirectoryName filesep fname_ '_prior.mat'];
else
filetoload=[OutputDirectoryName filesep fname_ '_mc.mat'];
end
load(filetoload,'lpmat','lpmat0','irestriction','iunstable','istable','iindeterm','iwrong','ixun','egg','yys','nspred','nboth','nfwrd','infox')
Nsam = size(lpmat,1);
- if pprior==0 && ~isempty(options_.mode_file),
+ if pprior==0 && ~isempty(options_.mode_file)
eval(['load ' options_.mode_file '.mat;']);
end
- if prepSA && isempty(strmatch('T',who('-file', filetoload),'exact')),
+ if prepSA && isempty(strmatch('T',who('-file', filetoload),'exact'))
h = dyn_waitbar(0,'Please wait...');
options_.periods=0;
options_.nomoments=1;
@@ -499,7 +499,7 @@ else
%T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),length(istable));
ntrans=length(istable);
yys=NaN(length(ys_),ntrans);
- for j=1:ntrans,
+ for j=1:ntrans
M_.params(estim_params_.param_vals(:,1)) = lpmat(istable(j),:)';
%stoch_simul([]);
[Tt,Rr,SteadyState,info,M_,options_,oo_] = dynare_resolve(M_,options_,oo_,'restrict');
@@ -548,51 +548,51 @@ delete([OutputDirectoryName,filesep,fname_,'_',aindname,'.*']);
delete([OutputDirectoryName,filesep,fname_,'_',aunstname,'.*']);
delete([OutputDirectoryName,filesep,fname_,'_',awrongname,'.*']);
-if length(iunstable)>0 || length(iwrong)>0,
+if length(iunstable)>0 || length(iwrong)>0
fprintf(['%4.1f%% of the prior support gives unique saddle-path solution.\n'],length(istable)/Nsam*100)
fprintf(['%4.1f%% of the prior support gives explosive dynamics.\n'],(length(ixun) )/Nsam*100)
- if ~isempty(iindeterm),
+ if ~isempty(iindeterm)
fprintf(['%4.1f%% of the prior support gives indeterminacy.\n'],length(iindeterm)/Nsam*100)
end
inorestriction = istable(find(~ismember(istable,irestriction))); % violation of prior restrictions
- if ~isempty(iwrong) || ~isempty(inorestriction),
+ if ~isempty(iwrong) || ~isempty(inorestriction)
skipline()
- if any(infox==49),
+ if any(infox==49)
fprintf(['%4.1f%% of the prior support violates prior restrictions.\n'],(length(inorestriction) )/Nsam*100)
end
- if ~isempty(iwrong),
+ if ~isempty(iwrong)
skipline()
disp(['For ',num2str(length(iwrong)/Nsam*100,'%4.1f'),'% of the prior support dynare could not find a solution.'])
skipline()
end
- if any(infox==1),
+ if any(infox==1)
disp([' For ',num2str(length(find(infox==1))/Nsam*100,'%4.1f'),'% The model doesn''t determine the current variables uniquely.'])
end
- if any(infox==2),
+ if any(infox==2)
disp([' For ',num2str(length(find(infox==2))/Nsam*100,'%4.1f'),'% MJDGGES returned an error code.'])
end
- if any(infox==6),
+ if any(infox==6)
disp([' For ',num2str(length(find(infox==6))/Nsam*100,'%4.1f'),'% The jacobian evaluated at the deterministic steady state is complex.'])
end
- if any(infox==19),
+ if any(infox==19)
disp([' For ',num2str(length(find(infox==19))/Nsam*100,'%4.1f'),'% The steadystate routine thrown an exception (inconsistent deep parameters).'])
end
- if any(infox==20),
+ if any(infox==20)
disp([' For ',num2str(length(find(infox==20))/Nsam*100,'%4.1f'),'% Cannot find the steady state.'])
end
- if any(infox==21),
+ if any(infox==21)
disp([' For ',num2str(length(find(infox==21))/Nsam*100,'%4.1f'),'% The steady state is complex.'])
end
- if any(infox==22),
+ if any(infox==22)
disp([' For ',num2str(length(find(infox==22))/Nsam*100,'%4.1f'),'% The steady has NaNs.'])
end
- if any(infox==23),
+ if any(infox==23)
disp([' For ',num2str(length(find(infox==23))/Nsam*100,'%4.1f'),'% M_.params has been updated in the steadystate routine and has complex valued scalars.'])
end
- if any(infox==24),
+ if any(infox==24)
disp([' For ',num2str(length(find(infox==24))/Nsam*100,'%4.1f'),'% M_.params has been updated in the steadystate routine and has some NaNs.'])
end
- if any(infox==30),
+ if any(infox==30)
disp([' For ',num2str(length(find(infox==30))/Nsam*100,'%4.1f'),'% Ergodic variance can''t be computed.'])
end
@@ -602,7 +602,7 @@ if length(iunstable)>0 || length(iwrong)>0,
itot = [1:Nsam];
isolve = itot(find(~ismember(itot,iwrong))); % dynare could find a solution
% Blanchard Kahn
- if neighborhood_width,
+ if neighborhood_width
options_mcf.xparam1 = xparam1(nshock+1:end);
end
itmp = itot(find(~ismember(itot,istable)));
@@ -613,7 +613,7 @@ if length(iunstable)>0 || length(iwrong)>0,
options_mcf.title = 'unique solution';
mcf_analysis(lpmat, istable, itmp, options_mcf, options_);
- if ~isempty(iindeterm),
+ if ~isempty(iindeterm)
itmp = isolve(find(~ismember(isolve,iindeterm)));
options_mcf.amcf_name = aindname;
options_mcf.amcf_title = aindtitle;
@@ -623,7 +623,7 @@ if length(iunstable)>0 || length(iwrong)>0,
mcf_analysis(lpmat, itmp, iindeterm, options_mcf, options_);
end
- if ~isempty(ixun),
+ if ~isempty(ixun)
itmp = isolve(find(~ismember(isolve,ixun)));
options_mcf.amcf_name = aunstname;
options_mcf.amcf_title = aunsttitle;
@@ -635,7 +635,7 @@ if length(iunstable)>0 || length(iwrong)>0,
inorestriction = istable(find(~ismember(istable,irestriction))); % violation of prior restrictions
iwrong = iwrong(find(~ismember(iwrong,inorestriction))); % what went wrong beyond prior restrictions
- if ~isempty(iwrong),
+ if ~isempty(iwrong)
itmp = itot(find(~ismember(itot,iwrong)));
options_mcf.amcf_name = awrongname;
options_mcf.amcf_title = awrongtitle;
@@ -645,8 +645,8 @@ if length(iunstable)>0 || length(iwrong)>0,
mcf_analysis(lpmat, itmp, iwrong, options_mcf, options_);
end
- if ~isempty(irestriction),
- if neighborhood_width,
+ if ~isempty(irestriction)
+ if neighborhood_width
options_mcf.xparam1 = xparam1;
end
np=size(bayestopt_.name,1);
@@ -699,7 +699,7 @@ xparam1=x0;
save prior_ok.mat xparam1;
options_.periods=opt.periods;
-if isfield(opt,'nomoments'),
+if isfield(opt,'nomoments')
options_.nomoments=opt.nomoments;
end
options_.irf=opt.irf;
diff --git a/matlab/gsa/stab_map_1.m b/matlab/gsa/stab_map_1.m
index 8535a78ec..0bd9888e7 100644
--- a/matlab/gsa/stab_map_1.m
+++ b/matlab/gsa/stab_map_1.m
@@ -40,11 +40,11 @@ function [proba, dproba] = stab_map_1(lpmat, ibehaviour, inonbehaviour, aname, i
global estim_params_ bayestopt_ M_ options_
-if nargin<5,
+if nargin<5
iplot=1;
end
fname_ = M_.fname;
-if nargin<7,
+if nargin<7
dirname='';
end
if nargin<9,
@@ -59,20 +59,20 @@ nshock = nshock + estim_params_.ncn;
npar=size(lpmat,2);
ishock= npar>estim_params_.np;
-if nargin<6,
+if nargin<6
ipar=[];
end
-if nargin<8 || isempty(pcrit),
+if nargin<8 || isempty(pcrit)
pcrit=1;
end
% Smirnov test for Blanchard;
-for j=1:npar,
+for j=1:npar
[H,P,KSSTAT] = smirnov(lpmat(ibehaviour,j),lpmat(inonbehaviour,j));
proba(j)=P;
dproba(j)=KSSTAT;
end
-if isempty(ipar),
+if isempty(ipar)
% ipar=find(dproba>dcrit);
ipar=find(proba<pcrit);
end
@@ -81,23 +81,23 @@ if iplot && ~options_.nograph
lpmat=lpmat(:,ipar);
ftit=bayestopt_.name(ipar+nshock*(1-ishock));
- for i=1:ceil(nparplot/12),
+ for i=1:ceil(nparplot/12)
hh=dyn_figure(options_.nodisplay,'name',atitle);
- for j=1+12*(i-1):min(nparplot,12*i),
+ for j=1+12*(i-1):min(nparplot,12*i)
subplot(3,4,j-12*(i-1))
- if ~isempty(ibehaviour),
+ if ~isempty(ibehaviour)
h=cumplot(lpmat(ibehaviour,j));
set(h,'color',[0 0 1], 'linestyle',':','LineWidth',1.5)
end
- hold on,
- if ~isempty(inonbehaviour),
+ hold on
+ if ~isempty(inonbehaviour)
h=cumplot(lpmat(inonbehaviour,j));
set(h,'color',[0 0 0],'LineWidth',1.5)
end
% title([ftit{j},'. D-stat ', num2str(dproba(ipar(j)),2)],'interpreter','none')
title([ftit{j},'. p-value ', num2str(proba(ipar(j)),2)],'interpreter','none')
end
- if nparplot>12,
+ if nparplot>12
dyn_saveas(hh,[dirname,filesep,fname_,'_',aname,'_SA_',int2str(i)],options_.nodisplay,options_.graph_format);
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fidTeX = fopen([dirname,filesep,fname_,'_',aname,'_SA_',int2str(i) '.tex'],'w');
diff --git a/matlab/gsa/stab_map_2.m b/matlab/gsa/stab_map_2.m
index beed786dc..d13435d11 100644
--- a/matlab/gsa/stab_map_2.m
+++ b/matlab/gsa/stab_map_2.m
@@ -29,17 +29,17 @@ npar=size(x,2);
nsam=size(x,1);
ishock= npar>estim_params_.np;
nograph = options_.nograph;
-if nargin<4,
+if nargin<4
fnam='';
end
-if nargin<5,
+if nargin<5
dirname='';
nograph=1;
end
-if nargin<6,
+if nargin<6
xparam1=[];
end
-if nargin<7,
+if nargin<7
figtitle=fnam;
end
@@ -61,7 +61,7 @@ ifig=0;
j2=0;
if ishock==0
npar=estim_params_.np;
- if ~isempty(xparam1),
+ if ~isempty(xparam1)
xparam1=xparam1(nshock+1:end);
end
else
@@ -73,14 +73,14 @@ title_string_tex=['Correlation analysis for ',strrep(fnam,'_','\\_')];
indcorr = [];
entry_iter=1;
-for j=1:npar,
+for j=1:npar
i2=find(abs(c00(:,j))>alpha2);
- if length(i2)>0,
- for jx=1:length(i2),
- if pvalue(j,i2(jx))<pvalue_crit,
+ if length(i2)>0
+ for jx=1:length(i2)
+ if pvalue(j,i2(jx))<pvalue_crit
indcorr = [indcorr; [j i2(jx)]];
j2=j2+1;
- if ishock,
+ if ishock
if options_.TeX
[param_name_temp1, param_name_tex_temp1]= get_the_name(j,options_.TeX,M_,estim_params_,options_);
param_name_tex_temp1 = strrep(param_name_tex_temp1,'$','');
@@ -116,8 +116,8 @@ for j=1:npar,
data_mat(entry_iter,1)=c0(i2(jx),j);
entry_iter=entry_iter+1;
- if ~nograph,
- if mod(j2,12)==1,
+ if ~nograph
+ if mod(j2,12)==1
ifig=ifig+1;
hh=dyn_figure(options_.nodisplay,'name',[figtitle,' sample bivariate projection ', num2str(ifig)]);
end
@@ -133,7 +133,7 @@ for j=1:npar,
end
% xlabel(deblank(estim_params_.param_names(j,:)),'interpreter','none'),
% ylabel(deblank(estim_params_.param_names(i2(jx),:)),'interpreter','none'),
- if ishock,
+ if ishock
xlabel(bayestopt_.name{j},'interpreter','none'),
ylabel(bayestopt_.name{i2(jx)},'interpreter','none'),
else
@@ -141,7 +141,7 @@ for j=1:npar,
ylabel(bayestopt_.name{i2(jx)+nshock},'interpreter','none'),
end
title(['cc = ',num2str(c0(i2(jx),j))])
- if (mod(j2,12)==0) && j2>0,
+ if (mod(j2,12)==0) && j2>0
dyn_saveas(hh,[dirname,filesep,fig_nam_,int2str(ifig)],options_.nodisplay,options_.graph_format);
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fidTeX = fopen([dirname,filesep,fig_nam_,int2str(ifig),'.tex'],'w');
@@ -162,7 +162,7 @@ for j=1:npar,
end
end
- if ~nograph && (j==(npar)) && j2>0 && (mod(j2,12)~=0),
+ if ~nograph && (j==(npar)) && j2>0 && (mod(j2,12)~=0)
dyn_saveas(hh,[dirname,filesep,fig_nam_,int2str(ifig)],options_.nodisplay,options_.graph_format);
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fidTeX = fopen([dirname,filesep,fig_nam_,int2str(ifig),'.tex'],'w');
@@ -180,7 +180,7 @@ for j=1:npar,
end
end
-if j2==0,
+if j2==0
disp(['No correlation term with pvalue <', num2str(pvalue_crit),' and |corr. coef.| >',num2str(alpha2),' found for ',fnam])
else
headers=strvcat('Parameters','corrcoef');
diff --git a/matlab/gsa/stand_.m b/matlab/gsa/stand_.m
index c69ec4bf3..b6a087a53 100644
--- a/matlab/gsa/stand_.m
+++ b/matlab/gsa/stand_.m
@@ -30,11 +30,11 @@ function [y, meany, stdy] = stand_(x)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-if nargin==0,
- return;
+if nargin==0
+ return
end
-for j=1:size(x,2);
+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);
diff --git a/matlab/gsa/tcrit.m b/matlab/gsa/tcrit.m
index 291725aad..ba5f85a9e 100644
--- a/matlab/gsa/tcrit.m
+++ b/matlab/gsa/tcrit.m
@@ -27,16 +27,16 @@ function t_crit = tcrit(n,pval0)
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-if nargin==1 || isempty(pval0),
+if nargin==1 || isempty(pval0)
pval0=0.05;
end
-if pval0==1,
+if pval0==1
t_crit=0;
- return,
+ return
end
-if pval0==0,
+if pval0==0
t_crit=inf;
- return,
+ return
end
pval = [ 0.10 0.05 0.025 0.01 0.005 0.001];
pval0=max(pval0,min(pval));
@@ -146,7 +146,7 @@ t_crit=[
inf 1.282 1.645 1.960 2.326 2.576 3.090
];
-if n<=100,
+if n<=100
t_crit=t_crit(n,ncol);
else
t_crit=t_crit(end,ncol);
diff --git a/matlab/gsa/teff.m b/matlab/gsa/teff.m
index 0956669a3..da2d04741 100644
--- a/matlab/gsa/teff.m
+++ b/matlab/gsa/teff.m
@@ -27,8 +27,8 @@ function [yt, j0, ir, ic]=teff(T,Nsam,istable)
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
ndim = (length(size(T)));
-if ndim==3,
-if nargin==1,
+if ndim==3
+if nargin==1
Nsam=size(T,3);
istable = [1:Nsam]';
end
@@ -38,7 +38,7 @@ tmin=min(T,[],3);
j0 = length(ir);
yt=zeros(Nsam, j0);
-for j=1:j0,
+for j=1:j0
y0=squeeze(T(ir(j),ic(j),:));
%y1=ones(size(lpmat,1),1)*NaN;
y1=ones(Nsam,1)*NaN;
diff --git a/matlab/gsa/th_moments.m b/matlab/gsa/th_moments.m
index 5616b4045..3f7708761 100644
--- a/matlab/gsa/th_moments.m
+++ b/matlab/gsa/th_moments.m
@@ -56,13 +56,13 @@ var = gamma_y{1};
z;
%'VARIANCE DECOMPOSITION (in percent)';
-if M_.exo_nbr>1,
+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,
+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
@@ -71,7 +71,7 @@ end
if options_.ar > 0
%'COEFFICIENTS OF AUTOCORRELATION';
for i=1:options_.ar
- if options_.opt_gsa.useautocorr,
+ 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)');
diff --git a/matlab/gsa/trank.m b/matlab/gsa/trank.m
index d6ac2d2db..42eff73ce 100644
--- a/matlab/gsa/trank.m
+++ b/matlab/gsa/trank.m
@@ -1,4 +1,4 @@
-function yr = trank(y);
+function yr = trank(y)
% yr = trank(y);
% yr is the rank transformation of y
%
@@ -28,7 +28,7 @@ function yr = trank(y);
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
[nr, nc] = size(y);
-for j=1:nc,
+for j=1:nc
[dum, is]=sort(y(:,j));
yr(is,j)=[1:nr]'./nr;
end
diff --git a/matlab/ident_bruteforce.m b/matlab/ident_bruteforce.m
index 41ed952d7..c42d2a7db 100644
--- a/matlab/ident_bruteforce.m
+++ b/matlab/ident_bruteforce.m
@@ -52,7 +52,7 @@ tittxt1=strrep(tittxt1, '.', '');
cosnJ=zeros(k,n);
pars{k,n}=[];
-for ll = 1:n,
+for ll = 1:n
h = dyn_waitbar(0,['Brute force collinearity for ' int2str(ll) ' parameters.']);
for ii = 1:k
tmp = find([1:k]~=ii);
@@ -63,8 +63,8 @@ for ll = 1:n,
[cosnJ2(jj,1), b(:,jj)] = cosn([J(:,ii),J(:,tmp2(jj,:))]);
end
cosnJ(ii,ll) = max(cosnJ2(:,1));
- if cosnJ(ii,ll)>1.e-8,
- if ll>1 && ((cosnJ(ii,ll)-cosnJ(ii,ll-1))<1.e-8),
+ if cosnJ(ii,ll)>1.e-8
+ if ll>1 && ((cosnJ(ii,ll)-cosnJ(ii,ll-1))<1.e-8)
pars{ii,ll} = [pars{ii,ll-1} NaN];
cosnJ(ii,ll) = cosnJ(ii,ll-1);
else
@@ -101,10 +101,10 @@ for ll = 1:n,
fprintf(fidTeX,'\\midrule \\endhead \n');
fprintf(fidTeX,'\\bottomrule \\multicolumn{3}{r}{(Continued on next page)}\\endfoot \n');
fprintf(fidTeX,'\\bottomrule\\endlastfoot \n');
- for i=1:k,
+ for i=1:k
plist='';
- for ii=1:ll,
- if ~isnan(pars{i,ll}(ii)),
+ for ii=1:ll
+ if ~isnan(pars{i,ll}(ii))
plist = [plist ' $' pnames_TeX(pars{i,ll}(ii),:) '\;\; $ '];
else
plist = [plist ' ---- '];
diff --git a/matlab/identification_analysis.m b/matlab/identification_analysis.m
index 88b60ca4d..e1a6e380e 100644
--- a/matlab/identification_analysis.m
+++ b/matlab/identification_analysis.m
@@ -51,7 +51,7 @@ persistent indH indJJ indLRE
nparam=length(params);
np=length(indx);
offset=nparam-np;
-if ~isempty(estim_params_),
+if ~isempty(estim_params_)
M_ = set_all_parameters(params,estim_params_,M_);
end
@@ -73,7 +73,7 @@ ide_lre = struct();
derivatives_info = struct();
[A,B,ys,info,M_,options_,oo_] = dynare_resolve(M_,options_,oo_);
-if info(1)==0,
+if info(1)==0
oo0=oo_;
tau=[oo_.dr.ys(oo_.dr.order_var); vec(A); dyn_vech(B*M_.Sigma_e*B')];
yy0=oo_.dr.ys(I);
@@ -86,14 +86,14 @@ if info(1)==0,
derivatives_info.DT=dA;
derivatives_info.DOm=dOm;
derivatives_info.DYss=dYss;
- if init,
+ if init
indJJ = (find(max(abs(JJ'),[],1)>1.e-8));
if isempty(indJJ) && any(any(isnan(JJ)))
error('There are NaN in the JJ matrix. Please check whether your model has units roots and you forgot to set diffuse_filter=1.' )
elseif any(any(isnan(gam)))
error('There are NaN''s in the theoretical moments: make sure that for non-stationary models stationary transformations of non-stationary observables are used for checking identification. [TIP: use first differences].')
end
- while length(indJJ)<nparam && nlags<10,
+ while length(indJJ)<nparam && nlags<10
disp('The number of moments with non-zero derivative is smaller than the number of parameters')
disp(['Try increasing ar = ', int2str(nlags+1)])
nlags=nlags+1;
@@ -104,7 +104,7 @@ if info(1)==0,
options_.ar=nlags;
indJJ = (find(max(abs(JJ'),[],1)>1.e-8));
end
- if length(indJJ)<nparam,
+ if length(indJJ)<nparam
disp('The number of moments with non-zero derivative is smaller than the number of parameters')
disp('up to 10 lags: check your model')
disp('Either further increase ar or reduce the list of estimated parameters')
@@ -121,18 +121,18 @@ if info(1)==0,
siLRE = (gp(indLRE,:));
ide_strength_J=NaN(1,nparam);
ide_strength_J_prior=NaN(1,nparam);
- if init, %~isempty(indok),
+ if init
normaliz = NaN(1,nparam);
- if prior_exist,
- if ~isempty(estim_params_.var_exo),
+ if prior_exist
+ if ~isempty(estim_params_.var_exo)
normaliz1 = estim_params_.var_exo(:,7)'; % normalize with prior standard deviation
else
normaliz1=[];
end
- if ~isempty(estim_params_.corrx),
+ if ~isempty(estim_params_.corrx)
normaliz1 = [normaliz1 estim_params_.corrx(:,8)']; % normalize with prior standard deviation
end
- if ~isempty(estim_params_.param_vals),
+ if ~isempty(estim_params_.param_vals)
normaliz1 = [normaliz1 estim_params_.param_vals(:,7)']; % normalize with prior standard deviation
end
% normaliz = max([normaliz; normaliz1]);
@@ -141,13 +141,13 @@ if info(1)==0,
else
normaliz1 = NaN(1,nparam);
end
- try,
+ try
options_.irf = 0;
options_.noprint = 1;
options_.order = 1;
options_.SpectralDensity.trigger = 0;
options_.periods = periods+100;
- if options_.kalman_algo > 2,
+ if options_.kalman_algo > 2
options_.kalman_algo = 1;
end
analytic_derivation = options_.analytic_derivation;
@@ -160,7 +160,7 @@ if info(1)==0,
% fval = DsgeLikelihood(xparam1,data_info,options_,M_,estim_params_,bayestopt_,oo_);
options_.analytic_derivation = analytic_derivation;
AHess=-AHess;
- if min(eig(AHess))<-1.e-10,
+ if min(eig(AHess))<-1.e-10
error('identification_analysis: Analytic Hessian is not positive semi-definite!')
end
% chol(AHess);
@@ -168,7 +168,7 @@ if info(1)==0,
deltaM = sqrt(diag(AHess));
iflag=any((deltaM.*deltaM)==0);
tildaM = AHess./((deltaM)*(deltaM'));
- if iflag || rank(AHess)>rank(tildaM),
+ if iflag || rank(AHess)>rank(tildaM)
[ide_hess.cond, ide_hess.ind0, ide_hess.indno, ide_hess.ino, ide_hess.Mco, ide_hess.Pco] = identification_checks(AHess, 1);
else
[ide_hess.cond, ide_hess.ind0, ide_hess.indno, ide_hess.ino, ide_hess.Mco, ide_hess.Pco] = identification_checks(tildaM, 1);
@@ -187,7 +187,7 @@ if info(1)==0,
rhoM=sqrt(1./diag(inv(tildaM(indok,indok))));
% deltaM = deltaM.*abs(params');
flag_score=1;
- catch,
+ catch
% replic = max([replic, nparam*(nparam+1)/2*10]);
replic = max([replic, length(indJJ)*3]);
cmm = simulated_moment_uncertainty(indJJ, periods, replic,options_,M_,oo_);
@@ -225,7 +225,7 @@ if info(1)==0,
deltaM = sqrt(diag(MIM));
iflag=any((deltaM.*deltaM)==0);
tildaM = MIM./((deltaM)*(deltaM'));
- if iflag || rank(MIM)>rank(tildaM),
+ if iflag || rank(MIM)>rank(tildaM)
[ide_hess.cond, ide_hess.ind0, ide_hess.indno, ide_hess.ino, ide_hess.Mco, ide_hess.Pco] = identification_checks(MIM, 1);
else
[ide_hess.cond, ide_hess.ind0, ide_hess.indno, ide_hess.ino, ide_hess.Mco, ide_hess.Pco] = identification_checks(tildaM, 1);
@@ -239,7 +239,7 @@ if info(1)==0,
% chh = siH(:,ind1)*((MIM(ind1,ind1))\siH(:,ind1)');
ind1=ind1(ind1>offset);
clre = siLRE(:,ind1-offset)*((MIM(ind1,ind1))\siLRE(:,ind1-offset)');
- if ~isempty(indok),
+ if ~isempty(indok)
rhoM(indok)=sqrt(1./diag(inv(tildaM(indok,indok))));
normaliz(indok) = (sqrt(diag(inv(tildaM(indok,indok))))./deltaM(indok))'; %sqrt(diag(inv(MIM(indok,indok))))';
end
@@ -253,7 +253,7 @@ if info(1)==0,
deltaM = deltaM.*abs(params');
deltaM(params==0)=deltaM_prior(params==0);
quant = siJ./repmat(sqrt(diag(cmm)),1,nparam);
- if size(quant,1)==1,
+ if size(quant,1)==1
siJnorm = abs(quant).*normaliz1;
else
siJnorm = vnorm(quant).*normaliz1;
@@ -268,9 +268,9 @@ if info(1)==0,
iy = find(diag_chh);
indH=indH(iy);
siH=siH(iy,:);
- if ~isempty(iy),
+ if ~isempty(iy)
quant = siH./repmat(sqrt(diag_chh(iy)),1,nparam);
- if size(quant,1)==1,
+ if size(quant,1)==1
siHnorm = abs(quant).*normaliz1;
else
siHnorm = vnorm(quant).*normaliz1;
@@ -288,9 +288,9 @@ if info(1)==0,
iy = find(diag_clre);
indLRE=indLRE(iy);
siLRE=siLRE(iy,:);
- if ~isempty(iy),
+ if ~isempty(iy)
quant = siLRE./repmat(sqrt(diag_clre(iy)),1,np);
- if size(quant,1)==1,
+ if size(quant,1)==1
siLREnorm = abs(quant).*normaliz1(offset+1:end);
else
siLREnorm = vnorm(quant).*normaliz1(offset+1:end);
@@ -307,8 +307,8 @@ if info(1)==0,
ide_model.siHnorm=siHnorm;
ide_lre.siLREnorm=siLREnorm;
ide_hess.flag_score=flag_score;
- end,
- if normalize_jacobians,
+ end
+ if normalize_jacobians
normH = max(abs(siH)')';
normH = normH(:,ones(nparam,1));
normJ = max(abs(siJ)')';
@@ -354,9 +354,8 @@ if info(1)==0,
ide_moments.S = S;
ide_moments.V = V;
end
-
indok = find(max(ide_moments.indno,[],1)==0);
- if advanced,
+ if advanced
[ide_moments.pars, ide_moments.cosnJ] = ident_bruteforce(JJ(indJJ,:)./normJ,max_dim_cova_group,options_.TeX,name_tex,tittxt);
end
-end
+end
diff --git a/matlab/identification_checks.m b/matlab/identification_checks.m
index 208d7ecd4..58a2a3ea2 100644
--- a/matlab/identification_checks.m
+++ b/matlab/identification_checks.m
@@ -45,7 +45,7 @@ function [condJ, ind0, indnoJ, ixnoJ, McoJ, PcoJ, jweak, jweak_pair] = identific
npar = size(JJ,2);
indnoJ = zeros(1,npar);
-if size(JJ,1)>1,
+if size(JJ,1)>1
ind1 = find(vnorm(JJ)>=eps); % take non-zero columns
else
ind1 = find(abs(JJ)>=eps); % take non-zero columns
@@ -56,12 +56,12 @@ condJ= cond(JJ1);
rankJ = rank(JJ);
rankJJ = rankJ;
icheck=0;
-if npar>0 && (rankJ<npar),
+if npar>0 && (rankJ<npar)
% search for singular values associated to ONE individual parameter
ee0 = [rankJJ+1:length(ind1)];
ind11=ones(length(ind1),1);
- for j=1:length(ee0),
- if length(find(abs(ee1(:,ee0(j))) > 1.e-3))==1,
+ for j=1:length(ee0)
+ if length(find(abs(ee1(:,ee0(j))) > 1.e-3))==1
icheck=1;
ind11 = ind11.*(abs(ee1(:,ee0(j))) <= 1.e-3); % take non-zero columns
end
@@ -69,13 +69,13 @@ if npar>0 && (rankJ<npar),
ind1 = ind1(find(ind11)); % take non-zero columns
end
-if icheck,
+if icheck
JJ1 = JJ(:,ind1);
[eu,ee2,ee1] = svd( JJ1, 0 );
condJ= cond(JJ1);
rankJ = rank(JJ);
rankJJ = rankJ;
-end
+end
% if hess_flag==0,
@@ -85,10 +85,10 @@ end
ind0 = zeros(1,npar);
ind0(ind1) = 1;
-if hess_flag==0,
+if hess_flag==0
% find near linear dependence problems:
McoJ = NaN(npar,1);
- for ii = 1:size(JJ1,2);
+ for ii = 1:size(JJ1,2)
McoJ(ind1(ii),:) = cosn([JJ1(:,ii),JJ1(:,find([1:1:size(JJ1,2)]~=ii))]);
end
else
@@ -109,19 +109,17 @@ if npar>0 && (rankJ<npar || rankJJ<npar || min(1-McoJ)<1.e-10)
% - find out which parameters are involved
% disp('Some parameters are NOT identified by the moments included in J')
% disp(' ')
- if length(ind1)<npar,
+ if length(ind1)<npar
% parameters with zero column in JJ
ixnoJ = ixnoJ + 1;
indnoJ(ixnoJ,:) = (~ismember([1:npar],ind1));
end
ee0 = [rankJJ+1:length(ind1)];
- for j=1:length(ee0),
+ for j=1:length(ee0)
% linearely dependent parameters in JJ
ixnoJ = ixnoJ + 1;
indnoJ(ixnoJ,ind1) = (abs(ee1(:,ee0(j))) > 1.e-3)';
end
-else %rank(J)==length(theta) =>
- % disp('All parameters are identified at theta by the moments included in J')
end
% here there is no exact linear dependence, but there are several
@@ -134,19 +132,19 @@ jweak_pair=zeros(npar,npar);
if hess_flag==0,
PcoJ = NaN(npar,npar);
-for ii = 1:size(JJ1,2);
+for ii = 1:size(JJ1,2)
PcoJ(ind1(ii),ind1(ii)) = 1;
- for jj = ii+1:size(JJ1,2);
+ for jj = ii+1:size(JJ1,2)
PcoJ(ind1(ii),ind1(jj)) = cosn([JJ1(:,ii),JJ1(:,jj)]);
PcoJ(ind1(jj),ind1(ii)) = PcoJ(ind1(ii),ind1(jj));
end
end
-for j=1:npar,
- if McoJ(j)>(1-1.e-10),
+for j=1:npar
+ if McoJ(j)>(1-1.e-10)
jweak(j)=1;
[ipair, jpair] = find(PcoJ(j,j+1:end)>(1-1.e-10));
- for jx=1:length(jpair),
+ for jx=1:length(jpair)
jweak_pair(j, jpair(jx)+j)=1;
jweak_pair(jpair(jx)+j, j)=1;
end
diff --git a/matlab/initial_condition_decomposition.m b/matlab/initial_condition_decomposition.m
index 7e2f0ae2c..af92d65ac 100644
--- a/matlab/initial_condition_decomposition.m
+++ b/matlab/initial_condition_decomposition.m
@@ -93,7 +93,7 @@ gend = size(oo.SmoothedShocks.(deblank(M_.exo_names(1,:))),1); %+options_.foreca
z = zeros(endo_nbr,endo_nbr+2,gend);
z(:,end,:) = Smoothed_Variables_deviation_from_mean;
-for i=1:endo_nbr,
+for i=1:endo_nbr
z(i,i,1) = Smoothed_Variables_deviation_from_mean(i,1);
end
diff --git a/matlab/k_order_pert.m b/matlab/k_order_pert.m
index db1ef91f4..f775cb363 100644
--- a/matlab/k_order_pert.m
+++ b/matlab/k_order_pert.m
@@ -40,14 +40,14 @@ switch(order)
[err, g_1] = k_order_perturbation(dr,M,options);
if err
info(1)=9;
- return;
+ return
end
dr.g_1 = g_1;
case 2
[err, g_0, g_1, g_2] = k_order_perturbation(dr,M,options);
if err
info(1)=9;
- return;
+ return
end
dr.g_0 = g_0;
dr.g_1 = g_1;
@@ -58,14 +58,14 @@ switch(order)
M,options);
if err
info(1)=9;
- return;
+ return
end
else
[err, g_0, g_1, g_2, g_3] = k_order_perturbation(dr, ...
M,options);
if err
info(1)=9;
- return;
+ return
end
end
dr.g_0 = g_0;
diff --git a/matlab/kalman/likelihood/computeDLIK.m b/matlab/kalman/likelihood/computeDLIK.m
index 1acb0796f..632506ef7 100644
--- a/matlab/kalman/likelihood/computeDLIK.m
+++ b/matlab/kalman/likelihood/computeDLIK.m
@@ -24,20 +24,20 @@ persistent DK DF D2K D2F
if notsteady
if Zflag
[DK,DF,DP1] = computeDKalmanZ(T,DT,DOm,P,DP,DH,Z,iF,K);
- if nargout>4,
+ if nargout>4
[D2K,D2F,D2P] = computeD2KalmanZ(T,DT,D2T,D2Om,P,DP,D2P,DH,Z,iF,K,DK);
end
else
[DK,DF,DP1] = computeDKalman(T,DT,DOm,P,DP,DH,Z,iF,K);
- if nargout>4,
+ if nargout>4
[D2K,D2F,D2P] = computeD2Kalman(T,DT,D2T,D2Om,P,DP,D2P,DH,Z,iF,K,DK);
end
end
DP=DP1;
-clear DP1,
+clear DP1
else
DP=DP;
- if nargout>4,
+ if nargout>4
D2P=D2P;
end
end
@@ -72,7 +72,7 @@ for ii = 1:k
dKi = DK(:,:,ii);
dtmp(:,ii) = Da(:,ii)+dKi*v+K*Dv(:,ii);
- if nargout>4,
+ if nargout>4
diFi = -iF*DF(:,:,ii)*iF;
for jj = 1:ii
jcount=jcount+1;
@@ -94,7 +94,7 @@ for ii = 1:k
D2a(:,jj,ii) = reshape(D2T(:,jcount),size(T))*tmp + DT(:,:,jj)*dtmp(:,ii) + DT(:,:,ii)*dtmp(:,jj) + T*d2tmpij;
D2a(:,ii,jj) = D2a(:,jj,ii);
- if nargout==6,
+ if nargout==6
Hesst(ii,jj) = getHesst_ij(v,Dv(:,ii),Dv(:,jj),d2vij,iF,diFi,diFj,d2iFij,dFj,d2Fij);
end
end
@@ -104,7 +104,7 @@ for ii = 1:k
DLIK(ii,1) = trace( iF*DF(:,:,ii) ) + 2*Dv(:,ii)'*iF*v - v'*(iF*DF(:,:,ii)*iF)*v;
end
-if nargout==4,
+if nargout==4
% Hesst(ii,jj) = getHesst_ij(v,Dv(:,ii),Dv(:,jj),0,iF,diFi,diFj,0,dFj,0);
vecDPmf = reshape(DF,[],k);
D2a = 2*Dv'*iF*Dv + (vecDPmf' * kron(iF,iF) * vecDPmf);
@@ -122,7 +122,7 @@ end
% end of computeDLIK
-function Hesst_ij = getHesst_ij(e,dei,dej,d2eij,iS,diSi,diSj,d2iSij,dSj,d2Sij);
+function Hesst_ij = getHesst_ij(e,dei,dej,d2eij,iS,diSi,diSj,d2iSij,dSj,d2Sij)
% computes (i,j) term in the Hessian
Hesst_ij = trace(diSi*dSj + iS*d2Sij) + e'*d2iSij*e + 2*(dei'*diSj*e + dei'*iS*dej + e'*diSi*dej + e'*iS*d2eij);
@@ -165,7 +165,7 @@ end
% end of computeDKalmanZ
-function [d2K,d2S,d2P1] = computeD2Kalman(A,dA,d2A,d2Om,P0,dP0,d2P1,DH,Z,iF,K0,dK0);
+function [d2K,d2S,d2P1] = computeD2Kalman(A,dA,d2A,d2Om,P0,dP0,d2P1,DH,Z,iF,K0,dK0)
% computes the second derivatives of the Kalman matrices
% note: A=T in main func.
@@ -189,7 +189,7 @@ for ii = 1:k
% d2Omi = d2Om(:,:,ii);
diFi = -iF*dFi*iF;
dKi = dK0(:,:,ii);
- for jj = 1:ii,
+ for jj = 1:ii
jcount=jcount+1;
dAj = dA(:,:,jj);
dFj = dP0(Z,Z,jj);
@@ -233,7 +233,7 @@ end
% end of computeD2Kalman
-function [d2K,d2S,d2P1] = computeD2KalmanZ(A,dA,d2A,d2Om,P0,dP0,d2P1,DH,Z,iF,K0,dK0);
+function [d2K,d2S,d2P1] = computeD2KalmanZ(A,dA,d2A,d2Om,P0,dP0,d2P1,DH,Z,iF,K0,dK0)
% computes the second derivatives of the Kalman matrices
% note: A=T in main func.
@@ -251,13 +251,13 @@ d2S = zeros(no,no,k,k);
% d2P1 = zeros(ns,ns,k,k);
jcount=0;
-for ii = 1:k,
+for ii = 1:k
dAi = dA(:,:,ii);
dFi = Z*dP0(:,:,ii)*Z;
% d2Omi = d2Om(:,:,ii);
diFi = -iF*dFi*iF;
dKi = dK0(:,:,ii);
- for jj = 1:ii,
+ for jj = 1:ii
jcount=jcount+1;
dAj = dA(:,:,jj);
dFj = Z*dP0(:,:,jj)*Z;
diff --git a/matlab/kalman/likelihood/kalman_filter.m b/matlab/kalman/likelihood/kalman_filter.m
index 398ab1f4b..18f8307a7 100644
--- a/matlab/kalman/likelihood/kalman_filter.m
+++ b/matlab/kalman/likelihood/kalman_filter.m
@@ -123,7 +123,7 @@ notsteady = 1;
F_singular = true;
asy_hess=0;
-if analytic_derivation == 0,
+if analytic_derivation == 0
DLIK=[];
Hess=[];
LIKK=[];
@@ -133,14 +133,14 @@ else
Da = zeros(mm,k); % Derivative State vector.
dlikk = zeros(smpl,k);
- if Zflag==0,
+ if Zflag==0
C = zeros(pp,mm);
- for ii=1:pp; C(ii,Z(ii))=1;end % SELECTION MATRIX IN MEASUREMENT EQ. (FOR WHEN IT IS NOT CONSTANT)
+ for ii=1:pp, C(ii,Z(ii))=1; end % SELECTION MATRIX IN MEASUREMENT EQ. (FOR WHEN IT IS NOT CONSTANT)
else
C=Z;
end
dC = zeros(pp,mm,k); % either selection matrix or schur have zero derivatives
- if analytic_derivation==2,
+ if analytic_derivation==2
Hess = zeros(k,k); % Initialization of the Hessian
D2a = zeros(mm,k,k); % State vector.
d2C = zeros(pp,mm,k,k);
@@ -151,7 +151,7 @@ else
D2T=[];
D2Yss=[];
end
- if asy_hess,
+ if asy_hess
Hess = zeros(k,k); % Initialization of the Hessian
end
LIK={inf,DLIK,Hess};
@@ -188,7 +188,7 @@ while notsteady && t<=last
end
else
F_singular = false;
- if rescale_prediction_error_covariance,
+ if rescale_prediction_error_covariance
log_dF = log(det(F./(sig*sig')))+2*sum(log(sig));
iF = inv(F./(sig*sig'))./(sig*sig');
else
@@ -204,15 +204,15 @@ while notsteady && t<=last
Ptmp = T*(P-K*P(Z,:))*transpose(T)+QQ;
end
tmp = (a+K*v);
- if analytic_derivation,
- if analytic_derivation==2,
+ if analytic_derivation
+ if analytic_derivation==2
[Da,DP,DLIKt,D2a,D2P, Hesst] = computeDLIK(k,tmp,Z,Zflag,v,T,K,P,iF,Da,DYss,DT,DOm,DP,DH,notsteady,D2a,D2Yss,D2T,D2Om,D2P);
else
[Da,DP,DLIKt,Hesst] = computeDLIK(k,tmp,Z,Zflag,v,T,K,P,iF,Da,DYss,DT,DOm,DP,DH,notsteady);
end
if t>presample
DLIK = DLIK + DLIKt;
- if analytic_derivation==2 || asy_hess,
+ if analytic_derivation==2 || asy_hess
Hess = Hess + Hesst;
end
end
@@ -232,11 +232,11 @@ end
% Add observation's densities constants and divide by two.
likk(1:s) = .5*(likk(1:s) + pp*log(2*pi));
-if analytic_derivation,
+if analytic_derivation
DLIK = DLIK/2;
dlikk = dlikk/2;
- if analytic_derivation==2 || asy_hess,
- if asy_hess==0,
+ if analytic_derivation==2 || asy_hess
+ if asy_hess==0
Hess = Hess + tril(Hess,-1)';
end
Hess = -Hess/2;
@@ -245,8 +245,8 @@ end
% Call steady state Kalman filter if needed.
if t <= last
- if analytic_derivation,
- if analytic_derivation==2,
+ if analytic_derivation
+ if analytic_derivation==2
[tmp, tmp2] = kalman_filter_ss(Y, t, last, a, T, K, iF, dF, Z, pp, Zflag, analytic_derivation, Da, DT, DYss, D2a, D2T, D2Yss);
else
[tmp, tmp2] = kalman_filter_ss(Y, t, last, a, T, K, iF, dF, Z, pp, Zflag, analytic_derivation, Da, DT, DYss, asy_hess);
@@ -263,14 +263,14 @@ if t <= last
end
% Compute minus the log-likelihood.
-if presample>diffuse_periods,
+if presample>diffuse_periods
LIK = sum(likk(1+(presample-diffuse_periods):end));
else
LIK = sum(likk);
end
-if analytic_derivation,
- if analytic_derivation==2 || asy_hess,
+if analytic_derivation
+ if analytic_derivation==2 || asy_hess
LIK={LIK, DLIK, Hess};
else
LIK={LIK, DLIK};
diff --git a/matlab/kalman/likelihood/kalman_filter_fast.m b/matlab/kalman/likelihood/kalman_filter_fast.m
index 4319b5502..1f6d070ae 100644
--- a/matlab/kalman/likelihood/kalman_filter_fast.m
+++ b/matlab/kalman/likelihood/kalman_filter_fast.m
@@ -194,11 +194,11 @@ end
% Add observation's densities constants and divide by two.
likk(1:s) = .5*(likk(1:s) + pp*log(2*pi));
-if analytic_derivation,
+if analytic_derivation
DLIK = DLIK/2;
dlikk = dlikk/2;
- if analytic_derivation==2 || asy_hess,
- if asy_hess==0,
+ if analytic_derivation==2 || asy_hess
+ if asy_hess==0
Hess = Hess + tril(Hess,-1)';
end
Hess = -Hess/2;
@@ -207,8 +207,8 @@ end
% Call steady state Kalman filter if needed.
if t <= last
- if analytic_derivation,
- if analytic_derivation==2,
+ if analytic_derivation
+ if analytic_derivation==2
[tmp, tmp2] = kalman_filter_ss(Y,t,last,a,T,K,iF,dF,Z,pp,Zflag, ...
analytic_derivation,Da,DT,DYss,D2a,D2T,D2Yss);
else
@@ -218,7 +218,7 @@ if t <= last
likk(s+1:end)=tmp2{1};
dlikk(s+1:end,:)=tmp2{2};
DLIK = DLIK + tmp{2};
- if analytic_derivation==2 || asy_hess,
+ if analytic_derivation==2 || asy_hess
Hess = Hess + tmp{3};
end
else
@@ -227,14 +227,14 @@ if t <= last
end
% Compute minus the log-likelihood.
-if presample>diffuse_periods,
+if presample>diffuse_periods
LIK = sum(likk(1+(presample-diffuse_periods):end));
else
LIK = sum(likk);
end
-if analytic_derivation,
- if analytic_derivation==2 || asy_hess,
+if analytic_derivation
+ if analytic_derivation==2 || asy_hess
LIK={LIK, DLIK, Hess};
else
LIK={LIK, DLIK};
diff --git a/matlab/kalman/likelihood/kalman_filter_ss.m b/matlab/kalman/likelihood/kalman_filter_ss.m
index 8e5f92733..b0aed34eb 100644
--- a/matlab/kalman/likelihood/kalman_filter_ss.m
+++ b/matlab/kalman/likelihood/kalman_filter_ss.m
@@ -86,18 +86,18 @@ if nargin<12
analytic_derivation = 0;
end
-if analytic_derivation == 0,
+if analytic_derivation == 0
DLIK=[];
Hess=[];
else
k = size(DT,3); % number of structural parameters
DLIK = zeros(k,1); % Initialization of the score.
dlikk = zeros(smpl,k);
- if analytic_derivation==2,
+ if analytic_derivation==2
Hess = zeros(k,k); % Initialization of the Hessian
else
asy_hess=D2a;
- if asy_hess,
+ if asy_hess
Hess = zeros(k,k); % Initialization of the Hessian
else
Hess=[];
@@ -112,14 +112,14 @@ while t <= last
v = Y(:,t)-a(Z);
end
tmp = (a+K*v);
- if analytic_derivation,
- if analytic_derivation==2,
+ if analytic_derivation
+ if analytic_derivation==2
[Da,junk,DLIKt,D2a,junk2, Hesst] = computeDLIK(k,tmp,Z,Zflag,v,T,K,[],iF,Da,DYss,DT,[],[],[],notsteady,D2a,D2Yss,D2T,[],[]);
else
[Da,junk,DLIKt,Hesst] = computeDLIK(k,tmp,Z,Zflag,v,T,K,[],iF,Da,DYss,DT,[],[],[],notsteady);
end
DLIK = DLIK + DLIKt;
- if analytic_derivation==2 || asy_hess,
+ if analytic_derivation==2 || asy_hess
Hess = Hess + Hesst;
end
dlikk(t-start+1,:)=DLIKt;
@@ -137,17 +137,17 @@ likk = .5*(likk + pp*log(2*pi));
% Sum the observation's densities (minus the likelihood)
LIK = sum(likk);
-if analytic_derivation,
+if analytic_derivation
dlikk = dlikk/2;
DLIK = DLIK/2;
likk = {likk, dlikk};
end
-if analytic_derivation==2 || asy_hess,
- if asy_hess==0,
+if analytic_derivation==2 || asy_hess
+ if asy_hess==0
Hess = Hess + tril(Hess,-1)';
end
Hess = -Hess/2;
LIK={LIK,DLIK,Hess};
-elseif analytic_derivation==1,
+elseif analytic_derivation==1
LIK={LIK,DLIK};
end
diff --git a/matlab/kalman/likelihood/missing_observations_kalman_filter.m b/matlab/kalman/likelihood/missing_observations_kalman_filter.m
index 4d357cd29..6b584f975 100644
--- a/matlab/kalman/likelihood/missing_observations_kalman_filter.m
+++ b/matlab/kalman/likelihood/missing_observations_kalman_filter.m
@@ -123,7 +123,7 @@ while notsteady && t<=last
end
else
F_singular = false;
- if rescale_prediction_error_covariance,
+ if rescale_prediction_error_covariance
log_dF = log(det(F./(sig*sig')))+2*sum(log(sig));
iF = inv(F./(sig*sig'))./(sig*sig');
else
diff --git a/matlab/kalman/likelihood/univariate_computeDLIK.m b/matlab/kalman/likelihood/univariate_computeDLIK.m
index 1338a84a6..defc0e290 100644
--- a/matlab/kalman/likelihood/univariate_computeDLIK.m
+++ b/matlab/kalman/likelihood/univariate_computeDLIK.m
@@ -21,12 +21,12 @@ function [Da,DP1,DLIK,D2a,D2P,Hesst] = univariate_computeDLIK(k,indx,Z,Zflag,v,K
persistent DDK DDF DD2K DD2F
-if notsteady,
+if notsteady
if Zflag
Dv = -Z*Da(:,:) - Z*DYss(:,:);
DF = zeros(k,1);
DK = zeros([rows(K),k]);
- for j=1:k,
+ for j=1:k
DF(j)=Z*DP(:,:,j)*Z'+DH;
DK(:,j) = (DP(:,:,j)*Z')/F-PZ*DF(j)/F^2;
end
@@ -35,9 +35,9 @@ if notsteady,
D2v = zeros(k,k);
D2K = zeros(rows(K),k,k);
jcount=0;
- for j=1:k,
+ for j=1:k
D2v(:,j) = -Z*D2a(:,:,j) - Z*D2Yss(:,:,j);
- for i=1:j,
+ for i=1:j
jcount=jcount+1;
D2F(j,i)=Z*dyn_unvech(D2P(:,jcount))*Z';
D2F(i,j)=D2F(j,i);
@@ -57,8 +57,8 @@ if notsteady,
D2K = zeros(rows(K),k,k);
D2v = squeeze(-D2a(Z,:,:) - D2Yss(Z,:,:));
jcount=0;
- for j=1:k,
- for i=1:j,
+ for j=1:k
+ for i=1:j
jcount=jcount+1;
tmp = dyn_unvech(D2P(:,jcount));
D2F(j,i) = tmp(Z,Z);
@@ -89,7 +89,7 @@ else
Dv = -Z*Da(:,:) - Z*DYss(:,:);
if nargout>4
D2v = zeros(k,k);
- for j=1:k,
+ for j=1:k
D2v(:,j) = -Z*D2a(:,:,j) - Z*D2Yss(:,:,j);
end
end
@@ -105,7 +105,7 @@ DLIK = DF/F + 2*Dv'/F*v - v^2/F^2*DF;
if nargout==6
Hesst = D2F/F-1/F^2*(DF*DF') + 2*D2v/F*v + 2*(Dv'*Dv)/F - 2*(DF*Dv)*v/F^2 ...
- v^2/F^2*D2F - 2*v/F^2*(Dv'*DF') + 2*v^2/F^3*(DF*DF');
-elseif nargout==4,
+elseif nargout==4
D2a = 1/F^2*(DF*DF') + 2*(Dv'*Dv)/F ;
% D2a = -1/F^2*(DF*DF') + 2*(Dv'*Dv)/F + 2*v^2/F^3*(DF*DF') ...
% - 2*(DF*Dv)*v/F^2 - 2*v/F^2*(Dv'*DF');
@@ -116,9 +116,9 @@ Da = Da + DK*v+K*Dv;
if nargout>4
D2a = D2a + D2K*v;
- for j=1:k,
+ for j=1:k
% D2a(:,:,j) = D2a(:,:,j) + DK*Dv(j) + DK(:,j)*Dv + K*D2v(j,:);
- for i=1:j,
+ for i=1:j
D2a(:,j,i) = D2a(:,j,i) + DK(:,i)*Dv(j) + DK(:,j)*Dv(i) + K*D2v(j,i);
D2a(:,i,j) = D2a(:,j,i);
end
@@ -127,21 +127,21 @@ if nargout>4
end
-if notsteady,
+if notsteady
DP1 = DP*0;
- if Zflag,
- for j=1:k,
+ if Zflag
+ for j=1:k
DP1(:,:,j)=DP(:,:,j) - (DP(:,:,j)*Z')*K'-PZ*DK(:,j)';
end
else
- for j=1:k,
+ for j=1:k
DP1(:,:,j)=DP(:,:,j) - (DP(:,Z,j))*K'-PZ*DK(:,j)';
end
end
- if nargout>4,
- if Zflag,
- for j=1:k,
- for i=1:j,
+ if nargout>4
+ if Zflag
+ for j=1:k
+ for i=1:j
jcount = jcount+1;
tmp = dyn_unvech(D2P(:,jcount));
tmp = tmp - (tmp*Z')*K' - (DP(:,:,j)*Z')*DK(:,i)' ...
@@ -153,8 +153,8 @@ if notsteady,
else
DPZ = squeeze(DP(:,Z,:));
jcount = 0;
- for j=1:k,
- for i=1:j,
+ for j=1:k
+ for i=1:j
jcount = jcount+1;
tmp = dyn_unvech(D2P(:,jcount));
D2PZ = tmp(:,Z);
diff --git a/matlab/kalman/likelihood/univariate_computeDstate.m b/matlab/kalman/likelihood/univariate_computeDstate.m
index a535a0a51..d4a3aaa2a 100644
--- a/matlab/kalman/likelihood/univariate_computeDstate.m
+++ b/matlab/kalman/likelihood/univariate_computeDstate.m
@@ -22,25 +22,25 @@ function [Da1,DP1,D2a,D2P] = univariate_computeDstate(k,a,P,T,Da,DP,DT,DOm,notst
DP1=DP*0;
Da1=Da*0;
-for j=1:k,
+for j=1:k
Da1(:,j) = T*Da(:,j) + DT(:,:,j)*a;
- if notsteady,
+ if notsteady
DP1(:,:,j) = T*DP(:,:,j)*T'+DT(:,:,j)*P*T'+T*P*DT(:,:,j)';
else
DP1=DP;
end
end
-if notsteady,
+if notsteady
DP1 = DP1 + DOm;
end
-if nargout>2,
+if nargout>2
jcount=0;
- for j=1:k,
- for i=1:j,
+ for j=1:k
+ for i=1:j
jcount=jcount+1;
D2a(:,j,i) = DT(:,:,i)*Da(:,j) + DT(:,:,j)*Da(:,i) + T*D2a(:,j,i)+ reshape(D2T(:,jcount),size(T))*a;
D2a(:,i,j) = D2a(:,j,i);
- if notsteady,
+ if notsteady
tmp = dyn_unvech(D2P(:,jcount));
tmp = T*tmp*T' +DT(:,:,i)*DP(:,:,j)*T'+T*DP(:,:,j)*DT(:,:,i)' + ...
DT(:,:,j)*DP(:,:,i)*T'+T*DP(:,:,i)*DT(:,:,j)' + ...
diff --git a/matlab/kalman/likelihood/univariate_kalman_filter.m b/matlab/kalman/likelihood/univariate_kalman_filter.m
index dd4559cd5..db1f67999 100644
--- a/matlab/kalman/likelihood/univariate_kalman_filter.m
+++ b/matlab/kalman/likelihood/univariate_kalman_filter.m
@@ -128,7 +128,7 @@ oldK = Inf;
K = NaN(mm,pp);
asy_hess=0;
-if analytic_derivation == 0,
+if analytic_derivation == 0
DLIK=[];
Hess=[];
else
@@ -137,14 +137,14 @@ else
Da = zeros(mm,k); % Derivative State vector.
dlik = zeros(smpl,k);
- if Zflag==0,
+ if Zflag==0
C = zeros(pp,mm);
- for ii=1:pp; C(ii,Z(ii))=1;end % SELECTION MATRIX IN MEASUREMENT EQ. (FOR WHEN IT IS NOT CONSTANT)
+ for ii=1:pp, C(ii,Z(ii))=1; end % SELECTION MATRIX IN MEASUREMENT EQ. (FOR WHEN IT IS NOT CONSTANT)
else
C=Z;
end
dC = zeros(pp,mm,k); % either selection matrix or schur have zero derivatives
- if analytic_derivation==2,
+ if analytic_derivation==2
Hess = zeros(k,k); % Initialization of the Hessian
D2a = zeros(mm,k,k); % State vector.
d2C = zeros(pp,mm,k,k);
@@ -155,7 +155,7 @@ else
D2T=[];
D2Yss=[];
end
- if asy_hess,
+ if asy_hess
Hess = zeros(k,k); % Initialization of the Hessian
end
LIK={inf,DLIK,Hess};
@@ -186,15 +186,15 @@ while notsteady && t<=last %loop over t
K(:,i) = Ki;
end
lik(s,i) = log(Fi) + (prediction_error*prediction_error)/Fi + l2pi; %Top equation p. 175 in DK (2012)
- if analytic_derivation,
- if analytic_derivation==2,
+ if analytic_derivation
+ if analytic_derivation==2
[Da,DP,DLIKt,D2a,D2P, Hesst] = univariate_computeDLIK(k,i,z(i,:),Zflag,prediction_error,Ki,PZ,Fi,Da,DYss,DP,DH(d_index(i),:),notsteady,D2a,D2Yss,D2P);
else
[Da,DP,DLIKt,Hesst] = univariate_computeDLIK(k,i,z(i,:),Zflag,prediction_error,Ki,PZ,Fi,Da,DYss,DP,DH(d_index(i),:),notsteady);
end
if t>presample
DLIK = DLIK + DLIKt;
- if analytic_derivation==2 || asy_hess,
+ if analytic_derivation==2 || asy_hess
Hess = Hess + Hesst;
end
end
@@ -207,8 +207,8 @@ while notsteady && t<=last %loop over t
% p. 157, DK (2012)
end
end
- if analytic_derivation,
- if analytic_derivation==2,
+ if analytic_derivation
+ if analytic_derivation==2
[Da,DP,D2a,D2P] = univariate_computeDstate(k,a,P,T,Da,DP,DT,DOm,notsteady,D2a,D2P,D2T,D2Om);
else
[Da,DP] = univariate_computeDstate(k,a,P,T,Da,DP,DT,DOm,notsteady);
@@ -225,10 +225,10 @@ end
% Divide by two.
lik(1:s,:) = .5*lik(1:s,:);
-if analytic_derivation,
+if analytic_derivation
DLIK = DLIK/2;
dlik = dlik/2;
- if analytic_derivation==2 || asy_hess,
+ if analytic_derivation==2 || asy_hess
% Hess = (Hess + Hess')/2;
Hess = -Hess/2;
end
@@ -236,8 +236,8 @@ end
% Call steady state univariate kalman filter if needed.
if t <= last
- if analytic_derivation,
- if analytic_derivation==2,
+ if analytic_derivation
+ if analytic_derivation==2
[tmp, tmp2] = univariate_kalman_filter_ss(Y,t,last,a,P,kalman_tol,T,H,Z,pp,Zflag, ...
analytic_derivation,Da,DT,DYss,DP,DH,D2a,D2T,D2Yss,D2P);
else
@@ -247,7 +247,7 @@ if t <= last
lik(s+1:end,:)=tmp2{1};
dlik(s+1:end,:)=tmp2{2};
DLIK = DLIK + tmp{2};
- if analytic_derivation==2 || asy_hess,
+ if analytic_derivation==2 || asy_hess
Hess = Hess + tmp{3};
end
else
@@ -262,8 +262,8 @@ else
LIK = sum(sum(lik));
end
-if analytic_derivation,
- if analytic_derivation==2 || asy_hess,
+if analytic_derivation
+ if analytic_derivation==2 || asy_hess
LIK={LIK, DLIK, Hess};
else
LIK={LIK, DLIK};
diff --git a/matlab/kalman/likelihood/univariate_kalman_filter_ss.m b/matlab/kalman/likelihood/univariate_kalman_filter_ss.m
index cbc1d5775..fdc08cf1e 100644
--- a/matlab/kalman/likelihood/univariate_kalman_filter_ss.m
+++ b/matlab/kalman/likelihood/univariate_kalman_filter_ss.m
@@ -90,18 +90,18 @@ if nargin<12
analytic_derivation = 0;
end
-if analytic_derivation == 0,
+if analytic_derivation == 0
DLIK=[];
Hess=[];
else
k = size(DT,3); % number of structural parameters
DLIK = zeros(k,1); % Initialization of the score.
dlikk = zeros(smpl,k);
- if analytic_derivation==2,
+ if analytic_derivation==2
Hess = zeros(k,k); % Initialization of the Hessian
else
asy_hess=D2a;
- if asy_hess,
+ if asy_hess
Hess = zeros(k,k); % Initialization of the Hessian
else
Hess=[];
@@ -113,9 +113,9 @@ end
while t<=last
s = t-start+1;
PP = P;
- if analytic_derivation,
+ if analytic_derivation
DPP = DP;
- if analytic_derivation==2,
+ if analytic_derivation==2
D2PP = D2P;
end
end
@@ -134,14 +134,14 @@ while t<=last
a = a + Ki*prediction_error;
PP = PP - PPZ*Ki';
likk(s,i) = log(Fi) + prediction_error*prediction_error/Fi + l2pi;
- if analytic_derivation,
- if analytic_derivation==2,
+ if analytic_derivation
+ if analytic_derivation==2
[Da,DPP,DLIKt,D2a,D2PP, Hesst] = univariate_computeDLIK(k,i,Z(i,:),Zflag,prediction_error,Ki,PPZ,Fi,Da,DYss,DPP,DH(i,:),0,D2a,D2Yss,D2PP);
else
[Da,DPP,DLIKt,Hesst] = univariate_computeDLIK(k,i,Z(i,:),Zflag,prediction_error,Ki,PPZ,Fi,Da,DYss,DPP,DH(i,:),0);
end
DLIK = DLIK + DLIKt;
- if analytic_derivation==2 || asy_hess,
+ if analytic_derivation==2 || asy_hess
Hess = Hess + Hesst;
end
dlikk(s,:)=dlikk(s,:)+DLIKt';
@@ -151,8 +151,8 @@ while t<=last
% p. 157, DK (2012)
end
end
- if analytic_derivation,
- if analytic_derivation==2,
+ if analytic_derivation
+ if analytic_derivation==2
[Da,junk,D2a] = univariate_computeDstate(k,a,P,T,Da,DP,DT,[],0,D2a,D2P,D2T);
else
Da = univariate_computeDstate(k,a,P,T,Da,DP,DT,[],0);
@@ -165,15 +165,15 @@ end
likk = .5*likk;
LIK = sum(sum(likk));
-if analytic_derivation,
+if analytic_derivation
dlikk = dlikk/2;
DLIK = DLIK/2;
likk = {likk, dlikk};
end
-if analytic_derivation==2 || asy_hess,
+if analytic_derivation==2 || asy_hess
% Hess = (Hess + Hess')/2;
Hess = -Hess/2;
LIK={LIK,DLIK,Hess};
-elseif analytic_derivation==1,
+elseif analytic_derivation==1
LIK={LIK,DLIK};
end
\ No newline at end of file
diff --git a/matlab/lmmcp/catstruct.m b/matlab/lmmcp/catstruct.m
index 540bc99d7..014768ad9 100644
--- a/matlab/lmmcp/catstruct.m
+++ b/matlab/lmmcp/catstruct.m
@@ -87,8 +87,8 @@ function A = catstruct(varargin)
narginchk(1, Inf);
N = nargin ;
-if ~isstruct(varargin{end}),
- if isequal(varargin{end},'sorted'),
+if ~isstruct(varargin{end})
+ if isequal(varargin{end},'sorted')
sorted = 1 ;
N = N-1 ;
if N<1
@@ -112,13 +112,13 @@ FN = cell(N,1) ;
VAL = cell(N,1) ;
% parse the inputs
-for ii=1:N,
+for ii=1:N
X = varargin{ii} ;
- if ~isstruct(X),
+ if ~isstruct(X)
error('catstruct:InvalidArgument',['Argument #' num2str(ii) ' is not a structure.']) ;
end
- if ~isempty(X),
+ if ~isempty(X)
% empty structs are ignored
if ii > 1 && ~isempty(sz0)
if ~isequal(size(X), sz0)
@@ -137,10 +137,10 @@ end
if NonEmptyInputsN == 0
% all structures were empty
A = struct([]) ;
-elseif NonEmptyInputsN == 1,
+elseif NonEmptyInputsN == 1
% there was only one non-empty structure
A = varargin{NonEmptyInputs} ;
- if sorted,
+ if sorted
A = orderfields(A) ;
end
else
@@ -156,12 +156,12 @@ else
[UFN,ind] = unique(FN,'legacy') ;
end
- if numel(UFN) ~= numel(FN),
+ if numel(UFN) ~= numel(FN)
warning('catstruct:DuplicatesFound','Fieldnames are not unique between structures.') ;
sorted = 1 ;
end
- if sorted,
+ if sorted
VAL = VAL(ind,:) ;
FN = FN(ind,:) ;
end
diff --git a/matlab/lnsrch1.m b/matlab/lnsrch1.m
index 6457793c7..56d617b35 100644
--- a/matlab/lnsrch1.m
+++ b/matlab/lnsrch1.m
@@ -103,7 +103,7 @@ while 1
else
if f <= fold+alf*alam*slope
check = 0;
- break ;
+ break
else
if alam == 1
tmplam = -slope/(2*(f-fold-slope)) ;
diff --git a/matlab/lpdfgam.m b/matlab/lpdfgam.m
index b82e43234..d54d674b4 100644
--- a/matlab/lpdfgam.m
+++ b/matlab/lpdfgam.m
@@ -1,4 +1,4 @@
-function [ldens,Dldens,D2ldens] = lpdfgam(x,a,b);
+function [ldens,Dldens,D2ldens] = lpdfgam(x,a,b)
% Evaluates the logged GAMMA PDF at x.
%
% INPUTS
diff --git a/matlab/lpdfgbeta.m b/matlab/lpdfgbeta.m
index e8d8af521..193a9201f 100644
--- a/matlab/lpdfgbeta.m
+++ b/matlab/lpdfgbeta.m
@@ -1,4 +1,4 @@
-function [ldens,Dldens,D2ldens] = lpdfgbeta(x,a,b,aa,bb);
+function [ldens,Dldens,D2ldens] = lpdfgbeta(x,a,b,aa,bb)
% Evaluates the logged BETA PDF at x.
%
% INPUTS
diff --git a/matlab/lyapunov_solver.m b/matlab/lyapunov_solver.m
index a7b96c997..18f6302a2 100644
--- a/matlab/lyapunov_solver.m
+++ b/matlab/lyapunov_solver.m
@@ -63,7 +63,7 @@ elseif DynareOptions.lyapunov_srs == 1
P = R_P' * R_P;
else
P = lyapunov_symm(T,R*Q*R',DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold, [], DynareOptions.debug);
-end;
+end
%@test:1
%$ t = NaN(10,1);
diff --git a/matlab/lyapunov_symm.m b/matlab/lyapunov_symm.m
index 694415d71..f9a771825 100644
--- a/matlab/lyapunov_symm.m
+++ b/matlab/lyapunov_symm.m
@@ -54,7 +54,7 @@ if method == 3
persistent X method1;
if ~isempty(method1)
method = method1;
- end;
+ end
if debug
fprintf('lyapunov_symm:: [method=%d] \n',method);
end
@@ -67,16 +67,16 @@ if method == 3
max_it_fp = 2000;
else
max_it_fp = 300;
- end;
+ end
at = a';
%fixed point iterations
- while evol > lyapunov_fixed_point_tol && it_fp < max_it_fp;
+ while evol > lyapunov_fixed_point_tol && it_fp < max_it_fp
X_old = X;
X = a * X * at + b;
evol = max(sum(abs(X - X_old))); %norm_1
%evol = max(sum(abs(X - X_old)')); %norm_inf
it_fp = it_fp + 1;
- end;
+ end
if debug
fprintf('lyapunov_symm:: lyapunov fixed_point iterations=%d norm=%g\n',it_fp,evol);
end
@@ -87,9 +87,9 @@ if method == 3
else
method1 = 3;
x = X;
- return;
- end;
- end;
+ return
+ end
+ end
end
if method
diff --git a/matlab/marginal_density.m b/matlab/marginal_density.m
index 250bb5ddf..628dd97d2 100644
--- a/matlab/marginal_density.m
+++ b/matlab/marginal_density.m
@@ -76,7 +76,7 @@ linee = 0;
check_coverage = 1;
increase = 1;
while check_coverage
- for p = 0.1:0.1:0.9;
+ for p = 0.1:0.1:0.9
critval = chi2inv(p,npar);
ifil = FirstLine;
tmp = 0;
diff --git a/matlab/metropolis_hastings_initialization.m b/matlab/metropolis_hastings_initialization.m
index e18ea098a..8adfdc89e 100644
--- a/matlab/metropolis_hastings_initialization.m
+++ b/matlab/metropolis_hastings_initialization.m
@@ -223,7 +223,7 @@ if ~options_.load_mh_file && ~options_.mh_recover
fprintf(fidlog,[' Expected number of files per block.......: ' int2str(AnticipatedNumberOfFiles) '.\n']);
fprintf(fidlog,[' Expected number of lines in the last file: ' int2str(AnticipatedNumberOfLinesInTheLastFile) '.\n']);
fprintf(fidlog,['\n']);
- for j = 1:NumberOfBlocks,
+ for j = 1:NumberOfBlocks
fprintf(fidlog,[' Initial state of the Gaussian random number generator for chain number ',int2str(j),':\n']);
for i=1:length(record.InitialSeeds(j).Normal)
fprintf(fidlog,[' ' num2str(record.InitialSeeds(j).Normal(i)') '\n']);
@@ -232,7 +232,7 @@ if ~options_.load_mh_file && ~options_.mh_recover
for i=1:length(record.InitialSeeds(j).Unifor)
fprintf(fidlog,[' ' num2str(record.InitialSeeds(j).Unifor(i)') '\n']);
end
- end,
+ end
fprintf(fidlog,' \n');
fclose(fidlog);
elseif options_.load_mh_file && ~options_.mh_recover
diff --git a/matlab/mh_optimal_bandwidth.m b/matlab/mh_optimal_bandwidth.m
index 7355fddbd..8b5e54c7a 100644
--- a/matlab/mh_optimal_bandwidth.m
+++ b/matlab/mh_optimal_bandwidth.m
@@ -98,10 +98,10 @@ end
%% Compute the standard deviation of the draws.
sigma = std(data);
%% Optimal bandwidth parameter.
-if bandwidth == 0; % Rule of thumb bandwidth parameter (Silverman [1986].
+if bandwidth == 0 % Rule of thumb bandwidth parameter (Silverman [1986].
h = 2*sigma*(sqrt(pi)*mu02/(12*(mu21^2)*number_of_draws))^(1/5);
h = h*correction^(1/5);
-elseif bandwidth == -1; % Sheather and Jones [1991] plug-in estimation of the optimal bandwidth parameter.
+elseif bandwidth == -1 % Sheather and Jones [1991] plug-in estimation of the optimal bandwidth parameter.
if strcmp(kernel_function,'uniform') || ...
strcmp(kernel_function,'triangle') || ...
strcmp(kernel_function,'epanechnikov') || ...
@@ -123,7 +123,7 @@ elseif bandwidth == -1; % Sheather and Jones [1991] plug-in estimation of the op
end
Ihat2 = Ihat2/((number_of_draws^2)*g2^5);
h = (correction*mu02/(number_of_draws*Ihat2*mu21^2))^(1/5); % equation (22) in Skold and Roberts [2003].
-elseif bandwidth == -2; % Bump killing... I compute local bandwith parameters in order to remove
+elseif bandwidth == -2 % Bump killing... I compute local bandwith parameters in order to remove
% spurious bumps introduced by long rejecting periods.
if strcmp(kernel_function,'uniform') || ...
strcmp(kernel_function,'triangle') || ...
@@ -135,7 +135,7 @@ elseif bandwidth == -2; % Bump killing... I compute local bandwith parameter
T = zeros(n,1);
for i=1:n
j = i;
- while j<= n && (data(j,1)-data(i,1))<2*eps;
+ while j<= n && (data(j,1)-data(i,1))<2*eps
j = j+1;
end
T(i) = (j-i);
@@ -151,7 +151,7 @@ elseif bandwidth == -2; % Bump killing... I compute local bandwith parameter
Ihat3 = -Ihat3/((n^2)*g3^7);
g2 = abs(2*correction*k4(0)/(mu21*Ihat3*n))^(1/7);
Ihat2 = 0;
- for i=1:number_of_draws;
+ for i=1:number_of_draws
Ihat2 = Ihat2 + sum(k4((data(i)-data)/g2));
end
Ihat2 = Ihat2/((number_of_draws^2)*g2^5);
@@ -169,7 +169,7 @@ function correction = correction_for_repeated_draws(draws,n)
correction = 0;
for i=1:n
j = i;
- while j<=n && ( draws(j,1) - draws(i,1) )<2*eps;
+ while j<=n && ( draws(j,1) - draws(i,1) )<2*eps
j = j+1;
end
correction = correction + 2*(j-i) - 1;
diff --git a/matlab/missing/corrcoef/corrcoef.m b/matlab/missing/corrcoef/corrcoef.m
index c918c6104..e997518ac 100644
--- a/matlab/missing/corrcoef/corrcoef.m
+++ b/matlab/missing/corrcoef/corrcoef.m
@@ -138,22 +138,22 @@ elseif nargin>1
Y=[];
else
varg = varargin;
- end;
+ end
- if length(varg)<1,
+ if length(varg)<1
Mode = 'Pearson';
- elseif length(varg)==1,
+ elseif length(varg)==1
Mode = varg{1};
else
- for k = 2:2:length(varg),
+ for k = 2:2:length(varg)
mode = setfield(mode,lower(varg{k-1}),varg{k});
- end;
+ end
if isfield(mode,'mode')
Mode = mode.mode;
- end;
- end;
-end;
-if isempty(Mode) Mode='pearson'; end;
+ end
+ end
+end
+if isempty(Mode), Mode='pearson'; end
Mode=[Mode,' '];
@@ -164,19 +164,19 @@ warning('off');
[r1,c1]=size(X);
if ~isempty(Y)
[r2,c2]=size(Y);
- if r1~=r2,
+ if r1~=r2
fprintf(2,'Error CORRCOEF: X and Y must have the same number of observations (rows).\n');
- return;
- end;
+ return
+ end
NN = real(~isnan(X)')*real(~isnan(Y));
else
[r2,c2]=size(X);
NN = real(~isnan(X)')*real(~isnan(X));
-end;
+end
%%%%% generate combinations using indices for pairwise calculation of the correlation
YESNAN = any(isnan(X(:))) | any(isnan(Y(:)));
-if YESNAN,
+if YESNAN
FLAG_NANS_OCCURED=(1==1);
if isfield(mode,'rows')
if strcmp(mode.rows,'complete')
@@ -184,7 +184,7 @@ if YESNAN,
X = X(ix,:);
if ~isempty(Y)
Y = Y(ix,:);
- end;
+ end
YESNAN = 0;
NN = size(X,1);
elseif strcmp(mode.rows,'all')
@@ -192,10 +192,10 @@ if YESNAN,
%%NN(NN < size(X,1)) = NaN;
elseif strcmp(mode.rows,'pairwise')
%%% default
- end;
- end;
-end;
-if isempty(Y),
+ end
+ end
+end
+if isempty(Y)
IX = ones(c1)-diag(ones(c1,1));
[jx, jy ] = find(IX);
[jxo,jyo] = find(IX);
@@ -208,13 +208,13 @@ else
IX = ones(c1,c2);
[jxo,jyo] = find(IX);
R = zeros(c1,c2);
-end;
+end
-if strcmp(lower(Mode(1:7)),'pearson');
+if strcmp(lower(Mode(1:7)),'pearson')
% see http://mathworld.wolfram.com/CorrelationCoefficient.html
- if ~YESNAN,
+ if ~YESNAN
[S,N,SSQ] = sumskipnan(X,1);
- if ~isempty(Y),
+ if ~isempty(Y)
[S2,N2,SSQ2] = sumskipnan(Y,1);
CC = X'*Y;
M1 = S./N;
@@ -227,12 +227,12 @@ if strcmp(lower(Mode(1:7)),'pearson');
cc = CC./NN - M'*M;
v = SSQ./N - M.*M; %max(N-1,0);
R = cc./sqrt(v'*v);
- end;
+ end
else
- if ~isempty(Y),
+ if ~isempty(Y)
X = [X,Y];
- end;
- for k = 1:length(jx),
+ end
+ for k = 1:length(jx)
%ik = ~any(isnan(X(:,[jx(k),jy(k)])),2);
ik = ~isnan(X(:,jx(k))) & ~isnan(X(:,jy(k)));
[s,n,s2] = sumskipnan(X(ik,[jx(k),jy(k)]),1);
@@ -241,83 +241,83 @@ if strcmp(lower(Mode(1:7)),'pearson');
cc = cc/n(1) - prod(s./n);
%r(k) = cc./sqrt(prod(v));
R(jxo(k),jyo(k)) = cc./sqrt(prod(v));
- end;
+ end
end
-elseif strcmp(lower(Mode(1:4)),'rank');
+elseif strcmp(lower(Mode(1:4)),'rank')
% see [ 6] http://mathworld.wolfram.com/SpearmanRankCorrelationCoefficient.html
- if ~YESNAN,
+ if ~YESNAN
if isempty(Y)
R = corrcoef(ranks(X));
else
R = corrcoef(ranks(X),ranks(Y));
- end;
+ end
else
- if ~isempty(Y),
+ if ~isempty(Y)
X = [X,Y];
- end;
- for k = 1:length(jx),
+ end
+ for k = 1:length(jx)
%ik = ~any(isnan(X(:,[jx(k),jy(k)])),2);
ik = ~isnan(X(:,jx(k))) & ~isnan(X(:,jy(k)));
il = ranks(X(ik,[jx(k),jy(k)]));
R(jxo(k),jyo(k)) = corrcoef(il(:,1),il(:,2));
- end;
+ end
X = ranks(X);
- end;
+ end
-elseif strcmp(lower(Mode(1:8)),'spearman');
+elseif strcmp(lower(Mode(1:8)),'spearman')
% see [ 6] http://mathworld.wolfram.com/SpearmanRankCorrelationCoefficient.html
- if ~isempty(Y),
+ if ~isempty(Y)
X = [X,Y];
- end;
+ end
n = repmat(nan,c1,c2);
- if ~YESNAN,
+ if ~YESNAN
iy = ranks(X); % calculates ranks;
- for k = 1:length(jx),
+ for k = 1:length(jx)
[R(jxo(k),jyo(k)),n(jxo(k),jyo(k))] = sumskipnan((iy(:,jx(k)) - iy(:,jy(k))).^2); % NN is the number of non-missing values
- end;
+ end
else
- for k = 1:length(jx),
+ for k = 1:length(jx)
%ik = ~any(isnan(X(:,[jx(k),jy(k)])),2);
ik = ~isnan(X(:,jx(k))) & ~isnan(X(:,jy(k)));
il = ranks(X(ik,[jx(k),jy(k)]));
% NN is the number of non-missing values
[R(jxo(k),jyo(k)),n(jxo(k),jyo(k))] = sumskipnan((il(:,1) - il(:,2)).^2);
- end;
+ end
X = ranks(X);
- end;
+ end
R = 1 - 6 * R ./ (n.*(n.*n-1));
-elseif strcmp(lower(Mode(1:7)),'partial');
+elseif strcmp(lower(Mode(1:7)),'partial')
fprintf(2,'Error CORRCOEF: use PARTCORRCOEF \n',Mode);
- return;
+ return
-elseif strcmp(lower(Mode(1:7)),'kendall');
+elseif strcmp(lower(Mode(1:7)),'kendall')
fprintf(2,'Error CORRCOEF: mode ''%s'' not implemented yet.\n',Mode);
- return;
+ return
else
fprintf(2,'Error CORRCOEF: unknown mode ''%s''\n',Mode);
-end;
+end
-if (NARG<2),
+if (NARG<2)
warning(FLAG_WARNING); % restore warning status
- return;
-end;
+ return
+end
% CONFIDENCE INTERVAL
if isfield(mode,'alpha')
alpha = mode.alpha;
-elseif exist('flag_implicit_significance','file'),
+elseif exist('flag_implicit_significance','file')
alpha = flag_implicit_significance;
else
alpha = 0.01;
-end;
+end
% fprintf(1,'CORRCOEF: confidence interval is based on alpha=%f\n',alpha);
@@ -327,21 +327,21 @@ tmp = 1 - R.*R;
tmp(tmp<0) = 0; % prevent tmp<0 i.e. imag(t)~=0
t = R.*sqrt(max(NN-2,0)./tmp);
-if exist('t_cdf','file');
+if exist('t_cdf','file')
sig = t_cdf(t,NN-2);
-elseif exist('tcdf','file')>1;
+elseif exist('tcdf','file')>1
sig = tcdf(t,NN-2);
else
fprintf('CORRCOEF: significance test not completed because of missing TCDF-function\n')
sig = repmat(nan,size(R));
-end;
+end
sig = 2 * min(sig,1 - sig);
-if NARG<3,
+if NARG<3
warning(FLAG_WARNING); % restore warning status
- return;
-end;
+ return
+end
tmp = R;
@@ -356,11 +356,11 @@ ci2 = tanh(z+sz);
%ci1(isnan(ci1))=R(isnan(ci1)); % in case of isnan(ci), the interval limits are exactly the R value
%ci2(isnan(ci2))=R(isnan(ci2));
-if (NARG<5) || ~YESNAN,
+if (NARG<5) || ~YESNAN
nan_sig = repmat(NaN,size(R));
warning(FLAG_WARNING); % restore warning status
- return;
-end;
+ return
+end
%%%%% ----- check independence of NaNs (missing values) -----
[nan_R, nan_sig] = corrcoef(X,double(isnan(X)));
@@ -370,7 +370,7 @@ nan_sig(isnan(nan_R)) = nan;
% remove diagonal elements, because these have not any meaning %
nan_R(isnan(nan_R)) = 0;
-if 0, any(nan_sig(:) < alpha),
+if 0, any(nan_sig(:) < alpha)
tmp = nan_sig(:); % Hack to skip NaN's in MIN(X)
min_sig = min(tmp(~isnan(tmp))); % Necessary, because Octave returns NaN rather than min(X) for min(NaN,X)
fprintf(1,'CORRCOFF Warning: Missing Values (i.e. NaNs) are not independent of data (p-value=%f)\n', min_sig);
@@ -378,10 +378,9 @@ if 0, any(nan_sig(:) < alpha),
fprintf(1,' The null-hypotheses (NaNs are uncorrelated) is rejected for the following parameter pair(s).\n');
[ix,iy] = find(nan_sig < alpha);
disp([ix,iy])
-end;
+end
%%%%% ----- end of independence check ------
warning(FLAG_WARNING); % restore warning status
-return;
diff --git a/matlab/missing/corrcoef/flag_implicit_skip_nan.m b/matlab/missing/corrcoef/flag_implicit_skip_nan.m
index 409b9f696..c86580d56 100644
--- a/matlab/missing/corrcoef/flag_implicit_skip_nan.m
+++ b/matlab/missing/corrcoef/flag_implicit_skip_nan.m
@@ -52,15 +52,15 @@ persistent FLAG_implicit_skip_nan;
%% if strcmp(version,'3.6'), FLAG_implicit_skip_nan=(1==1); end; %% hack for the use with Freemat3.6
%%% set DEFAULT value of FLAG
-if isempty(FLAG_implicit_skip_nan),
+if isempty(FLAG_implicit_skip_nan)
FLAG_implicit_skip_nan = (1==1); %logical(1); % logical.m not available on 2.0.16
-end;
+end
FLAG = FLAG_implicit_skip_nan;
-if nargin>0,
+if nargin>0
FLAG_implicit_skip_nan = (i~=0); %logical(i); %logical.m not available in 2.0.16
if (~i)
warning('flag_implicit_skipnan(0): You are warned!!! You have turned off skipping NaN in sumskipnan. This is not recommended. Make sure you really know what you do.')
- end;
-end;
+ end
+end
diff --git a/matlab/missing/corrcoef/sumskipnan.m b/matlab/missing/corrcoef/sumskipnan.m
index 78f8ecbc1..1c53fee6d 100644
--- a/matlab/missing/corrcoef/sumskipnan.m
+++ b/matlab/missing/corrcoef/sumskipnan.m
@@ -56,12 +56,12 @@ function [o,count,SSQ] = sumskipnan(x, DIM, W)
global FLAG_NANS_OCCURED;
-if nargin<2,
+if nargin<2
DIM = [];
-end;
-if nargin<3,
+end
+if nargin<3
W = [];
-end;
+end
% an efficient implementation in C of the following lines
% could significantly increase performance
@@ -78,19 +78,19 @@ end;
% o3 += tmp.*tmp;
% };
-if isempty(DIM),
+if isempty(DIM)
DIM = find(size(x)>1,1);
- if isempty(DIM), DIM = 1; end;
+ if isempty(DIM), DIM = 1; end
end
-if (DIM<1), DIM = 1; end; %% Hack, because min([])=0 for FreeMat v3.5
+if (DIM<1), DIM = 1; end %% Hack, because min([])=0 for FreeMat v3.5
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% non-float data
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-if (isempty(W) && (~(isa(x,'float') || isa(x,'double')))) || ~flag_implicit_skip_nan(), %%% skip always NaN's
+if (isempty(W) && (~(isa(x,'float') || isa(x,'double')))) || ~flag_implicit_skip_nan() %%% skip always NaN's
if ~isempty(W)
error('SUMSKIPNAN: weighted sum of integers not supported, yet');
- end;
+ end
x = double(x);
o = sum(x,DIM);
if nargout>1
@@ -101,16 +101,16 @@ if (isempty(W) && (~(isa(x,'float') || isa(x,'double')))) || ~flag_implicit_ski
if nargout>2
x = x.*x;
SSQ = sum(x,DIM);
- end;
- end;
- return;
-end;
+ end
+ end
+ return
+end
if (length(size(x))<DIM)
error('SUMSKIPNAN: DIM argument larger than number of dimensions of x');
elseif ~isempty(W) && (size(x,DIM)~=numel(W))
error('SUMSKIPNAN: size of weight vector does not match size(x,DIM)');
-end;
+end
%% mex and oct files expect double
x = double(x);
@@ -124,18 +124,18 @@ try
%% using sumskipnan_mex.mex
%% !!! hack: FLAG_NANS_OCCURED is an output argument, reserve memory !!!
- if isempty(FLAG_NANS_OCCURED),
+ if isempty(FLAG_NANS_OCCURED)
FLAG_NANS_OCCURED = logical(0); % default value
- end;
+ end
- if (nargout<2),
+ if (nargout<2)
o = sumskipnan_mex(real(x),DIM,FLAG_NANS_OCCURED,W);
if (~isreal(x))
io = sumskipnan_mex(imag(x),DIM,FLAG_NANS_OCCURED,W);
o = o + i*io;
- end;
- return;
- elseif (nargout==2),
+ end
+ return
+ elseif (nargout==2)
[o,count] = sumskipnan_mex(real(x),DIM,FLAG_NANS_OCCURED,W);
if (~isreal(x))
[io,icount] = sumskipnan_mex(imag(x),DIM,FLAG_NANS_OCCURED,W);
@@ -143,10 +143,10 @@ try
error('Number of NaNs differ for REAL and IMAG part');
else
o = o+i*io;
- end;
- end;
- return;
- elseif (nargout>=3),
+ end
+ end
+ return
+ elseif (nargout>=3)
[o,count,SSQ] = sumskipnan_mex(real(x),DIM,FLAG_NANS_OCCURED,W);
if (~isreal(x))
[io,icount,iSSQ] = sumskipnan_mex(imag(x),DIM,FLAG_NANS_OCCURED,W);
@@ -155,23 +155,23 @@ try
else
o = o+i*io;
SSQ = SSQ+iSSQ;
- end;
- end;
- return;
- end;
-end;
+ end
+ end
+ return
+ end
+end
if ~isempty(W)
error('weighted sumskipnan requires sumskipnan_mex');
-end;
+end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% count non-NaN's
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-if nargout>1,
+if nargout>1
count = sum(x==x,DIM);
FLAG_NANS_OCCURED = any(count(:)<size(x,DIM));
-end;
+end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% replace NaN's with zero
@@ -179,10 +179,10 @@ end;
x(x~=x) = 0;
o = sum(x,DIM);
-if nargout>2,
+if nargout>2
x = real(x).^2 + imag(x).^2;
SSQ = sum(x,DIM);
-end;
+end
%!assert(sumskipnan([1,2],1),[1,2])
%!assert(sumskipnan([1,NaN],2),1)
diff --git a/matlab/missing/corrcoef/tcdf.m b/matlab/missing/corrcoef/tcdf.m
index c282e0a17..1901c4f7d 100644
--- a/matlab/missing/corrcoef/tcdf.m
+++ b/matlab/missing/corrcoef/tcdf.m
@@ -37,10 +37,10 @@ if all(size(x)==1)
elseif all(size(n)==1)
n = repmat(n,size(x));
elseif all(size(x)==size(n))
- ; %% OK, do nothing
+ % OK, do nothing
else
error('size of input arguments must be equal or scalar')
-end;
+end
% allocate memory
p = zeros(size(x));
diff --git a/matlab/missing/ordeig/ordeig.m b/matlab/missing/ordeig/ordeig.m
index 6004fd86f..0cbcc8267 100644
--- a/matlab/missing/ordeig/ordeig.m
+++ b/matlab/missing/ordeig/ordeig.m
@@ -34,7 +34,7 @@ i = 1;
while i <= n
if i == n
eigs(n) = t(n,n);
- break;
+ break
elseif t(i+1,i) == 0
eigs(i) = t(i,i);
i = i+1;
diff --git a/matlab/missing/stats/betainv.m b/matlab/missing/stats/betainv.m
index 8273fc356..a7300d1b1 100644
--- a/matlab/missing/stats/betainv.m
+++ b/matlab/missing/stats/betainv.m
@@ -84,7 +84,7 @@ if (any (k))
end
h = y_old - y_new;
if (max (abs (h)) < sqrt (eps))
- break;
+ break
end
y_old = y_new;
end
diff --git a/matlab/missing/stats/corr.m b/matlab/missing/stats/corr.m
index 21cdda767..4f3ebfb7b 100644
--- a/matlab/missing/stats/corr.m
+++ b/matlab/missing/stats/corr.m
@@ -84,12 +84,12 @@ if isscalar(x)
else
retval = NaN(size(y));
end
- return;
+ return
end
if nargin==2 && isscalar(y)
retval = NaN(size(x'));
- return;
+ return
end
n = size (x, 1);
diff --git a/matlab/missing/stats/gaminv.m b/matlab/missing/stats/gaminv.m
index e879616c4..96c4a0a3f 100644
--- a/matlab/missing/stats/gaminv.m
+++ b/matlab/missing/stats/gaminv.m
@@ -76,7 +76,7 @@ if (any (k))
h = y_old - y_new;
end
if (max (abs (h)) < sqrt (eps))
- break;
+ break
end
y_old = y_new;
end
diff --git a/matlab/mode_check.m b/matlab/mode_check.m
index 3217dbd12..ac4497249 100644
--- a/matlab/mode_check.m
+++ b/matlab/mode_check.m
@@ -58,13 +58,13 @@ function mode_check(fun,x,hessian_mat,DynareDataset,DatasetInfo,DynareOptions,Mo
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
TeX = DynareOptions.TeX;
-if ~isempty(hessian_mat);
+if ~isempty(hessian_mat)
[ s_min, k ] = min(diag(hessian_mat));
end
fval = feval(fun,x,DynareDataset,DatasetInfo,DynareOptions,Model,EstimatedParameters,BayesInfo,BoundsInfo,DynareResults);
-if ~isempty(hessian_mat);
+if ~isempty(hessian_mat)
skipline()
disp('MODE CHECK')
skipline()
@@ -85,13 +85,13 @@ if TeX && any(strcmp('eps',cellstr(DynareOptions.graph_format)))
end
ll = DynareOptions.mode_check.neighbourhood_size;
-if isinf(ll),
+if isinf(ll)
DynareOptions.mode_check.symmetric_plots = 0;
end
mcheck = struct('cross',struct(),'emode',struct());
-for plt = 1:nbplt,
+for plt = 1:nbplt
if TeX
NAMES = [];
TeXNAMES = [];
@@ -134,7 +134,7 @@ for plt = 1:nbplt,
z1 = l1:((x(kk)-l1)/(DynareOptions.mode_check.number_of_points/2)):x(kk);
z2 = x(kk):((l2-x(kk))/(DynareOptions.mode_check.number_of_points/2)):l2;
z = union(z1,z2);
- if DynareOptions.mode_check.nolik==0,
+ if DynareOptions.mode_check.nolik==0
y = zeros(length(z),2);
dy = priordens(xx,BayesInfo.pshape,BayesInfo.p6,BayesInfo.p7,BayesInfo.p3,BayesInfo.p4);
end
@@ -174,7 +174,7 @@ for plt = 1:nbplt,
hold off
drawnow
end
- if DynareOptions.mode_check.nolik==0,
+ if DynareOptions.mode_check.nolik==0
if isoctave
axes('outerposition',[0.3 0.93 0.42 0.07],'box','on'),
else
diff --git a/matlab/model_diagnostics.m b/matlab/model_diagnostics.m
index 32a01725d..80854f499 100644
--- a/matlab/model_diagnostics.m
+++ b/matlab/model_diagnostics.m
@@ -67,7 +67,7 @@ end
info=test_for_deep_parameters_calibration(M);
if info
problem_dummy=1;
-end;
+end
% check if ys is steady state
options.debug=1; %locally set debug option to 1
@@ -83,7 +83,7 @@ if check1(1)
if any(isinf(dr.ys))
disp(['MODEL_DIAGNOSTICS: Steady state contains Inf'])
end
- return;
+ return
end
if ~isreal(dr.ys)
@@ -210,7 +210,7 @@ if ~options.block
else
[junk,jacobia_] = feval([M.fname '_dynamic'],z(iyr0),exo_simul, ...
M.params, dr.ys, it_);
- end;
+ end
elseif options.order >= 2
if (options.bytecode)
[chck, junk, loc_dr] = bytecode('dynamic','evaluate', z,exo_simul, ...
@@ -220,7 +220,7 @@ if ~options.block
[junk,jacobia_,hessian1] = feval([M.fname '_dynamic'],z(iyr0),...
exo_simul, ...
M.params, dr.ys, it_);
- end;
+ end
if options.use_dll
% In USE_DLL mode, the hessian is in the 3-column sparse representation
hessian1 = sparse(hessian1(:,1), hessian1(:,2), hessian1(:,3), ...
diff --git a/matlab/model_info.m b/matlab/model_info.m
index d99ca4807..4ceccd01b 100644
--- a/matlab/model_info.m
+++ b/matlab/model_info.m
@@ -1,4 +1,4 @@
-function model_info(varargin);
+function model_info(varargin)
%function model_info;
% Copyright (C) 2008-2012 Dynare Team
@@ -23,12 +23,12 @@ if sum(strcmp(varargin,'static')) > 0
static_ = 1;
else
static_ = 0;
-end;
+end
if sum(strcmp(varargin,'incidence')) > 0
incidence = 1;
else
incidence = 0;
-end;
+end
if static_
fprintf(' Informations about %s (static model)\n',M_.fname);
block_structre_str = 'block_structure_stat';
@@ -37,13 +37,13 @@ if static_
fprintf(' Informations about %s (dynamic model)\n',M_.fname);
block_structre_str = 'block_structure';
nb_leadlag = 3;
- end;
+ end
if(isfield(M_,block_structre_str))
if static_
block_structure = M_.block_structure_stat;
else
block_structure = M_.block_structure;
- end;
+ end
fprintf(strcat(' ===================',char(ones(1,length(M_.fname))*'='),'\n\n'));
nb_blocks=length(block_structure.block);
fprintf('The model has %d equations and is decomposed in %d blocks as follow:\n',M_.endo_nbr,nb_blocks);
@@ -54,15 +54,15 @@ if(isfield(M_,block_structre_str))
size_block=length(block_structure.block(i).equation);
if(i>1)
fprintf('|------------|------------|--------------------------------|----------------|---------------------------------|\n');
- end;
+ end
for j=1:size_block
if(j==1)
fprintf('| %10d | %10d | %30s | %14d | %-6d %24s |\n',i,size_block,Sym_type(block_structure.block(i).Simulation_Type),block_structure.block(i).equation(j),block_structure.block(i).variable(j),M_.endo_names(block_structure.block(i).variable(j),:));
else
fprintf('| %10s | %10s | %30s | %14d | %-6d %24s |\n','','','',block_structure.block(i).equation(j),block_structure.block(i).variable(j),M_.endo_names(block_structure.block(i).variable(j),:));
- end;
- end;
- end;
+ end
+ end
+ end
fprintf('===============================================================================================================\n');
fprintf('\n');
if static_
@@ -71,16 +71,16 @@ if(isfield(M_,block_structre_str))
IM=sortrows(block_structure.incidence.sparse_IM,2);
else
IM=[];
- end;
+ end
size_IM=size(IM,1);
last=99999999;
for i=1:size_IM
if(last~=IM(i,2))
fprintf('\n%-30s',M_.endo_names(IM(i,2),:));
- end;
+ end
fprintf(' %5d',IM(i,1));
last=IM(i,2);
- end;
+ end
fprintf('\n\n');
else
for k=1:M_.maximum_endo_lag+M_.maximum_endo_lead+1
@@ -90,24 +90,24 @@ if(isfield(M_,block_structre_str))
fprintf('%-30s %s %d','the variable','is used in equations with lag ',M_.maximum_endo_lag+1-k);
else
fprintf('%-30s %s %d','the variable','is used in equations with lead ',k-(M_.maximum_endo_lag+1));
- end;
+ end
if(size(block_structure.incidence(k).sparse_IM,1)>0)
IM=sortrows(block_structure.incidence(k).sparse_IM,2);
else
IM=[];
- end;
+ end
size_IM=size(IM,1);
last=99999999;
for i=1:size_IM
if(last~=IM(i,2))
fprintf('\n%-30s',M_.endo_names(IM(i,2),:));
- end;
+ end
fprintf(' %5d',IM(i,1));
last=IM(i,2);
- end;
+ end
fprintf('\n\n');
- end;
- end;
+ end
+ end
%printing the gross incidence matrix
IM_star = char([kron(ones(M_.endo_nbr, M_.endo_nbr-1), double(blanks(3))) double(blanks(M_.endo_nbr)')]);
@@ -118,9 +118,9 @@ if(isfield(M_,block_structre_str))
IM_star(block_structure.incidence(i).sparse_IM(j,1), 3 * (block_structure.incidence(i).sparse_IM(j,2) - 1) + 1) = 'X';
else
IM_star(block_structure.incidence(i).sparse_IM(j,1), 3 * (block_structure.incidence(i).sparse_IM(j,2) - 1) + 1) = '1';
- end;
- end;
- end;
+ end
+ end
+ end
seq = 1: M_.endo_nbr;
blank = [ blanks(size(M_.endo_names,2)); blanks(size(M_.endo_names,2))];
for i = 1:M_.endo_nbr
@@ -128,8 +128,8 @@ if(isfield(M_,block_structre_str))
var_names = [blank; M_.endo_names(i,:)];
else
var_names = [var_names; blank; M_.endo_names(i,:)];
- end;
- end;
+ end
+ end
if incidence
topp = [char(kron(double(blanks(ceil(log10(M_.endo_nbr)))),ones(size(M_.endo_names,2),1))) var_names' ];
bott = [int2str(seq') blanks(M_.endo_nbr)' blanks(M_.endo_nbr)' IM_star];
@@ -145,9 +145,9 @@ if(isfield(M_,block_structre_str))
cur_block = 1;
for i = 1:M_.endo_nbr
past_block = cur_block;
- while ismember(block_structure.variable_reordered(i), block_structure.block(cur_block).variable) == 0;
+ while ismember(block_structure.variable_reordered(i), block_structure.block(cur_block).variable) == 0
cur_block = cur_block + 1;
- end;
+ end
if i == 1
var_names = [blank; M_.endo_names(block_structure.variable_reordered(i),:)];
else
@@ -156,8 +156,8 @@ if(isfield(M_,block_structre_str))
else
var_names = [var_names; blank; M_.endo_names(block_structure.variable_reordered(i),:)];
end
- end;
- end;
+ end
+ end
topp = [char(kron(double(blanks(ceil(log10(M_.endo_nbr)))),ones(size(M_.endo_names,2),1))) var_names' ];
n_state_var = length(M_.state_var);
IM_state_var = zeros(n_state_var, n_state_var);
@@ -172,38 +172,38 @@ if(isfield(M_,block_structre_str))
[tfi, loci] = ismember(block_structure.incidence(i).sparse_IM(j,1), state_equation);
if tfi
IM_state_var(loci, loc) = 1;
- end;
+ end
else
IM_star_reordered(eq(block_structure.incidence(i).sparse_IM(j,1)), 3 * (va(block_structure.incidence(i).sparse_IM(j,2)) - 1) + 1) = '1';
- end;
- end;
- end;
+ end
+ end
+ end
fprintf('1: non nul element, X: non nul element related to a state variable\n');
cur_block = 1;
i_last = 0;
block = {};
- for i = 1:n_state_var;
+ for i = 1:n_state_var
past_block = cur_block;
- while ismember(M_.state_var(i), block_structure.block(cur_block).variable) == 0;
+ while ismember(M_.state_var(i), block_structure.block(cur_block).variable) == 0
cur_block = cur_block + 1;
- end;
+ end
if (past_block ~= cur_block) || (past_block == cur_block && i == n_state_var)
block(past_block).IM_state_var(1:(i - 1 - i_last), 1:i - 1) = IM_state_var(i_last+1:i - 1, 1:i - 1);
i_last = i - 1;
- end;
- end;
+ end
+ end
cur_block = 1;
for i = 1:M_.endo_nbr
past_block = cur_block;
- while ismember(block_structure.variable_reordered(i), block_structure.block(cur_block).variable) == 0;
+ while ismember(block_structure.variable_reordered(i), block_structure.block(cur_block).variable) == 0
cur_block = cur_block + 1;
- end;
+ end
if past_block ~= cur_block
for j = 1:i-1
IM_star_reordered(j, 3 * (i - 1) - 1) = '|';
- end;
- end;
+ end
+ end
end
bott = [int2str(block_structure.equation_reordered') blanks(M_.endo_nbr)' blanks(M_.endo_nbr)' IM_star_reordered];
@@ -211,10 +211,10 @@ if(isfield(M_,block_structre_str))
fprintf(' ==========================\n');
disp([topp; bott]);
fprintf('1: non nul element, X: non nul element related to a state variable\n');
- end;
+ end
else
fprintf('There is no block decomposition of the model.\nUse ''block'' model''s option.\n');
-end;
+end
function ret=Sym_type(type)
UNKNOWN=0;
@@ -229,32 +229,32 @@ SOLVE_TWO_BOUNDARIES_COMPLETE=8;
EVALUATE_FORWARD_R=9;
EVALUATE_BACKWARD_R=10;
switch (type)
- case (UNKNOWN),
+ case (UNKNOWN)
ret='UNKNOWN ';
- case {EVALUATE_FORWARD,EVALUATE_FORWARD_R},
+ case {EVALUATE_FORWARD,EVALUATE_FORWARD_R}
ret='EVALUATE FORWARD ';
- case {EVALUATE_BACKWARD,EVALUATE_BACKWARD_R},
+ case {EVALUATE_BACKWARD,EVALUATE_BACKWARD_R}
ret='EVALUATE BACKWARD ';
- case SOLVE_FORWARD_SIMPLE,
+ case SOLVE_FORWARD_SIMPLE
ret='SOLVE FORWARD SIMPLE ';
- case SOLVE_BACKWARD_SIMPLE,
+ case SOLVE_BACKWARD_SIMPLE
ret='SOLVE BACKWARD SIMPLE ';
- case SOLVE_TWO_BOUNDARIES_SIMPLE,
+ case SOLVE_TWO_BOUNDARIES_SIMPLE
ret='SOLVE TWO BOUNDARIES SIMPLE ';
- case SOLVE_FORWARD_COMPLETE,
+ case SOLVE_FORWARD_COMPLETE
ret='SOLVE FORWARD COMPLETE ';
- case SOLVE_BACKWARD_COMPLETE,
+ case SOLVE_BACKWARD_COMPLETE
ret='SOLVE BACKWARD COMPLETE ';
- case SOLVE_TWO_BOUNDARIES_COMPLETE,
+ case SOLVE_TWO_BOUNDARIES_COMPLETE
ret='SOLVE TWO BOUNDARIES COMPLETE';
-end;
+end
function ret = barre(n)
s = [];
-for i=1:n;
+for i=1:n
s = [s '|'];
-end;
+end
ret = s;
diff --git a/matlab/moment_function.m b/matlab/moment_function.m
index af0488a59..f10de3c5e 100644
--- a/matlab/moment_function.m
+++ b/matlab/moment_function.m
@@ -61,7 +61,7 @@ end
if penalty>0
flag = 0;
- return;
+ return
end
save('estimated_parameters.mat','xparams');
diff --git a/matlab/myboxplot.m b/matlab/myboxplot.m
index fc54607e2..4a8b33658 100644
--- a/matlab/myboxplot.m
+++ b/matlab/myboxplot.m
@@ -33,7 +33,7 @@ if notched==1, notched=0.25; end
a=1-notched;
% ## figure out how many data sets we have
-if iscell(data),
+if iscell(data)
nc = length(data);
else
% if isvector(data), data = data(:); end
@@ -149,7 +149,7 @@ cap_y = whisker_y([1,1],:);
mm=min(min(data));
MM=max(max(data));
-if isnan(mm), mm=0; MM=0; end,
+if isnan(mm), mm=0; MM=0; end
if vertical
plot (quartile_x, quartile_y, 'b', ...
@@ -171,7 +171,7 @@ else
% % % % % outliers2_y, outliers2_x, [symbol(2),"r;;"]);
end
-if nargout,
+if nargout
sout=s;
end
% % % endfunction
\ No newline at end of file
diff --git a/matlab/mydelete.m b/matlab/mydelete.m
index 13ef6ee9d..06795b084 100644
--- a/matlab/mydelete.m
+++ b/matlab/mydelete.m
@@ -18,16 +18,16 @@ function mydelete(fname,pname)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-if nargin ==0,
+if nargin ==0
disp('mydelete(fname)')
return
end
-if nargin ==1,
+if nargin ==1
pname='';
end
file_to_delete = dir([pname,fname]);
-for j=1:length(file_to_delete),
+for j=1:length(file_to_delete)
delete([pname,file_to_delete(j).name]);
end
diff --git a/matlab/occbin/call_solve_one_constraint.m b/matlab/occbin/call_solve_one_constraint.m
index b4ec1baed..c613b5034 100755
--- a/matlab/occbin/call_solve_one_constraint.m
+++ b/matlab/occbin/call_solve_one_constraint.m
@@ -1,5 +1,5 @@
% Solve model, generate model IRFs
-[zdatalinear zdatapiecewise zdatass oobase_ Mbase_ ] = ...
+[zdatalinear, zdatapiecewise, zdatass, oobase_, Mbase_ ] = ...
solve_one_constraint(modnam,modnamstar,...
constraint, constraint_relax,...
shockssequence,irfshock,nperiods,maxiter);
diff --git a/matlab/occbin/call_solve_two_constraints.m b/matlab/occbin/call_solve_two_constraints.m
index b782e6db7..3adda90d7 100755
--- a/matlab/occbin/call_solve_two_constraints.m
+++ b/matlab/occbin/call_solve_two_constraints.m
@@ -1,4 +1,4 @@
-[zdatalinear zdatapiecewise zdatass oobase_ Mbase_] = solve_two_constraints(...
+[zdatalinear, zdatapiecewise, zdatass, oobase_, Mbase_] = solve_two_constraints(...
modnam_00,modnam_10,modnam_01,modnam_11,...
constraint1, constraint2,...
constraint_relax1, constraint_relax2,...
diff --git a/matlab/occbin/get_deriv.m b/matlab/occbin/get_deriv.m
index 24f1b42ae..d1fe78032 100755
--- a/matlab/occbin/get_deriv.m
+++ b/matlab/occbin/get_deriv.m
@@ -77,7 +77,7 @@ for i=1:nlea_cols
end
-for i = 1:M_.exo_nbr;
+for i = 1:M_.exo_nbr
j(:,i) =g1(:,i+ny);
end
diff --git a/matlab/occbin/get_pq.m b/matlab/occbin/get_pq.m
index 5caab79af..2924eacf5 100755
--- a/matlab/occbin/get_pq.m
+++ b/matlab/occbin/get_pq.m
@@ -1,4 +1,4 @@
-function [p,q]=get_pq(dr_,nstatic,nfwrd);
+function [p,q]=get_pq(dr_,nstatic,nfwrd)
nvars = size(dr_.ghx,1);
nshocks = size(dr_.ghu,2);
diff --git a/matlab/occbin/makechart.m b/matlab/occbin/makechart.m
index a3801e956..c3ea7719e 100755
--- a/matlab/occbin/makechart.m
+++ b/matlab/occbin/makechart.m
@@ -49,9 +49,9 @@ for i = 1:nvars
h1=plot(xvalues,zdata1(:,i),'b-','linewidth',2); hold on
h1=plot(xvalues,zdata2(:,i),'r--','linewidth',2); hold on
h2=plot(xvalues,zdata3(:,i),'b-','LineWidth',3);
- [x0 x1 y10 y11] = pickaxes(xvalues,zdata1(:,i));
- [x0 x1 y20 y21] = pickaxes(xvalues,zdata2(:,i));
- [x0 x1 y30 y31] = pickaxes(xvalues,zdata3(:,i));
+ [x0, x1, y10, y11] = pickaxes(xvalues,zdata1(:,i));
+ [x0, x1, y20, y21] = pickaxes(xvalues,zdata2(:,i));
+ [x0, x1, y30, y31] = pickaxes(xvalues,zdata3(:,i));
y0 = min([y10,y20,y30]);
y1 = max([y11,y21,y31]);
if y0==y1
diff --git a/matlab/occbin/makechart9.m b/matlab/occbin/makechart9.m
index c6e65afcd..8f9ae5479 100755
--- a/matlab/occbin/makechart9.m
+++ b/matlab/occbin/makechart9.m
@@ -72,10 +72,10 @@ elseif (nvars==5 | nvars ==6)
elseif (nvars==7 | nvars==8)
nrows = 4;
ncols = 2;
-elseif nvars>8 & nvars<=12;
+elseif nvars>8 & nvars<=12
nrows = 3;
ncols = 4;
-elseif nvars>12 & nvars<=15;
+elseif nvars>12 & nvars<=15
nrows = 5;
ncols = 3;
else
@@ -92,13 +92,13 @@ for i = 1:nvars
xvalues,zdata5(:,i),'g',...
xvalues,zdata6(:,i),'c',...
xvalues,zdata7(:,i),'y');
- [x0 x1 y10 y11] = pickaxes(xvalues,zdata1(:,i));
- [x0 x1 y20 y21] = pickaxes(xvalues,zdata2(:,i));
- [x0 x1 y30 y31] = pickaxes(xvalues,zdata3(:,i));
- [x0 x1 y40 y41] = pickaxes(xvalues,zdata4(:,i));
- [x0 x1 y50 y51] = pickaxes(xvalues,zdata5(:,i));
- [x0 x1 y60 y61] = pickaxes(xvalues,zdata6(:,i));
- [x0 x1 y70 y71] = pickaxes(xvalues,zdata7(:,i));
+ [x0, x1, y10, y11] = pickaxes(xvalues,zdata1(:,i));
+ [x0, x1, y20, y21] = pickaxes(xvalues,zdata2(:,i));
+ [x0, x1, y30, y31] = pickaxes(xvalues,zdata3(:,i));
+ [x0, x1, y40, y41] = pickaxes(xvalues,zdata4(:,i));
+ [x0, x1, y50, y51] = pickaxes(xvalues,zdata5(:,i));
+ [x0, x1, y60, y61] = pickaxes(xvalues,zdata6(:,i));
+ [x0, x1, y70, y71] = pickaxes(xvalues,zdata7(:,i));
grid on
y0 = min([y10,y20,y30,y40,y50,y60,y70]);
y1 = max([y11,y21,y31,y41,y51,y61,y71]);
diff --git a/matlab/occbin/map_regime.m b/matlab/occbin/map_regime.m
index a3ed88b47..1c84871bd 100755
--- a/matlab/occbin/map_regime.m
+++ b/matlab/occbin/map_regime.m
@@ -1,4 +1,4 @@
-function [regime regimestart]=map_regimes(violvecbool)
+function [regime, regimestart]=map_regimes(violvecbool)
nperiods = length(violvecbool)-1;
diff --git a/matlab/occbin/mkdatap_anticipated.m b/matlab/occbin/mkdatap_anticipated.m
index 524d3dd5d..6fef8c7f2 100755
--- a/matlab/occbin/mkdatap_anticipated.m
+++ b/matlab/occbin/mkdatap_anticipated.m
@@ -12,7 +12,7 @@ if nargin<16
init=zeros(nvars,1);
end
-if nargin<15;
+if nargin<15
scalefactormod=1;
end
diff --git a/matlab/occbin/mkdatap_anticipated_2constraints.m b/matlab/occbin/mkdatap_anticipated_2constraints.m
index b05c90d6d..85da740e5 100755
--- a/matlab/occbin/mkdatap_anticipated_2constraints.m
+++ b/matlab/occbin/mkdatap_anticipated_2constraints.m
@@ -16,7 +16,7 @@ if nargin<16
init=zeros(nvars,1);
end
-if nargin<15;
+if nargin<15
scalefactormod=1;
end
diff --git a/matlab/occbin/solve_no_constraint_noclear.m b/matlab/occbin/solve_no_constraint_noclear.m
index 309c5c546..0dab8c816 100755
--- a/matlab/occbin/solve_no_constraint_noclear.m
+++ b/matlab/occbin/solve_no_constraint_noclear.m
@@ -1,6 +1,6 @@
-function [zdata oobase_ Mbase_ ] = ...
+function [zdata, oobase_, Mbase_ ] = ...
solve_no_constraint_noclear(modnam,...
- shockssequence,irfshock,nperiods);
+ shockssequence,irfshock,nperiods)
global M_ oo_
diff --git a/matlab/occbin/solve_one_constraint.m b/matlab/occbin/solve_one_constraint.m
index c446f4c40..c8a7c2494 100755
--- a/matlab/occbin/solve_one_constraint.m
+++ b/matlab/occbin/solve_one_constraint.m
@@ -24,7 +24,7 @@
% 6/17/2013 -- Luca replaced external .m file setss.m
-function [zdatalinear_ zdatapiecewise_ zdatass_ oobase_ Mbase_ ] = ...
+function [zdatalinear_, zdatapiecewise_, zdatass_, oobase_, Mbase_ ] = ...
solve_one_constraint(modnam_,modnamstar_,...
constraint_, constraint_relax_,...
shockssequence_,irfshock_,nperiods_,maxiter_,init_)
@@ -140,7 +140,7 @@ for ishock_ = 1:nshocks_
iter_ = iter_ +1;
% analyze when each regime starts based on current guess
- [regime regimestart]=map_regime(violvecbool_);
+ [regime, regimestart]=map_regime(violvecbool_);
diff --git a/matlab/occbin/solve_two_constraints.m b/matlab/occbin/solve_two_constraints.m
index dfca403a2..ff5f734ed 100755
--- a/matlab/occbin/solve_two_constraints.m
+++ b/matlab/occbin/solve_two_constraints.m
@@ -29,7 +29,7 @@
% to be processed.
% 6/17/2013 -- Luca replaced external .m file setss.m
-function [ zdatalinear_ zdatapiecewise_ zdatass_ oo00_ M00_ ] = ...
+function [ zdatalinear_, zdatapiecewise_, zdatass_, oo00_ , M00_ ] = ...
solve_two_constraints(modnam_00_,modnam_10_,modnam_01_,modnam_11_,...
constrain1_, constrain2_,...
constraint_relax1_, constraint_relax2_,...
@@ -220,8 +220,8 @@ for ishock_ = 1:nshocks
% analyse violvec and isolate contiguous periods in the other
% regime.
- [regime1 regimestart1]=map_regime(violvecbool_(:,1));
- [regime2 regimestart2]=map_regime(violvecbool_(:,2));
+ [regime1, regimestart1]=map_regime(violvecbool_(:,1));
+ [regime2, regimestart2]=map_regime(violvecbool_(:,2));
[zdatalinear_]=mkdatap_anticipated_2constraints(nperiods_,decrulea,decruleb,...
diff --git a/matlab/occbin/tokenize.m b/matlab/occbin/tokenize.m
index f6e9f330c..b711ca082 100755
--- a/matlab/occbin/tokenize.m
+++ b/matlab/occbin/tokenize.m
@@ -28,7 +28,7 @@ else
ndelims = length(posdelims);
% build positions for substrings
delims = zeros(ndelims+1,2);
- for i=1:ndelims+1;
+ for i=1:ndelims+1
if i==1
if posdelims(1) == 1
tokens = cellstr(source(1));
diff --git a/matlab/optimization/apprgrdn.m b/matlab/optimization/apprgrdn.m
index 9f16e4466..633cfbf9c 100644
--- a/matlab/optimization/apprgrdn.m
+++ b/matlab/optimization/apprgrdn.m
@@ -51,7 +51,7 @@ for i=1:n
y(i)=x(i)+di(i);
fi=feval(fun,y,varargin{:});
if obj
- if fi==f,
+ if fi==f
for j=1:3
di(i)=di(i)*10; y(i)=x(i)+di(i);
fi=feval(fun,y,varargin{:});
diff --git a/matlab/optimization/cmaes.m b/matlab/optimization/cmaes.m
index 833dbe9b2..8ec94e5ea 100644
--- a/matlab/optimization/cmaes.m
+++ b/matlab/optimization/cmaes.m
@@ -283,7 +283,7 @@ if nargin < 1 || isequal(fitfun, 'defaults') % pass default options
if nargin > 1 % supplement second argument with default options
xmin = getoptions(xstart, defopts);
end
- return;
+ return
end
if isequal(fitfun, 'displayoptions')
@@ -291,7 +291,7 @@ if isequal(fitfun, 'displayoptions')
for name = names'
disp([name{:} repmat(' ', 1, 20-length(name{:})) ': ''' defopts.(name{:}) '''']);
end
- return;
+ return
end
input.fitfun = fitfun; % record used input
@@ -378,7 +378,7 @@ if ~flgresume % not resuming a former run
else % flgresume is true, do resume former run
tmp = whos('-file', opts.SaveFilename);
for i = 1:length(tmp)
- if strcmp(tmp(i).name, 'localopts');
+ if strcmp(tmp(i).name, 'localopts')
error('Saved variables include variable "localopts", please remove');
end
end
@@ -576,7 +576,7 @@ else % flgresume
if any(lbounds>ubounds)
error('lower bound found to be greater than upper bound');
end
- [xmean ti] = xintobounds(xmean, lbounds, ubounds); % just in case
+ [xmean, ti] = xintobounds(xmean, lbounds, ubounds); % just in case
if any(ti)
warning('Initial point was out of bounds, corrected');
end
@@ -910,7 +910,7 @@ while isempty(stopflag)
% non-parallel evaluation and remaining NaN-values
% set also the reevaluated solution to NaN
fitness.raw(lambda + find(isnan(fitness.raw(1:noiseReevals)))) = NaN;
- for k=find(isnan(fitness.raw)),
+ for k=find(isnan(fitness.raw))
% fitness.raw(k) = NaN;
tries = 0;
% Resample, until fitness is not NaN
@@ -987,7 +987,7 @@ while isempty(stopflag)
bnd.dfithist = [bnd.dfithist(2:end) val];
end
- [tx ti] = xintobounds(xmean, lbounds, ubounds);
+ [tx, ti] = xintobounds(xmean, lbounds, ubounds);
% Set initial weights
if bnd.iniphase
@@ -1148,8 +1148,8 @@ while isempty(stopflag)
% i-th longest becomes i-th shortest
% TODO: this is not in compliance with the paper Hansen&Ros2010,
% where simply arnorms = arnorms(end:-1:1) ?
- [arnorms idxnorms] = sort(sqrt(sum(arzneg.^2, 1)));
- [ignore idxnorms] = sort(idxnorms); % inverse index
+ [arnorms, idxnorms] = sort(sqrt(sum(arzneg.^2, 1)));
+ [ignore, idxnorms] = sort(idxnorms); % inverse index
arnormfacs = arnorms(end:-1:1) ./ arnorms;
% arnormfacs = arnorms(randperm(neg.mu)) ./ arnorms;
arnorms = arnorms(end:-1:1); % for the record
@@ -1510,13 +1510,13 @@ while isempty(stopflag)
while fid > 0
strline = fgetl(fid); %fgets(fid, 300);
if strline < 0 % fgets and fgetl returns -1 at end of file
- break;
+ break
end
% 'stop filename' sets stopflag to manual
str = sscanf(strline, ' %s %s', 2);
if strcmp(str, ['stop' opts.LogFilenamePrefix])
stopflag(end+1) = {'manual'};
- break;
+ break
end
% 'skip filename run 3' skips a run, but not the last
str = sscanf(strline, ' %s %s %s', 3);
@@ -1545,8 +1545,8 @@ while isempty(stopflag)
if mod(countiter, verbosemodulo) < 1 ...
|| (verbosemodulo > 0 && isfinite(verbosemodulo) && ...
(countiter < 3 || ~isempty(stopflag)))
- [minstd minstdidx] = min(sigma*sqrt(diagC));
- [maxstd maxstdidx] = max(sigma*sqrt(diagC));
+ [minstd, minstdidx] = min(sigma*sqrt(diagC));
+ [maxstd, maxstdidx] = max(sigma*sqrt(diagC));
% format display nicely
disp([repmat(' ',1,4-floor(log10(countiter))) ...
num2str(countiter) ' , ' ...
@@ -1749,7 +1749,7 @@ end
|| any(strcmp(stopflag, 'maxfunevals')) ...
|| any(strcmp(stopflag, 'stoptoresume')) ...
|| any(strcmp(stopflag, 'manual'))
- break;
+ break
end
end % while irun <= Restarts
@@ -1839,10 +1839,10 @@ function opts=getoptions(inopts, defopts)
if nargin < 2 || isempty(defopts) % no default options available
opts=inopts;
- return;
+ return
elseif isempty(inopts) % empty inopts invoke default options
opts = defopts;
- return;
+ return
elseif ~isstruct(defopts) % handle a single option value
if isempty(inopts)
opts = defopts;
@@ -1851,7 +1851,7 @@ elseif ~isstruct(defopts) % handle a single option value
else
error('Input options are a struct, while default options are not');
end
- return;
+ return
elseif ~isstruct(inopts) % no valid input options
error('The options need to be a struct or empty');
end
@@ -1989,7 +1989,7 @@ end
% sort inar
if nargin < 3 || isempty(idx)
- [sar idx] = sort(inar);
+ [sar, idx] = sort(inar);
else
sar = inar(idx);
end
@@ -2024,7 +2024,7 @@ end
-function [s ranks rankDelta] = local_noisemeasurement(arf1, arf2, lamreev, theta, cutlimit)
+function [s, ranks, rankDelta] = local_noisemeasurement(arf1, arf2, lamreev, theta, cutlimit)
% function [s ranks rankDelta] = noisemeasurement(arf1, arf2, lamreev, theta)
%
% Input:
@@ -2207,7 +2207,7 @@ manual_mode = 0;
% plot fitness etc
foffset = 1e-99;
dfit = d.f(:,6)-min(d.f(:,6));
- [ignore idxbest] = min(dfit);
+ [ignore, idxbest] = min(dfit);
dfit(dfit<1e-98) = NaN;
subplot(2,2,1); hold off;
dd = abs(d.f(:,7:8)) + foffset;
@@ -2308,7 +2308,7 @@ manual_mode = 0;
ax(2) = max(minxend, ax(2));
axis(ax);
% add some annotation lines
- [ignore idx] = sort(d.std(end,6:end));
+ [ignore, idx] = sort(d.std(end,6:end));
% choose no more than 25 indices
idxs = round(linspace(1, size(d.x,2)-5, min(size(d.x,2)-5, 25)));
yy = repmat(NaN, 2, size(d.std,2)-5);
@@ -2565,7 +2565,7 @@ function f=fbaluja(x)
function f=fschwefel(x)
f = 0;
- for i = 1:size(x,1),
+ for i = 1:size(x,1)
f = f+sum(x(1:i))^2;
end
@@ -2662,7 +2662,7 @@ function f=fsharpR(x)
f = abs(-x(1, :)).^2 + 100 * sqrt(sum(x(2:end,:).^2, 1));
function f=frosen(x)
- if size(x,1) < 2 error('dimension must be greater one'); end
+ if size(x,1) < 2, error('dimension must be greater one'); end
N = size(x,1);
popsi = size(x,2);
f = 1e2*sum((x(1:end-1,:).^2 - x(2:end,:)).^2,1) + sum((x(1:end-1,:)-1).^2,1);
@@ -2704,7 +2704,7 @@ function f=fschwefelrosen2(x)
f=sum((x(2:end).^2-x(1)).^2 + (x(2:end)-1).^2);
function f=fdiffpow(x)
- [N popsi] = size(x); if N < 2 error('dimension must be greater one'); end
+ [N, popsi] = size(x); if N < 2 error('dimension must be greater one'); end
f = sum(abs(x).^repmat(2+10*(0:N-1)'/(N-1), 1, popsi), 1);
f = sqrt(f);
diff --git a/matlab/optimization/csminit1.m b/matlab/optimization/csminit1.m
index 1a0795195..4184af2df 100644
--- a/matlab/optimization/csminit1.m
+++ b/matlab/optimization/csminit1.m
@@ -216,7 +216,7 @@ else
end
end
lambda=lambda*factor;
- if abs(lambda) > 1e20;
+ if abs(lambda) > 1e20
retcode = 5;
done =1;
end
diff --git a/matlab/optimization/csminwel1.m b/matlab/optimization/csminwel1.m
index 52a018792..7b067a0a8 100644
--- a/matlab/optimization/csminwel1.m
+++ b/matlab/optimization/csminwel1.m
@@ -139,7 +139,7 @@ while ~done
else
if NumGrad
[g1, badg1]=get_num_grad(method,fcn,penalty,f1,x1,epsilon,varargin{:});
- elseif ischar(grad),
+ elseif ischar(grad)
[g1, badg1] = grad(x1,varargin{:});
else
[junk1,cost_flag,g1] = penalty_objective_function(x1,fcn,penalty,varargin{:});
@@ -166,7 +166,7 @@ while ~done
else
if NumGrad
[g2, badg2]=get_num_grad(method,fcn,penalty,f2,x2,epsilon,varargin{:});
- elseif ischar(grad),
+ elseif ischar(grad)
[g2, badg2] = grad(x2,varargin{:});
else
[junk2,cost_flag,g2] = penalty_objective_function(x1,fcn,penalty,varargin{:});
@@ -198,7 +198,7 @@ while ~done
else
if NumGrad
[g3, badg3]=get_num_grad(method,fcn,penalty,f3,x3,epsilon,varargin{:});
- elseif ischar(grad),
+ elseif ischar(grad)
[g3, badg3] = grad(x3,varargin{:});
else
[junk3,cost_flag,g3] = penalty_objective_function(x1,fcn,penalty,varargin{:});
@@ -258,7 +258,7 @@ while ~done
if nogh
if NumGrad
[gh, badgh]=get_num_grad(method,fcn,penalty,fh,xh,epsilon,varargin{:});
- elseif ischar(grad),
+ elseif ischar(grad)
[gh, badgh] = grad(xh,varargin{:});
else
[junkh,cost_flag,gh] = penalty_objective_function(x1,fcn,penalty,varargin{:});
diff --git a/matlab/optimization/dynare_minimize_objective.m b/matlab/optimization/dynare_minimize_objective.m
index 30705f54a..4a99e7841 100644
--- a/matlab/optimization/dynare_minimize_objective.m
+++ b/matlab/optimization/dynare_minimize_objective.m
@@ -77,7 +77,7 @@ switch minimizer_algorithm
if options_.silent_optimizer
optim_options = optimset(optim_options,'display','off');
end
- if options_.analytic_derivation,
+ if options_.analytic_derivation
optim_options = optimset(optim_options,'GradObj','on','TolX',1e-7);
end
[opt_par_values,fval,exitflag,output,lamdba,grad,hessian_mat] = ...
@@ -148,7 +148,7 @@ switch minimizer_algorithm
if ~isempty(options_.optim_opt)
eval(['optim_options = optimset(optim_options,' options_.optim_opt ');']);
end
- if options_.analytic_derivation,
+ if options_.analytic_derivation
optim_options = optimset(optim_options,'GradObj','on');
end
if options_.silent_optimizer
diff --git a/matlab/optimization/gmhmaxlik.m b/matlab/optimization/gmhmaxlik.m
index 3710d8d65..b479a31a2 100644
--- a/matlab/optimization/gmhmaxlik.m
+++ b/matlab/optimization/gmhmaxlik.m
@@ -19,7 +19,7 @@ function [PostMode, HessianMatrix, Scale, ModeValue] = gmhmaxlik(fun, xinit, Hin
% Set default options
-if ~isempty(Hinit);
+if ~isempty(Hinit)
gmhmaxlikOptions.varinit = 'previous';
else
gmhmaxlikOptions.varinit = 'prior';
diff --git a/matlab/optimization/mr_gstep.m b/matlab/optimization/mr_gstep.m
index 605508d2c..f6533a5d9 100644
--- a/matlab/optimization/mr_gstep.m
+++ b/matlab/optimization/mr_gstep.m
@@ -29,7 +29,7 @@ function [f0, x, ig] = mr_gstep(h1,x,bounds,func0,penalty,htol0,Verbose,Save_fil
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
n=size(x,1);
-if isempty(h1),
+if isempty(h1)
h1=varargin{3}.gradient_epsilon*ones(n,1);
end
@@ -39,7 +39,7 @@ if isempty(htol0)
else
htol = htol0;
end
-if length(htol)==1,
+if length(htol)==1
htol=htol*ones(n,1);
end
f0=penalty_objective_function(x,func0,penalty,varargin{:});
@@ -72,7 +72,7 @@ while i<n
gg(i)=(f1(i)'-f_1(i)')./(2.*h1(i));
hh(i) = 1/max(1.e-9,abs( (f1(i)+f_1(i)-2*f0)./(h1(i)*h1(i)) ));
if gg(i)*(hh(i)*gg(i))/2 > htol(i)
- [f0 x fc retcode] = csminit1(func0,x,penalty,f0,gg,0,diag(hh),Verbose,varargin{:});
+ [f0, x, fc, retcode] = csminit1(func0,x,penalty,f0,gg,0,diag(hh),Verbose,varargin{:});
ig(i)=1;
if Verbose
fprintf(['Done for param %s = %8.4f\n'],varargin{6}.name{i},x(i))
@@ -95,12 +95,12 @@ return
function x = check_bounds(x,bounds)
inx = find(x>=bounds(:,2));
-if ~isempty(inx),
+if ~isempty(inx)
x(inx) = bounds(inx,2)-eps;
end
inx = find(x<=bounds(:,1));
-if ~isempty(inx),
+if ~isempty(inx)
x(inx) = bounds(inx,1)+eps;
end
diff --git a/matlab/optimization/mr_hessian.m b/matlab/optimization/mr_hessian.m
index eb1c0752e..4ffb3bdc3 100644
--- a/matlab/optimization/mr_hessian.m
+++ b/matlab/optimization/mr_hessian.m
@@ -67,7 +67,7 @@ n=size(x,1);
h2=varargin{7}.ub-varargin{7}.lb;
hmax=varargin{7}.ub-x;
hmax=min(hmax,x-varargin{7}.lb);
-if isempty(ff0),
+if isempty(ff0)
outer_product_gradient=0;
else
outer_product_gradient=1;
@@ -109,7 +109,7 @@ while i<n
while (abs(dx(it))<0.5*hess_info.htol || abs(dx(it))>(3*hess_info.htol)) && icount<10 && ic==0
icount=icount+1;
if abs(dx(it))<0.5*hess_info.htol
- if abs(dx(it)) ~= 0,
+ if abs(dx(it)) ~= 0
hess_info.h1(i)=min(max(1.e-10,0.3*abs(x(i))), 0.9*hess_info.htol/abs(dx(it))*hess_info.h1(i));
else
hess_info.h1(i)=2.1*hess_info.h1(i);
@@ -147,8 +147,8 @@ while i<n
end
end
f1(:,i)=fx;
- if outer_product_gradient,
- if any(isnan(ffx)) || isempty(ffx),
+ if outer_product_gradient
+ if any(isnan(ffx)) || isempty(ffx)
ff1=ones(size(ff0)).*fx/length(ff0);
else
ff1=ffx;
@@ -157,8 +157,8 @@ while i<n
xh1(i)=x(i)-hess_info.h1(i);
[fx,exit_flag,ffx]=penalty_objective_function(xh1,func,penalty,varargin{:});
f_1(:,i)=fx;
- if outer_product_gradient,
- if any(isnan(ffx)) || isempty(ffx),
+ if outer_product_gradient
+ if any(isnan(ffx)) || isempty(ffx)
ff_1=ones(size(ff0)).*fx/length(ff0);
else
ff_1=ffx;
@@ -180,7 +180,7 @@ xh_1=xh1;
gg=(f1'-f_1')./(2.*hess_info.h1);
-if outer_product_gradient,
+if outer_product_gradient
if hflag==2
gg=(f1'-f_1')./(2.*hess_info.h1);
hessian_mat = zeros(size(f0,1),n*n);
diff --git a/matlab/optimization/newrat.m b/matlab/optimization/newrat.m
index 8085316d0..5bec31e7a 100644
--- a/matlab/optimization/newrat.m
+++ b/matlab/optimization/newrat.m
@@ -86,7 +86,7 @@ fval=fval0;
outer_product_gradient=1;
if isempty(hh)
[dum, gg, htol0, igg, hhg, h1, hess_info]=mr_hessian(x,func0,penalty,flagit,htol,hess_info,varargin{:});
- if isempty(dum),
+ if isempty(dum)
outer_product_gradient=0;
igg = 1e-4*eye(nx);
else
@@ -154,7 +154,7 @@ while norm(gg)>gtol && check==0 && jit<nit
if length(find(ig))<nx
ggx=ggx*0;
ggx(find(ig))=gg(find(ig));
- if analytic_derivation,
+ if analytic_derivation
hhx=hh;
else
hhx = reshape(dum,nx,nx);
@@ -195,7 +195,7 @@ while norm(gg)>gtol && check==0 && jit<nit
if (fval0(icount)-fval)<ftol
disp_verbose('No further improvement is possible!',Verbose)
check=1;
- if analytic_derivation,
+ if analytic_derivation
[fvalx,exit_flag,gg,hh]=penalty_objective_function(xparam1,func0,penalty,varargin{:});
hhg=hh;
H = inv(hh);
@@ -233,7 +233,7 @@ while norm(gg)>gtol && check==0 && jit<nit
disp_verbose(['Ftol ',num2str(ftol)],Verbose)
disp_verbose(['Htol ',num2str(max(htol0))],Verbose)
htol=htol_base;
- if norm(x(:,icount)-xparam1)>1.e-12 && analytic_derivation==0,
+ if norm(x(:,icount)-xparam1)>1.e-12 && analytic_derivation==0
try
if Save_files
save('m1.mat','x','fval0','nig','-append')
@@ -244,7 +244,7 @@ while norm(gg)>gtol && check==0 && jit<nit
end
end
[dum, gg, htol0, igg, hhg, h1, hess_info]=mr_hessian(xparam1,func0,penalty,flagit,htol,hess_info,varargin{:});
- if isempty(dum),
+ if isempty(dum)
outer_product_gradient=0;
end
if max(htol0)>htol
@@ -253,7 +253,7 @@ while norm(gg)>gtol && check==0 && jit<nit
disp_verbose('Tolerance has to be relaxed',Verbose)
skipline()
end
- if ~outer_product_gradient,
+ if ~outer_product_gradient
H = bfgsi1(H,gg-g(:,icount),xparam1-x(:,icount),Verbose,Save_files);
hh=inv(H);
hhg=hh;
@@ -270,7 +270,7 @@ while norm(gg)>gtol && check==0 && jit<nit
end
H = igg;
end
- elseif analytic_derivation,
+ elseif analytic_derivation
[fvalx,exit_flag,gg,hh]=penalty_objective_function(xparam1,func0,penalty,varargin{:});
hhg=hh;
H = inv(hh);
@@ -311,7 +311,7 @@ if norm(gg)<=gtol
disp_verbose(['Estimation ended:'],Verbose)
disp_verbose(['Gradient norm < ', num2str(gtol)],Verbose)
end
-if check==1,
+if check==1
disp_verbose(['Estimation successful.'],Verbose)
end
@@ -321,11 +321,11 @@ return
function x = check_bounds(x,bounds)
inx = find(x>=bounds(:,2));
-if ~isempty(inx),
+if ~isempty(inx)
x(inx) = bounds(inx,2)-eps;
end
inx = find(x<=bounds(:,1));
-if ~isempty(inx),
+if ~isempty(inx)
x(inx) = bounds(inx,1)+eps;
end
diff --git a/matlab/optimization/simplex_optimization_routine.m b/matlab/optimization/simplex_optimization_routine.m
index 58b3ff1b0..39785898a 100644
--- a/matlab/optimization/simplex_optimization_routine.m
+++ b/matlab/optimization/simplex_optimization_routine.m
@@ -396,7 +396,7 @@ while (func_count < max_func_calls) && (iter_count < max_iterations) && (simplex
disp(['Crit. x: ' num2str(critX)])
skipline()
end
- if verbose && max(abs(best_point-v(:,1)))>x_tolerance;
+ if verbose && max(abs(best_point-v(:,1)))>x_tolerance
if verbose<2
disp(['Simplex iteration number: ' int2str(simplex_iterations) '-' int2str(simplex_init) '-' int2str(simplex_algo_iterations)])
disp(['Objective function value: ' num2str(fv(1))])
diff --git a/matlab/optimization/simpsa.m b/matlab/optimization/simpsa.m
index 260607a24..b389b37bd 100644
--- a/matlab/optimization/simpsa.m
+++ b/matlab/optimization/simpsa.m
@@ -77,11 +77,11 @@ function [X,FVAL,EXITFLAG,OUTPUT] = simpsa(FUN,X0,LB,UB,OPTIONS,varargin)
% handle variable input arguments
-if nargin < 5,
+if nargin < 5
OPTIONS = [];
- if nargin < 4,
+ if nargin < 4
UB = 1e5;
- if nargin < 3,
+ if nargin < 3
LB = -1e5;
end
end
@@ -89,22 +89,22 @@ end
% check input arguments
-if ~ischar(FUN),
+if ~ischar(FUN)
error('''FUN'' incorrectly specified in ''SIMPSA''');
end
-if ~isfloat(X0),
+if ~isfloat(X0)
error('''X0'' incorrectly specified in ''SIMPSA''');
end
-if ~isfloat(LB),
+if ~isfloat(LB)
error('''LB'' incorrectly specified in ''SIMPSA''');
end
-if ~isfloat(UB),
+if ~isfloat(UB)
error('''UB'' incorrectly specified in ''SIMPSA''');
end
-if length(X0) ~= length(LB),
+if length(X0) ~= length(LB)
error('''LB'' and ''X0'' have incompatible dimensions in ''SIMPSA''');
end
-if length(X0) ~= length(UB),
+if length(X0) ~= length(UB)
error('''UB'' and ''X0'' have incompatible dimensions in ''SIMPSA''');
end
@@ -167,7 +167,7 @@ TEMP_LOOP_NUMBER = 1;
% loop as described by Cardoso et al., 1996 (recommended)
% therefore, the temperature is set to YBEST*1e5 in the first loop
-if isempty(OPTIONS.TEMP_START),
+if isempty(OPTIONS.TEMP_START)
TEMP = abs(YBEST)*1e5;
else
TEMP = OPTIONS.TEMP_START;
@@ -195,7 +195,7 @@ nITERATIONS = 0;
% temperature loop: run SIMPSA till stopping criterion is met
% -----------------------------------------------------------
-while 1,
+while 1
% detect if termination criterium was met
% ---------------------------------------
@@ -203,23 +203,23 @@ while 1,
% if a termination criterium was met, the value of EXITFLAG should have changed
% from its default value of -2 to -1, 0, 1 or 2
- if EXITFLAG ~= -2,
+ if EXITFLAG ~= -2
break
end
% set MAXITERTEMP: maximum number of iterations at current temperature
% --------------------------------------------------------------------
- if TEMP_LOOP_NUMBER == 1,
+ if TEMP_LOOP_NUMBER == 1
MAXITERTEMP = OPTIONS.MAX_ITER_TEMP_FIRST*NDIM;
% The initial temperature is estimated (is requested) as described in
% Cardoso et al. (1996). Therefore, we need to store the number of
% successful and unsuccessful moves, as well as the increase in cost
% for the unsuccessful moves.
- if isempty(OPTIONS.TEMP_START),
+ if isempty(OPTIONS.TEMP_START)
[SUCCESSFUL_MOVES,UNSUCCESSFUL_MOVES,UNSUCCESSFUL_COSTS] = deal(0);
end
- elseif TEMP < OPTIONS.TEMP_END,
+ elseif TEMP < OPTIONS.TEMP_END
TEMP = 0;
MAXITERTEMP = OPTIONS.MAX_ITER_TEMP_LAST*NDIM;
else
@@ -234,12 +234,12 @@ while 1,
Y(1) = CALCULATE_COST(FUN,P(1,:),LB,UB,varargin{:});
% if output function given then run output function to plot intermediate result
- if ~isempty(OPTIONS.OUTPUT_FCN),
+ if ~isempty(OPTIONS.OUTPUT_FCN)
feval(OPTIONS.OUTPUT_FCN,transpose(P(1,:)),Y(1));
end
% remaining vertices of simplex
- for k = 1:NDIM,
+ for k = 1:NDIM
% copy first vertex in new vertex
P(k+1,:) = P(1,:);
% alter new vertex
@@ -259,8 +259,8 @@ while 1,
% dimensions of vector Y: (NDIM+1) x 1
% give user feedback if requested
- if strcmp(OPTIONS.DISPLAY,'iter'),
- if nITERATIONS == 0,
+ if strcmp(OPTIONS.DISPLAY,'iter')
+ if nITERATIONS == 0
disp(' Nr Iter Nr Fun Eval Min function Best function TEMP Algorithm Step');
else
disp(sprintf('%5.0f %5.0f %12.6g %15.6g %12.6g %s',nITERATIONS,nFUN_EVALS,Y(1),YBEST,TEMP,'best point'));
@@ -280,7 +280,7 @@ while 1,
% start
- for ITERTEMP = 1:MAXITERTEMP,
+ for ITERTEMP = 1:MAXITERTEMP
% add one to number of iterations
nITERATIONS = nITERATIONS + 1;
@@ -315,12 +315,12 @@ while 1,
OUTPUT.COSTS(nITERATIONS,:) = Y;
OUTPUT.COST_BEST(nITERATIONS) = YBEST;
- if strcmp(OPTIONS.DISPLAY,'iter'),
+ if strcmp(OPTIONS.DISPLAY,'iter')
disp(sprintf('%5.0f %5.0f %12.6g %15.6g %12.6g %s',nITERATIONS,nFUN_EVALS,Y(1),YBEST,TEMP,ALGOSTEP));
end
% if output function given then run output function to plot intermediate result
- if ~isempty(OPTIONS.OUTPUT_FCN),
+ if ~isempty(OPTIONS.OUTPUT_FCN)
feval(OPTIONS.OUTPUT_FCN,transpose(P(1,:)),Y(1));
end
@@ -330,36 +330,36 @@ while 1,
%% 3. no convergence,but maximum number of iterations has been reached
%% 4. no convergence,but maximum time has been reached
- if (abs(max(Y)-min(Y)) < OPTIONS.TOLFUN) && (TEMP_LOOP_NUMBER ~= 1),
- if strcmp(OPTIONS.DISPLAY,'iter'),
+ if (abs(max(Y)-min(Y)) < OPTIONS.TOLFUN) && (TEMP_LOOP_NUMBER ~= 1)
+ if strcmp(OPTIONS.DISPLAY,'iter')
disp('Change in the objective function value less than the specified tolerance (TOLFUN).')
end
EXITFLAG = 1;
- break;
+ break
end
- if (max(max(abs(P(2:NDIM+1,:)-P(1:NDIM,:)))) < OPTIONS.TOLX) && (TEMP_LOOP_NUMBER ~= 1),
- if strcmp(OPTIONS.DISPLAY,'iter'),
+ if (max(max(abs(P(2:NDIM+1,:)-P(1:NDIM,:)))) < OPTIONS.TOLX) && (TEMP_LOOP_NUMBER ~= 1)
+ if strcmp(OPTIONS.DISPLAY,'iter')
disp('Change in X less than the specified tolerance (TOLX).')
end
EXITFLAG = 2;
- break;
+ break
end
- if (nITERATIONS >= OPTIONS.MAX_ITER_TOTAL*NDIM) || (nFUN_EVALS >= OPTIONS.MAX_FUN_EVALS*NDIM*(NDIM+1)),
- if strcmp(OPTIONS.DISPLAY,'iter'),
+ if (nITERATIONS >= OPTIONS.MAX_ITER_TOTAL*NDIM) || (nFUN_EVALS >= OPTIONS.MAX_FUN_EVALS*NDIM*(NDIM+1))
+ if strcmp(OPTIONS.DISPLAY,'iter')
disp('Maximum number of function evaluations or iterations reached.');
end
EXITFLAG = 0;
- break;
+ break
end
- if toc/60 > OPTIONS.MAX_TIME,
- if strcmp(OPTIONS.DISPLAY,'iter'),
+ if toc/60 > OPTIONS.MAX_TIME
+ if strcmp(OPTIONS.DISPLAY,'iter')
disp('Exceeded maximum time.');
end
EXITFLAG = -1;
- break;
+ break
end
% begin a new iteration
@@ -369,11 +369,11 @@ while 1,
[YFTRY,YTRY,PTRY] = AMOTRY(FUN,P,-1,LB,UB,varargin{:});
%% check the result
- if YFTRY <= YFLUCT(1),
+ if YFTRY <= YFLUCT(1)
%% gives a result better than the best point,so try an additional
%% extrapolation by a factor 2
[YFTRYEXP,YTRYEXP,PTRYEXP] = AMOTRY(FUN,P,-2,LB,UB,varargin{:});
- if YFTRYEXP < YFTRY,
+ if YFTRYEXP < YFTRY
P(end,:) = PTRYEXP;
Y(end) = YTRYEXP;
ALGOSTEP = 'reflection and expansion';
@@ -382,12 +382,12 @@ while 1,
Y(end) = YTRY;
ALGOSTEP = 'reflection';
end
- elseif YFTRY >= YFLUCT(NDIM),
+ elseif YFTRY >= YFLUCT(NDIM)
%% the reflected point is worse than the second-highest, so look
%% for an intermediate lower point, i.e., do a one-dimensional
%% contraction
[YFTRYCONTR,YTRYCONTR,PTRYCONTR] = AMOTRY(FUN,P,-0.5,LB,UB,varargin{:});
- if YFTRYCONTR < YFLUCT(end),
+ if YFTRYCONTR < YFLUCT(end)
P(end,:) = PTRYCONTR;
Y(end) = YTRYCONTR;
ALGOSTEP = 'one dimensional contraction';
@@ -396,7 +396,7 @@ while 1,
%% around the lowest (best) point
X = ones(NDIM,NDIM)*diag(P(1,:));
P(2:end,:) = 0.5*(P(2:end,:)+X);
- for k=2:NDIM,
+ for k=2:NDIM
Y(k) = CALCULATE_COST(FUN,P(k,:),LB,UB,varargin{:});
end
ALGOSTEP = 'multiple contraction';
@@ -412,10 +412,10 @@ while 1,
% the number of successfull and unsuccesfull moves, and the average
% increase in cost associated with the unsuccessful moves
- if TEMP_LOOP_NUMBER == 1 && isempty(OPTIONS.TEMP_START),
- if Y(1) > Y(end),
+ if TEMP_LOOP_NUMBER == 1 && isempty(OPTIONS.TEMP_START)
+ if Y(1) > Y(end)
SUCCESSFUL_MOVES = SUCCESSFUL_MOVES+1;
- elseif Y(1) <= Y(end),
+ elseif Y(1) <= Y(end)
UNSUCCESSFUL_MOVES = UNSUCCESSFUL_MOVES+1;
UNSUCCESSFUL_COSTS = UNSUCCESSFUL_COSTS+(Y(end)-Y(1));
end
@@ -424,8 +424,8 @@ while 1,
end
% stop if previous for loop was broken due to some stop criterion
- if ITERTEMP < MAXITERTEMP,
- break;
+ if ITERTEMP < MAXITERTEMP
+ break
end
% store cost function values in COSTS vector
@@ -435,9 +435,9 @@ while 1,
% using cooling schedule as proposed by Cardoso et al. (1996)
% -----------------------------------------------------------
- if TEMP_LOOP_NUMBER == 1 && isempty(OPTIONS.TEMP_START),
+ if TEMP_LOOP_NUMBER == 1 && isempty(OPTIONS.TEMP_START)
TEMP = -(UNSUCCESSFUL_COSTS/(SUCCESSFUL_MOVES+UNSUCCESSFUL_MOVES))/log(((SUCCESSFUL_MOVES+UNSUCCESSFUL_MOVES)*OPTIONS.INITIAL_ACCEPTANCE_RATIO-SUCCESSFUL_MOVES)/UNSUCCESSFUL_MOVES);
- elseif TEMP_LOOP_NUMBER ~= 0,
+ elseif TEMP_LOOP_NUMBER ~= 0
STDEV_Y = std(COSTS);
COOLING_FACTOR = 1/(1+TEMP*log(1+OPTIONS.COOL_RATE)/(3*STDEV_Y));
TEMP = TEMP*min(OPTIONS.MIN_COOLING_FACTOR,COOLING_FACTOR);
@@ -502,14 +502,14 @@ function [YTRY] = CALCULATE_COST(FUN,PTRY,LB,UB,varargin)
global YBEST PBEST NDIM nFUN_EVALS
-for i = 1:NDIM,
+for i = 1:NDIM
% check lower bounds
- if PTRY(i) < LB(i),
+ if PTRY(i) < LB(i)
YTRY = 1e12+(LB(i)-PTRY(i))*1e6;
return
end
% check upper bounds
- if PTRY(i) > UB(i),
+ if PTRY(i) > UB(i)
YTRY = 1e12+(PTRY(i)-UB(i))*1e6;
return
end
@@ -522,7 +522,7 @@ YTRY = feval(FUN,PTRY(:),varargin{:});
nFUN_EVALS = nFUN_EVALS + 1;
% save the best point ever
-if YTRY < YBEST,
+if YTRY < YBEST
YBEST = YTRY;
PBEST = PTRY;
end
diff --git a/matlab/optimization/simpsaget.m b/matlab/optimization/simpsaget.m
index e482a3e00..e1c775495 100644
--- a/matlab/optimization/simpsaget.m
+++ b/matlab/optimization/simpsaget.m
@@ -56,7 +56,7 @@ end
if isempty(options)
o = default;
- return;
+ return
end
Names = [
diff --git a/matlab/optimization/simpsaset.m b/matlab/optimization/simpsaset.m
index ca687891a..dc0aade4f 100644
--- a/matlab/optimization/simpsaset.m
+++ b/matlab/optimization/simpsaset.m
@@ -64,7 +64,7 @@ if (nargin == 0) && (nargout == 0)
fprintf(' DISPLAY: [ ''iter'' or ''none'' {''iter''} ]\n');
fprintf(' OUTPUT_FCN: [ function_handle ]\n');
fprintf('\n');
-return;
+return
end
Names = [
@@ -97,7 +97,7 @@ i = 1;
while i <= nargin
arg = varargin{i};
if ischar(arg) % arg is an option name
- break;
+ break
end
if ~isempty(arg) % [] is a valid options argument
if ~isa(arg,'struct')
diff --git a/matlab/optimization/simulated_annealing.m b/matlab/optimization/simulated_annealing.m
index 5b505b71d..35f0240e0 100644
--- a/matlab/optimization/simulated_annealing.m
+++ b/matlab/optimization/simulated_annealing.m
@@ -194,17 +194,17 @@ xopt=x;
nacp=zeros(n,1);
fstar=1e20*ones(optim.neps,1);
%* If the initial temperature is not positive, notify the user and abort. *
-if(t<=0.0);
+if(t<=0.0)
fprintf('\nThe initial temperature is not positive. Reset the variable t\n');
exitflag=3;
- return;
-end;
+ return
+end
%* If the initial value is out of bounds, notify the user and abort. *
-if(sum(x>ub)+sum(x<lb)>0);
+if(sum(x>ub)+sum(x<lb)>0)
fprintf('\nInitial condition out of bounds\n');
exitflag=2;
- return;
-end;
+ return
+end
%* Evaluate the function with input x and return value as f. *
f=feval(fcn,x,varargin{:});
%*
@@ -212,98 +212,98 @@ f=feval(fcn,x,varargin{:});
% Note that all intermediate and final output switches the sign back
% to eliminate any possible confusion for the user.
%*
-if(optim.maximizer_indicator==0);
+if(optim.maximizer_indicator==0)
f=-f;
-end;
+end
n_total_draws=n_total_draws+1;
fopt=f;
fstar(1)=f;
-if(optim.verbosity >1);
+if(optim.verbosity >1)
disp ' ';
disp(['initial x ' num2str(x(:)')]);
- if(optim.maximizer_indicator);
+ if(optim.maximizer_indicator)
disp(['initial f ' num2str(f)]);
else
disp(['initial f ' num2str(-f)]);
- end;
-end;
+ end
+end
% Start the main loop. Note that it terminates if (i) the algorithm
% succesfully optimizes the function or (ii) there are too many
% function evaluations (more than optim.MaxIter).
-while (1>0);
+while (1>0)
nup=0;
nrej=0;
nnew=0;
ndown=0;
lnobds=0;
m=1;
- while m<=optim.nt;
+ while m<=optim.nt
j=1;
- while j<=optim.ns;
+ while j<=optim.ns
h=1;
- while h<=n;
+ while h<=n
%* Generate xp, the trial value of x. Note use of vm to choose xp. *
i=1;
- while i<=n;
- if(i==h);
+ while i<=n
+ if(i==h)
xp(i)=x(i)+(rand(1,1)*2.0-1.0)*vm(i);
else
xp(i)=x(i);
- end;
+ end
%* If xp is out of bounds, select a point in bounds for the trial. *
- if((xp(i)<lb(i) || xp(i)>ub(i)));
+ if((xp(i)<lb(i) || xp(i)>ub(i)))
xp(i)=lb(i)+(ub(i)-lb(i))*rand(1,1);
lnobds=lnobds+1;
n_out_of_bounds_draws=n_out_of_bounds_draws+1;
- if(optim.verbosity >=3);
+ if(optim.verbosity >=3)
if exist('fp','var')
print_current_invalid_try(optim.maximizer_indicator,xp,x,fp,f);
end
- end;
- end;
+ end
+ end
i=i+1;
- end;
+ end
%* Evaluate the function with the trial point xp and return as fp. *
% fp=feval(fcn,xp,listarg);
fp=feval(fcn,xp,varargin{:});
- if(optim.maximizer_indicator==0);
+ if(optim.maximizer_indicator==0)
fp=-fp;
- end;
+ end
n_total_draws=n_total_draws+1;
- if(optim.verbosity >=3);
+ if(optim.verbosity >=3)
print_current_valid_try(optim.maximizer_indicator,xp,x,fp,f);
- end;
+ end
%* If too many function evaluations occur, terminate the algorithm. *
- if(n_total_draws>=optim.MaxIter);
+ if(n_total_draws>=optim.MaxIter)
fprintf('Too many function evaluations; consider\n');
fprintf('increasing optim.MaxIter or optim.TolFun or decreasing\n');
fprintf('optim.nt or optim.rt. These results are likely to be poor\n');
- if(optim.maximizer_indicator==0);
+ if(optim.maximizer_indicator==0)
fopt=-fopt;
- end;
+ end
exitflag=1;
- return;
- end;
+ return
+ end
%* Accept the new point if the function value increases. *
- if(fp>=f);
- if(optim.verbosity >=3);
+ if(fp>=f)
+ if(optim.verbosity >=3)
fprintf('point accepted\n');
- end;
+ end
x=xp;
f=fp;
n_accepted_draws=n_accepted_draws+1;
nacp(h)=nacp(h)+1;
nup=nup+1;
%* If greater than any other point, record as new optimum. *
- if(fp>fopt);
- if(optim.verbosity >=3);
+ if(fp>fopt)
+ if(optim.verbosity >=3)
fprintf('new optimum\n');
- end;
+ end
xopt=xp;
fopt=fp;
nnew=nnew+1;
- end;
+ end
%*
% If the point is lower, use the Metropolis criteria to decide on
% acceptance or rejection.
@@ -311,14 +311,14 @@ while (1>0);
else
p=exp((fp-f)/t);
pp=rand(1,1);
- if(pp<p);
- if(optim.verbosity >=3);
- if(optim.maximizer_indicator);
+ if(pp<p)
+ if(optim.verbosity >=3)
+ if(optim.maximizer_indicator)
fprintf('though lower, point accepted\n');
else
fprintf('though higher, point accepted\n');
- end;
- end;
+ end
+ end
x=xp;
f=fp;
n_accepted_draws=n_accepted_draws+1;
@@ -326,87 +326,87 @@ while (1>0);
ndown=ndown+1;
else
nrej=nrej+1;
- if(optim.verbosity >=3);
- if(optim.maximizer_indicator);
+ if(optim.verbosity >=3)
+ if(optim.maximizer_indicator)
fprintf('lower point rejected\n');
else
fprintf('higher point rejected\n');
- end;
- end;
- end;
- end;
+ end
+ end
+ end
+ end
h=h+1;
- end;
+ end
j=j+1;
- end;
+ end
%* Adjust vm so that approximately half of all evaluations are accepted. *
i=1;
- while i<=n;
+ while i<=n
ratio=nacp(i)/optim.ns;
- if(ratio>.6);
+ if(ratio>.6)
vm(i)=vm(i)*(1.+c(i)*(ratio-.6)/.4);
- elseif(ratio<.4);
+ elseif(ratio<.4)
vm(i)=vm(i)/(1.+c(i)*((.4-ratio)/.4));
- end;
- if(vm(i)>(ub(i)-lb(i)));
+ end
+ if(vm(i)>(ub(i)-lb(i)))
vm(i)=ub(i)-lb(i);
- end;
+ end
i=i+1;
- end;
- if(optim.verbosity >=2);
+ end
+ if(optim.verbosity >=2)
fprintf('intermediate results after step length adjustment\n');
fprintf('new step length(vm) %4.3f', vm(:)');
fprintf('current optimal x %4.3f', xopt(:)');
fprintf('current x %4.3f', x(:)');
- end;
+ end
nacp=zeros(n,1);
m=m+1;
- end;
- if(optim.verbosity >=1);
+ end
+ if(optim.verbosity >=1)
print_intermediate_statistics(optim.maximizer_indicator,t,xopt,vm,fopt,nup,ndown,nrej,lnobds,nnew);
- end;
+ end
%* Check termination criteria. *
quit=0;
fstar(1)=f;
- if((fopt-fstar(1))<=optim.TolFun);
+ if((fopt-fstar(1))<=optim.TolFun)
quit=1;
- end;
- if(sum(abs(f-fstar)>optim.TolFun)>0);
+ end
+ if(sum(abs(f-fstar)>optim.TolFun)>0)
quit=0;
- end;
+ end
%* Terminate SA if appropriate. *
- if(quit);
+ if(quit)
exitflag=0;
- if(optim.maximizer_indicator==0);
+ if(optim.maximizer_indicator==0)
fopt=-fopt;
- end;
- if(optim.verbosity >=1);
+ end
+ if(optim.verbosity >=1)
fprintf('SA achieved termination criteria.exitflag=0\n');
- end;
- return;
- end;
+ end
+ return
+ end
%* If termination criteria are not met, prepare for another loop. *
t=optim.rt*t;
i=optim.neps;
- while i>=2;
+ while i>=2
fstar(i)=fstar(i-1);
i=i-1;
- end;
+ end
f=fopt;
x=xopt;
%* Loop again. *
-end;
+end
end
function print_current_invalid_try(max,xp,x,fp,f)
fprintf('\n');
disp(['Current x ' num2str(x(:)')]);
-if(max);
+if(max)
disp(['Current f ' num2str(f)]);
else
disp(['Current f ' num2str(-f)]);
-end;
+end
disp(['Trial x ' num2str(xp(:)')]);
disp 'Point rejected since out of bounds';
end
@@ -414,7 +414,7 @@ end
function print_current_valid_try(max,xp,x,fp,f)
disp(['Current x ' num2str(x(:)')]);
-if(max);
+if(max)
disp(['Current f ' num2str(f)]);
disp(['Trial x ' num2str(xp(:)')]);
disp(['Resulting f ' num2str(fp)]);
@@ -422,7 +422,7 @@ else
disp(['Current f ' num2str(-f)]);
disp(['Trial x ' num2str(xp(:)')]);
disp(['Resulting f ' num2str(-fp)]);
-end;
+end
end
diff --git a/matlab/optimization/solvopt.m b/matlab/optimization/solvopt.m
index 6d5693e86..9976ad850 100644
--- a/matlab/optimization/solvopt.m
+++ b/matlab/optimization/solvopt.m
@@ -162,7 +162,7 @@ if isempty(func)
constr=0;
else
constr=1; % Constrained problem
- if isempty(gradc),
+ if isempty(gradc)
appconstr=1;
else
appconstr=0; % Exact gradients of constraints are supplied
@@ -201,7 +201,7 @@ end
epsnorm=1.e-15;
epsnorm2=1.e-30; % epsilon & epsilon^2
-if constr, h1=-1; % NLP: restricted to minimization
+if constr, h1=-1 % NLP: restricted to minimization
cnteps=optim.TolXConstraint; % Max. admissible residual
else
h1=sign(optim.minimizer_indicator); % Minimize resp. maximize a function
@@ -220,7 +220,7 @@ knorms=0; gnorms=zeros(1,10); % Gradient norms stored
%---}
%Display control ---{
-if optim.verbosity<=0, dispdata=0;
+if optim.verbosity<=0, dispdata=0
if optim.verbosity==-1
dispwarn=0;
else
@@ -276,30 +276,79 @@ else
f=feval(fun,x,varargin{:});
end
n_f_evals=n_f_evals+1;
-if isempty(f), if dispwarn,disp(errmes);disp(error30);end
- exitflag=-3; if trx, x=x';end, return
-elseif isnan(f), if dispwarn,disp(errmes);disp(error31);disp(error6);end
- exitflag=-3; if trx, x=x';end, return
-elseif abs(f)==Inf, if dispwarn,disp(errmes);disp(error32);disp(error6);end
- exitflag=-3; if trx, x=x';end, return
+if isempty(f)
+ if dispwarn
+ disp(errmes)
+ disp(error30)
+ end
+ exitflag=-3;
+ if trx
+ x=x';
+ end
+ return
+elseif isnan(f)
+ if dispwarn
+ disp(errmes)
+ disp(error31)
+ disp(error6)
+ end
+ exitflag=-3;
+ if trx
+ x=x';
+ end
+ return
+elseif abs(f)==Inf
+ if dispwarn
+ disp(errmes)
+ disp(error32)
+ disp(error6)
+ end
+ exitflag=-3;
+ if trx
+ x=x';
+ end
+ return
end
xrec=x; frec=f; % record point and function value
% Constrained problem
-if constr, fp=f; kless=0;
- if trx,
+if constr, fp=f; kless=0
+ if trx
fc=feval(func,x');
else
fc=feval(func,x);
end
- if isempty(fc),
- if dispwarn,disp(errmes);disp(error50);end
- exitflag=-5; if trx, x=x';end, return
- elseif isnan(fc),
- if dispwarn,disp(errmes);disp(error51);disp(error6);end
- exitflag=-5; if trx, x=x';end, return
- elseif abs(fc)==Inf,
- if dispwarn,disp(errmes);disp(error52);disp(error6);end
- exitflag=-5; if trx, x=x';end, return
+ if isempty(fc)
+ if dispwarn
+ disp(errmes)
+ disp(error50)
+ end
+ exitflag=-5;
+ if trx
+ x=x';
+ end
+ return
+ elseif isnan(fc)
+ if dispwarn
+ disp(errmes)
+ disp(error51)
+ disp(error6)
+ end
+ exitflag=-5;
+ if trx
+ x=x';
+ end
+ return
+ elseif abs(fc)==Inf
+ if dispwarn
+ disp(errmes)
+ disp(error52)
+ disp(error6)
+ end
+ exitflag=-5;
+ if trx
+ x=x';
+ end
+ return
end
n_constraint_evals=n_constraint_evals+1;
PenCoef=1; % first rough approximation
@@ -336,19 +385,55 @@ else
end
n_grad_evals=n_grad_evals+1;
end
-if size(g,2)==1, g=g'; end, ng=norm(g);
-if size(g,2)~=n, if dispwarn,disp(errmes);disp(error40);end
- exitflag=-4; if trx, x=x';end, return
-elseif isnan(ng), if dispwarn,disp(errmes);disp(error41);disp(error6);end
- exitflag=-4; if trx, x=x';end, return
-elseif ng==Inf, if dispwarn,disp(errmes);disp(error42);disp(error6);end
- exitflag=-4; if trx, x=x';end, return
-elseif ng<ZeroGrad, if dispwarn,disp(errmes);disp(error43);disp(error6);end
- exitflag=-4; if trx, x=x';end, return
+if size(g,2)==1, g=g'; end
+ng=norm(g);
+if size(g,2)~=n
+ if dispwarn
+ disp(errmes)
+ disp(error40)
+ end
+ exitflag=-4;
+ if trx
+ x=x';
+ end
+ return
+elseif isnan(ng)
+ if dispwarn
+ disp(errmes)
+ disp(error41)
+ disp(error6)
+ end
+ exitflag=-4;
+ if trx
+ x=x';
+ end
+ return
+elseif ng==Inf
+ if dispwarn
+ disp(errmes)
+ disp(error42)
+ disp(error6)
+ end
+ exitflag=-4;
+ if trx
+ x=x';
+ end
+ return
+elseif ng<ZeroGrad
+ if dispwarn
+ disp(errmes)
+ disp(error43)
+ disp(error6)
+ end
+ exitflag=-4;
+ if trx
+ x=x';
+ end
+ return
end
if constr
if ~FP
- if appconstr,
+ if appconstr
deltax=sign(x); idx=find(deltax==0);
deltax(idx)=ones(size(idx));
deltax=ddx*deltax;
@@ -370,42 +455,42 @@ if constr
gc=gc';
end
ngc=norm(gc);
- if size(gc,2)~=n,
+ if size(gc,2)~=n
if dispwarn
- disp(errmes);
- disp(error60);
+ disp(errmes)
+ disp(error60)
end
exitflag=-6;
if trx
x=x';
end
return
- elseif isnan(ngc),
+ elseif isnan(ngc)
if dispwarn
- disp(errmes);
- disp(error61);
- disp(error6);
+ disp(errmes)
+ disp(error61)
+ disp(error6)
end
- exitflag=-6;
+ exitflag=-6;
if trx
x=x';
end
return
- elseif ngc==Inf,
+ elseif ngc==Inf
if dispwarn
- disp(errmes);
- disp(error62);
- disp(error6);
+ disp(errmes)
+ disp(error62)
+ disp(error6)
end
exitflag=-6;
if trx
x=x';
end
return
- elseif ngc<ZeroGrad,
+ elseif ngc<ZeroGrad
if dispwarn
- disp(errmes);
- disp(error63);
+ disp(errmes)
+ disp(error63)
end
exitflag=-6;
if trx
@@ -414,19 +499,20 @@ if constr
return
end
g=g+PenCoef*gc; ng=norm(g);
- end, end
+ end
+end
grec=g; nng=ng;
% ----}
% INITIAL STEPSIZE
h=h1*sqrt(optim.TolX)*max(abs(x)); % smallest possible stepsize
-if abs(optim.minimizer_indicator)~=1,
+if abs(optim.minimizer_indicator)~=1
h=h1*max(abs([optim.minimizer_indicator,h])); % user-supplied stepsize
else
h=h1*max(1/log(ng+1.1),abs(h)); % calculated stepsize
end
% RESETTING LOOP ----{
-while 1,
+while 1
kcheck=0; % Set checkpoint counter.
kg=0; % stepsizes stored
kj=0; % ravine jump counter
@@ -436,7 +522,7 @@ while 1,
% MAIN ITERATIONS ----{
- while 1,
+ while 1
k=k+1;kcheck=kcheck+1;
laststep=dx;
@@ -447,11 +533,21 @@ while 1,
gt=g*B; w=wdef;
% JUMPING OVER A RAVINE ----{
if (gt/norm(gt))*(g1'/norm(g1))<low_bound
- if kj==2, xx=x; end, if kj==0, kd=4; end,
+ if kj==2
+ xx=x;
+ end
+ if kj==0
+ kd=4
+ end
kj=kj+1; w=-.9; h=h*2; % use large coef. of space dilation
- if kj>2*kd, kd=kd+1; warnno=1;
- if any(abs(x-xx)<epsnorm*abs(x)), % flat bottom is detected
- if dispwarn,disp(wrnmes);disp(warn08); end
+ if kj>2*kd
+ kd=kd+1;
+ warnno=1;
+ if any(abs(x-xx)<epsnorm*abs(x)) % flat bottom is detected
+ if dispwarn
+ disp(wrnmes)
+ disp(warn08)
+ end
end
end
else
@@ -474,9 +570,12 @@ while 1,
% RESETTING ----{
if kcheck>1
idx=find(abs(g)>ZeroGrad); numelem=size(idx,2);
- if numelem>0, grbnd=epsnorm*numelem^2;
- if all(abs(g1(idx))<=abs(g(idx))*grbnd) | nrmz==0
- if dispwarn, disp(wrnmes); disp(warn20); end
+ if numelem>0, grbnd=epsnorm*numelem^2
+ if all(abs(g1(idx))<=abs(g(idx))*grbnd) || nrmz==0
+ if dispwarn
+ disp(wrnmes)
+ disp(warn20)
+ end
if abs(fst-f)<abs(f)*.01
ajp=ajp-10*n;
else
@@ -493,9 +592,12 @@ while 1,
xopt=x;fopt=f; k1=0;k2=0;ksm=0;kc=0;knan=0; hp=h;
if constr, Reset=0; end
% 1-D SEARCH ----{
- while 1,
+ while 1
x1=x;f1=f;
- if constr, FP1=FP; fp1=fp; end
+ if constr
+ FP1=FP;
+ fp1=fp;
+ end
x=x+hp*g0;
% FUNCTION VALUE
if trx
@@ -506,8 +608,8 @@ while 1,
n_f_evals=n_f_evals+1;
if h1*f==Inf
if dispwarn
- disp(errmes);
- disp(error5);
+ disp(errmes)
+ disp(error5)
end
exitflag=-7;
if trx
@@ -522,12 +624,28 @@ while 1,
fc=feval(func,x);
end
n_constraint_evals=n_constraint_evals+1;
- if isnan(fc),
- if dispwarn,disp(errmes);disp(error51);disp(error6);end
- exitflag=-5; if trx, x=x';end, return
- elseif abs(fc)==Inf,
- if dispwarn,disp(errmes);disp(error52);disp(error6);end
- exitflag=-5; if trx, x=x';end, return
+ if isnan(fc)
+ if dispwarn
+ disp(errmes)
+ disp(error51)
+ disp(error6)
+ end
+ exitflag=-5;
+ if trx
+ x=x';
+ end
+ return
+ elseif abs(fc)==Inf
+ if dispwarn
+ disp(errmes)
+ disp(error52)
+ disp(error6)
+ end
+ exitflag=-5;
+ if trx
+ x=x';
+ end
+ return
end
if fc<=cnteps
FP=1;
@@ -538,7 +656,7 @@ while 1,
if fp_rate<-epsnorm
if ~FP1
PenCoefNew=-15*fp_rate/norm(x-x1);
- if PenCoefNew>1.2*PenCoef,
+ if PenCoefNew>1.2*PenCoef
PenCoef=PenCoefNew; Reset=1; kless=0; f=f+PenCoef*fc; break
end
end
@@ -547,22 +665,22 @@ while 1,
f=f+PenCoef*fc;
end
if abs(f)==Inf || isnan(f)
- if dispwarn, disp(wrnmes);
+ if dispwarn, disp(wrnmes)
if isnan(f)
- disp(error31);
+ disp(error31)
else
- disp(error32);
+ disp(error32)
end
end
if ksm || kc>=mxtc
- exitflag=-3;
+ exitflag=-3;
if trx
x=x';
end
return
else
k2=k2+1;
- k1=0;
+ k1=0;
hp=hp/dq;
x=x1;
f=f1;
@@ -573,13 +691,18 @@ while 1,
end
end
% STEP SIZE IS ZERO TO THE EXTENT OF EPSNORM
- elseif all(abs(x-x1)<abs(x)*epsnorm),
+ elseif all(abs(x-x1)<abs(x)*epsnorm)
stepvanish=stepvanish+1;
- if stepvanish>=5,
+ if stepvanish>=5
exitflag=-14;
- if dispwarn, disp(termwarn1);
- disp(endwarn(4,:)); end
- if trx,x=x';end, return
+ if dispwarn
+ disp(termwarn1)
+ disp(endwarn(4,:))
+ end
+ if trx
+ x=x';
+ end
+ return
else
x=x1;
f=f1;
@@ -592,24 +715,44 @@ while 1,
end
% USE SMALLER STEP
elseif h1*f<h1*gamma^sign(f1)*f1
- if ksm,break,end, k2=k2+1;k1=0; hp=hp/dq; x=x1;f=f1;
- if constr, FP=FP1; fp=fp1; end
+ if ksm
+ break
+ end
+ k2=k2+1;k1=0; hp=hp/dq; x=x1;f=f1;
+ if constr
+ FP=FP1;
+ fp=fp1;
+ end
if kc>=mxtc, break, end
% 1-D OPTIMIZER IS LEFT BEHIND
- else if h1*f<=h1*f1, break, end
+ else
+ if h1*f<=h1*f1
+ break
+ end
% USE LARGER STEP
- k1=k1+1; if k2>0, kc=kc+1; end, k2=0;
- if k1>=20, hp=du20*hp;
- elseif k1>=10, hp=du10*hp;
- elseif k1>=3, hp=du03*hp;
+ k1=k1+1;
+ if k2>0
+ kc=kc+1;
+ end
+ k2=0;
+ if k1>=20
+ hp=du20*hp;
+ elseif k1>=10
+ hp=du10*hp;
+ elseif k1>=3
+ hp=du03*hp;
end
end
end
% ----} End of 1-D search
% ADJUST THE TRIAL STEP SIZE ----{
dx=norm(xopt-x);
- if kg<kstore, kg=kg+1; end
- if kg>=2, nsteps(2:kg)=nsteps(1:kg-1); end
+ if kg<kstore
+ kg=kg+1;
+ end
+ if kg>=2
+ nsteps(2:kg)=nsteps(1:kg-1);
+ end
nsteps(1)=dx/(abs(h)*norm(g0));
kk=sum(nsteps(1:kg).*[kg:-1:1])/sum([kg:-1:1]);
if kk>des
@@ -625,7 +768,7 @@ while 1,
stepvanish=stepvanish+ksm;
% ----}
% COMPUTE THE GRADIENT ----{
- if app,
+ if app
deltax=sign(g0); idx=find(deltax==0);
deltax(idx)=ones(size(idx)); deltax=h1*ddx*deltax;
if constr
@@ -650,15 +793,35 @@ while 1,
end
n_grad_evals=n_grad_evals+1;
end
- if size(g,2)==1, g=g'; end, ng=norm(g);
- if isnan(ng),
- if dispwarn, disp(errmes); disp(error41); end
- exitflag=-4; if trx, x=x'; end, return
- elseif ng==Inf,
- if dispwarn,disp(errmes);disp(error42);end
- exitflag=-4; if trx, x=x';end, return
- elseif ng<ZeroGrad,
- if dispwarn,disp(wrnmes);disp(warn1);end
+ if size(g,2)==1
+ g=g'
+ end
+ ng=norm(g);
+ if isnan(ng)
+ if dispwarn
+ disp(errmes)
+ disp(error41)
+ end
+ exitflag=-4;
+ if trx
+ x=x';
+ end
+ return
+ elseif ng==Inf
+ if dispwarn
+ disp(errmes)
+ disp(error42)
+ end
+ exitflag=-4;
+ if trx
+ x=x';
+ end
+ return
+ elseif ng<ZeroGrad
+ if dispwarn
+ disp(wrnmes)
+ disp(warn1)
+ end
ng=ZeroGrad;
end
% Constraints:
@@ -666,11 +829,15 @@ while 1,
if ~FP
if ng<.01*PenCoef
kless=kless+1;
- if kless>=20, PenCoef=PenCoef/10; Reset=1; kless=0; end
+ if kless>=20
+ PenCoef=PenCoef/10;
+ Reset=1;
+ kless=0;
+ end
else
kless=0;
end
- if appconstr,
+ if appconstr
deltax=sign(x); idx=find(deltax==0);
deltax(idx)=ones(size(idx)); deltax=ddx*deltax;
if trx
@@ -687,27 +854,64 @@ while 1,
end
n_constraint_gradient_evals=n_constraint_gradient_evals+1;
end
- if size(gc,2)==1, gc=gc'; end, ngc=norm(gc);
- if isnan(ngc),
- if dispwarn,disp(errmes);disp(error61);end
- exitflag=-6; if trx, x=x';end, return
- elseif ngc==Inf,
- if dispwarn,disp(errmes);disp(error62);end
- exitflag=-6; if trx, x=x';end, return
- elseif ngc<ZeroGrad && ~appconstr,
- if dispwarn,disp(errmes);disp(error63);end
- exitflag=-6; if trx, x=x';end, return
+ if size(gc,2)==1
+ gc=gc';
+ end
+ ngc=norm(gc);
+ if isnan(ngc)
+ if dispwarn
+ disp(errmes)
+ disp(error61)
+ end
+ exitflag=-6;
+ if trx
+ x=x';
+ end
+ return
+ elseif ngc==Inf
+ if dispwarn
+ disp(errmes)
+ disp(error62)
+ end
+ exitflag=-6;
+ if trx
+ x=x';
+ end
+ return
+ elseif ngc<ZeroGrad && ~appconstr
+ if dispwarn
+ disp(errmes)
+ disp(error63)
+ end
+ exitflag=-6;
+ if trx
+ x=x';
+ end
+ return
end
g=g+PenCoef*gc; ng=norm(g);
- if Reset, if dispwarn, disp(wrnmes); disp(warn21); end
+ if Reset
+ if dispwarn
+ disp(wrnmes)
+ disp(warn21)
+ end
h=h1*dx/3; k=k-1; nng=ng; break
end
- end, end
- if h1*f>h1*frec, frec=f; xrec=x; grec=g; end
+ end
+ end
+ if h1*f>h1*frec
+ frec=f;
+ xrec=x;
+ grec=g;
+ end
% ----}
- if ng>ZeroGrad,
- if knorms<10, knorms=knorms+1; end
- if knorms>=2, gnorms(2:knorms)=gnorms(1:knorms-1); end
+ if ng>ZeroGrad
+ if knorms<10
+ knorms=knorms+1;
+ end
+ if knorms>=2
+ gnorms(2:knorms)=gnorms(1:knorms-1);
+ end
gnorms(1)=ng;
nng=(prod(gnorms(1:knorms)))^(1/knorms);
end
@@ -721,10 +925,20 @@ while 1,
%----}
% CHECK THE STOPPING CRITERIA ----{
termflag=1;
- if constr, if ~FP, termflag=0; end, end
- if kcheck<=5, termflag=0; end
- if knan, termflag=0; end
- if kc>=mxtc, termflag=0; end
+ if constr
+ if ~FP
+ termflag=0;
+ end
+ end
+ if kcheck<=5
+ termflag=0;
+ end
+ if knan
+ termflag=0
+ end
+ if kc>=mxtc
+ termflag=0;
+ end
% ARGUMENT
if termflag
idx=find(abs(x)>=lowxbound);
@@ -737,8 +951,8 @@ while 1,
~constr
if any(abs(xrec(idx)-x(idx))> detxr * abs(x(idx)))
if dispwarn
- disp(wrnmes);
- disp(warn09);
+ disp(wrnmes)
+ disp(warn09)
end
x=xrec;
f=frec;
@@ -759,13 +973,21 @@ while 1,
(abs(f-fopt)<=optim.TolFun && termx>=limxterm )
if stopf
if dx<=laststep
- if warnno==1 && ng<sqrt(optim.TolFun), warnno=0; end
- if ~app, if any(abs(g)<=epsnorm2), warnno=3; end, end
+ if warnno==1 && ng<sqrt(optim.TolFun)
+ warnno=0;
+ end
+ if ~app
+ if any(abs(g)<=epsnorm2)
+ warnno=3;
+ end
+ end
if warnno~=0
exitflag=-warnno-10;
- if dispwarn, disp(termwarn1);
- disp(endwarn(warnno,:));
- if app, disp(appwarn); end
+ if dispwarn, disp(termwarn1)
+ disp(endwarn(warnno,:))
+ if app
+ disp(appwarn);
+ end
end
else
exitflag=k;
@@ -783,11 +1005,18 @@ while 1,
end
elseif dx<1.e-12*max(norm(x),1) && termx>=limxterm
exitflag=-14;
- if dispwarn, disp(termwarn1); disp(endwarn(4,:));
- if app, disp(appwarn); end
+ if dispwarn
+ disp(termwarn1)
+ disp(endwarn(4,:))
+ if app
+ disp(appwarn)
+ end
end
x=xrec; f=frec;
- if trx,x=x';end, return
+ if trx
+ x=x';
+ end
+ return
else
stopf=0;
end
@@ -798,15 +1027,21 @@ while 1,
exitflag=-9;
if trx
x=x';
- end,
- if dispwarn, disp(wrnmes); disp(warn4); end
+ end
+ if dispwarn
+ disp(wrnmes)
+ disp(warn4)
+ end
return
end
% ----}
% ZERO GRADIENT ----{
if constr
- if ng<=ZeroGrad,
- if dispwarn, disp(termwarn1); disp(warn1); end
+ if ng<=ZeroGrad
+ if dispwarn
+ disp(termwarn1)
+ disp(warn1)
+ end
exitflag=-8;
if trx
x=x';
@@ -814,8 +1049,12 @@ while 1,
return
end
else
- if ng<=ZeroGrad, nzero=nzero+1;
- if dispwarn, disp(wrnmes); disp(warn1); end
+ if ng<=ZeroGrad
+ nzero=nzero+1;
+ if dispwarn
+ disp(wrnmes)
+ disp(warn1)
+ end
if nzero>=3
exitflag=-8;
if trx
@@ -824,7 +1063,7 @@ while 1,
return
end
g0=-h*g0/2;
- for i=1:10,
+ for i=1:10
x=x+g0;
if trx
f=feval(fun,x',varargin{:});
@@ -834,18 +1073,18 @@ while 1,
n_f_evals=n_f_evals+1;
if abs(f)==Inf
if dispwarn
- disp(errmes);
- disp(error32);
+ disp(errmes)
+ disp(error32)
end
exitflag=-3;
if trx
x=x';
end
return
- elseif isnan(f),
+ elseif isnan(f)
if dispwarn
- disp(errmes);
- disp(error32);
+ disp(errmes)
+ disp(error32)
end
exitflag=-3;
if trx
@@ -853,7 +1092,7 @@ while 1,
end
return
end
- if app,
+ if app
deltax=sign(g0);
idx=find(deltax==0);
deltax(idx)=ones(size(idx));
@@ -878,8 +1117,8 @@ while 1,
ng=norm(g);
if ng==Inf
if dispwarn
- disp(errmes);
- disp(error42);
+ disp(errmes)
+ disp(error42)
end
exitflag=-4;
if trx
@@ -888,8 +1127,8 @@ while 1,
return
elseif isnan(ng)
if dispwarn
- disp(errmes);
- disp(error41);
+ disp(errmes)
+ disp(error41)
end
exitflag=-4;
if trx
@@ -901,10 +1140,10 @@ while 1,
break
end
end
- if ng<=ZeroGrad,
+ if ng<=ZeroGrad
if dispwarn
- disp(termwarn1);
- disp(warn1);
+ disp(termwarn1)
+ disp(warn1)
end
exitflag=-8;
if trx
@@ -921,19 +1160,32 @@ while 1,
if ~constr && abs(f-fopt)<abs(fopt)*optim.TolFun && kcheck>5 && ng<1
idx=find(abs(g)<=epsnorm2);
ni=size(idx,2);
- if ni>=1 && ni<=n/2 && kflat<=3, kflat=kflat+1;
- if dispwarn, disp(wrnmes); disp(warn31); end, warnno=1;
+ if ni>=1 && ni<=n/2 && kflat<=3
+ kflat=kflat+1;
+ if dispwarn
+ disp(wrnmes)
+ disp(warn31)
+ end
+ warnno=1;
x1=x; fm=f;
- for j=idx, y=x(j); f2=fm;
- if y==0, x1(j)=1; elseif abs(y)<1, x1(j)=sign(y); else, x1(j)=y; end
- for i=1:20, x1(j)=x1(j)/1.15;
+ for j=idx
+ y=x(j); f2=fm;
+ if y==0
+ x1(j)=1;
+ elseif abs(y)<1
+ x1(j)=sign(y);
+ else
+ x1(j)=y;
+ end
+ for i=1:20
+ x1(j)=x1(j)/1.15;
if trx
f1=feval(fun,x1',varargin{:});
else
f1=feval(fun,x1,varargin{:});
end
n_f_evals=n_f_evals+1;
- if abs(f1)~=Inf && ~isnan(f1),
+ if abs(f1)~=Inf && ~isnan(f1)
if h1*f1>h1*fm
y=x1(j);
fm=f1;
@@ -948,7 +1200,7 @@ while 1,
x1(j)=y;
end
if h1*fm>h1*f
- if app,
+ if app
deltax=h1*ddx*ones(size(deltax));
if trx
gt=apprgrdn(x1',fm,fun,deltax',1,varargin{:});
@@ -968,9 +1220,9 @@ while 1,
gt=gt';
end
ngt=norm(gt);
- if ~isnan(ngt) && ngt>epsnorm2,
+ if ~isnan(ngt) && ngt>epsnorm2
if dispwarn
- disp(warn32);
+ disp(warn32)
end
optim.TolFun=optim.TolFun/5;
x=x1;
diff --git a/matlab/optimize_prior.m b/matlab/optimize_prior.m
index cdb03ecff..ffa5ff3df 100644
--- a/matlab/optimize_prior.m
+++ b/matlab/optimize_prior.m
@@ -34,7 +34,7 @@ while look_for_admissible_initial_condition
look_for_admissible_initial_condition = 0;
end
else
- if iter == 2000;
+ if iter == 2000
scale = scale/1.1;
iter = 0;
else
diff --git a/matlab/parallel/AnalyseComputationalEnvironment.m b/matlab/parallel/AnalyseComputationalEnvironment.m
index e5d2a87f5..c214ec405 100644
--- a/matlab/parallel/AnalyseComputationalEnvironment.m
+++ b/matlab/parallel/AnalyseComputationalEnvironment.m
@@ -31,7 +31,7 @@ function [ErrorCode] = AnalyseComputationalEnvironment(DataInput, DataInputAdd)
% field RemoteTmpFolder (the temporary directory created/destroyed on remote
% computer) is used.
-if ispc,
+if ispc
[tempo, MasterName]=system('hostname');
MasterName=deblank(MasterName);
end
@@ -114,11 +114,11 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
OScallerUnix=~ispc;
OScallerWindows=ispc;
OStargetUnix=strcmpi('unix',DataInput(Node).OperatingSystem);
- if isempty(DataInput(Node).OperatingSystem),
+ if isempty(DataInput(Node).OperatingSystem)
OStargetUnix=OScallerUnix;
end
OStargetWindows=strcmpi('windows',DataInput(Node).OperatingSystem);
- if isempty(DataInput(Node).OperatingSystem),
+ if isempty(DataInput(Node).OperatingSystem)
OStargetWindows=OScallerWindows;
end
@@ -279,7 +279,7 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
si2=[];
de2=[];
- if ~isempty(DataInput(Node).Port),
+ if ~isempty(DataInput(Node).Port)
ssh_token = ['-p ',DataInput(Node).Port];
else
ssh_token = '';
@@ -347,11 +347,11 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
s2='fclose(fT);\n';
SBS=strfind(DataInput(Node).DynarePath,'\');
DPStr=DataInput(Node).DynarePath;
- if isempty(SBS),
+ if isempty(SBS)
DPStrNew=DPStr;
else
DPStrNew=[DPStr(1:SBS(1)),'\'];
- for j=2:length(SBS),
+ for j=2:length(SBS)
DPStrNew=[DPStrNew,DPStr(SBS(j-1)+1:SBS(j)),'\'];
end
DPStrNew=[DPStrNew,DPStr(SBS(end)+1:end)];
@@ -401,8 +401,8 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
% machine when the user is .UserName with password .Password and
% the path is MatlabOctavePath.
- if Environment,
- if ~isempty(DataInput(Node).Port),
+ if Environment
+ if ~isempty(DataInput(Node).Port)
ssh_token = ['-p ',DataInput(Node).Port];
else
ssh_token = '';
@@ -413,7 +413,7 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
system(['ssh ',ssh_token,' ',DataInput(Node).UserName,'@',DataInput(Node).ComputerName,' "cd ',DataInput(Node).RemoteDirectory,'/',RemoteTmpFolder, '; ', DataInput(Node).MatlabOctavePath, ' -nosplash -nodesktop -minimize -r Tracing;" &']);
end
else
- if ~strcmp(DataInput(Node).ComputerName,MasterName), % run on remote machine
+ if ~strcmp(DataInput(Node).ComputerName,MasterName) % run on remote machine
if strfind([DataInput(Node).MatlabOctavePath], 'octave') % Hybrid computing Matlab(Master)->Octave(Slaves) and Vice Versa!
[NonServeS NenServeD]=system(['start /B psexec \\',DataInput(Node).ComputerName,' -e -u ',DataInput(Node).UserName,' -p ',DataInput(Node).Password,' -W ',DataInput(Node).RemoteDrive,':\',DataInput(Node).RemoteDirectory,'\',RemoteTmpFolder ' -low ',DataInput(Node).MatlabOctavePath,' Tracing.m']);
else
@@ -433,14 +433,15 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
t1=fix(clock);
- if t1(5)+1>60;
+ if t1(5)+1>60
t2=2;
- else t2=t1(5)+1;
+ else
+ t2=t1(5)+1;
end
Flag=0;
- while (1);
+ while (1)
if Flag==0
disp('Try to run matlab/octave on remote machine ... ')
skipline()
@@ -556,7 +557,7 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
Environment1=Environment;
disp('Checking Hardware please wait ...');
if (DataInput(Node).Local == 1)
- if Environment,
+ if Environment
if ~ismac
[si0 de0]=system('grep processor /proc/cpuinfo');
else
@@ -567,14 +568,14 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
[si0 de0]=system(['psinfo \\']);
end
else
- if Environment,
- if ~isempty(DataInput(Node).Port),
+ if Environment
+ if ~isempty(DataInput(Node).Port)
ssh_token = ['-p ',DataInput(Node).Port];
else
ssh_token = '';
end
- if OStargetUnix,
- if RemoteEnvironment ==1 ,
+ if OStargetUnix
+ if RemoteEnvironment ==1
[si0 de0]=system(['ssh ',ssh_token,' ',DataInput(Node).UserName,'@',DataInput(Node).ComputerName,' grep processor /proc/cpuinfo']);
else % it is MAC
[si0 de0]=system(['ssh ',ssh_token,' ',DataInput(Node).UserName,'@',DataInput(Node).ComputerName,' sysctl -n hw.ncpu']);
@@ -594,7 +595,7 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
RealCPUnbr=GiveCPUnumber(de0,Environment1);
% Questo controllo penso che si possa MIGLIORARE!!!!!
- if isempty (RealCPUnbr) && Environment1==0,
+ if isempty (RealCPUnbr) && Environment1==0
[si0 de0]=system(['psinfo \\',DataInput(Node).ComputerName]);
end
RealCPUnbr=GiveCPUnumber(de0,Environment1);
@@ -626,7 +627,7 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
disp(['Hardware has ', num2str(RealCPUnbr),' Cpu/Cores!'])
disp(['User requires ',num2str(CPUnbrUser),' Cpu/Cores!'])
- if CPUnbrUser==RealCPUnbr,
+ if CPUnbrUser==RealCPUnbr
% It is Ok!
disp('Check on CPUnbr Variable ..... Ok!')
skipline(3)
diff --git a/matlab/parallel/GiveCPUnumber.m b/matlab/parallel/GiveCPUnumber.m
index 00b7fc451..4314a0607 100644
--- a/matlab/parallel/GiveCPUnumber.m
+++ b/matlab/parallel/GiveCPUnumber.m
@@ -33,7 +33,7 @@ function [nCPU]= GiveCPUnumber (ComputerInformations, Environment)
nCPU='';
-if nargin < 2,
+if nargin < 2
% Determine a specific operating system or software version when necessary
% for different command (sintax, name, ...).
Environment=~ispc;
diff --git a/matlab/parallel/InitializeComputationalEnvironment.m b/matlab/parallel/InitializeComputationalEnvironment.m
index 02df7aad4..3a13a96ad 100644
--- a/matlab/parallel/InitializeComputationalEnvironment.m
+++ b/matlab/parallel/InitializeComputationalEnvironment.m
@@ -46,15 +46,15 @@ end
global options_
isHybridMatlabOctave = false;
-for j=1:length(options_.parallel),
- if isempty(options_.parallel(j).MatlabOctavePath),
+for j=1:length(options_.parallel)
+ if isempty(options_.parallel(j).MatlabOctavePath)
if isoctave
options_.parallel(j).MatlabOctavePath = 'octave';
else
options_.parallel(j).MatlabOctavePath = 'matlab';
end
end
- if options_.parallel(j).Local && isempty(options_.parallel(j).DynarePath),
+ if options_.parallel(j).Local && isempty(options_.parallel(j).DynarePath)
dynareroot = strrep(which('dynare'),'dynare.m','');
options_.parallel(j).DynarePath=dynareroot;
end
@@ -62,7 +62,7 @@ for j=1:length(options_.parallel),
end
isHybridMatlabOctave = isHybridMatlabOctave && ~isoctave;
options_.parallel_info.isHybridMatlabOctave = isHybridMatlabOctave;
-if isHybridMatlabOctave,
+if isHybridMatlabOctave
% Reset dynare random generator and seed.
set_dynare_seed('default');
end
@@ -94,7 +94,7 @@ CPUWeightTemp=ones(1,lP)*(-1);
CPUWeightTemp=CPUWeight;
for i=1:lP
- [NoNServes mP]=max(CPUWeightTemp);
+ [NoNServes, mP]=max(CPUWeightTemp);
NewPosition(i)=mP;
CPUWeightTemp(mP)=-1;
end
diff --git a/matlab/parallel/closeSlave.m b/matlab/parallel/closeSlave.m
index 339d776bb..38c7d2b11 100644
--- a/matlab/parallel/closeSlave.m
+++ b/matlab/parallel/closeSlave.m
@@ -1,4 +1,4 @@
-function closeSlave(Parallel,TmpFolder,partial),
+function closeSlave(Parallel,TmpFolder,partial)
% PARALLEL CONTEXT
% In parallel context, this utility closes all remote matlab instances
% called by masterParallel when strategy (1) is active i.e. always open (which leaves
@@ -32,7 +32,7 @@ function closeSlave(Parallel,TmpFolder,partial),
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-if nargin<3,
+if nargin<3
partial=0;
end
@@ -40,8 +40,8 @@ s=warning('off');
if partial==1
save('slaveParallel_break.mat','partial')
- for indPC=1:length(Parallel),
- if (Parallel(indPC).Local==0),
+ for indPC=1:length(Parallel)
+ if (Parallel(indPC).Local==0)
dynareParallelSendFiles('slaveParallel_break.mat',TmpFolder,Parallel(indPC));
end
end
@@ -50,8 +50,8 @@ if partial==1
end
if partial==-1
delete('slaveParallel_break.mat')
- for indPC=1:length(Parallel),
- if (Parallel(indPC).Local==0),
+ for indPC=1:length(Parallel)
+ if (Parallel(indPC).Local==0)
dynareParallelDelete( 'slaveParallel_break.mat',TmpFolder,Parallel(indPC));
end
end
@@ -59,8 +59,8 @@ if partial==-1
return
end
-for indPC=1:length(Parallel),
- if (Parallel(indPC).Local==0),
+for indPC=1:length(Parallel)
+ if (Parallel(indPC).Local==0)
dynareParallelDelete( 'slaveParallel_input*.mat',TmpFolder,Parallel(indPC));
end
@@ -74,10 +74,10 @@ for indPC=1:length(Parallel),
end
while(1)
- if isempty(dynareParallelDir(['P_slave_',int2str(j),'End.txt'],TmpFolder,Parallel));
- for indPC=1:length(Parallel),
- if (Parallel(indPC).Local==0),
- dynareParallelRmDir(TmpFolder,Parallel(indPC)),
+ if isempty(dynareParallelDir(['P_slave_',int2str(j),'End.txt'],TmpFolder,Parallel))
+ for indPC=1:length(Parallel)
+ if (Parallel(indPC).Local==0)
+ dynareParallelRmDir(TmpFolder,Parallel(indPC))
end
end
break
@@ -85,5 +85,4 @@ while(1)
end
end
-s=warning('on');
-
+s=warning('on');
\ No newline at end of file
diff --git a/matlab/parallel/distributeJobs.m b/matlab/parallel/distributeJobs.m
index 0667d902f..f763fa771 100644
--- a/matlab/parallel/distributeJobs.m
+++ b/matlab/parallel/distributeJobs.m
@@ -48,7 +48,7 @@ totCPU=0;
lP=length(Parallel);
CPUWeight=ones(1,length(Parallel))*(-1);
-for j=1:lP,
+for j=1:lP
if mod(length(Parallel(j).CPUnbr),Parallel(j).NumberOfThreadsPerJob)
skipline()
disp(['PARALLEL_ERROR:: NumberOfThreadsPerJob = ',int2str(Parallel(j).NumberOfThreadsPerJob),' is not an exact divisor of number of CPUs = ',int2str(length(Parallel(j).CPUnbr)),'!'])
@@ -77,7 +77,7 @@ NumbersOfJobs=nBlock-fBlock+1;
SumOfJobs=0;
JobsForNode=zeros(1,nC);
-for j=1:lP,
+for j=1:lP
CPUWeight(j)=str2num(Parallel(j).NodeWeight)*nCPUoriginal(j);
end
CPUWeight=CPUWeight./sum(CPUWeight);
@@ -161,7 +161,7 @@ for i=1:nC
ChekOverFlow=ChekOverFlow+JobAssignedCpu;
if ChekOverFlow>=JobsForNode(i)
- break;
+ break
end
end
@@ -204,7 +204,7 @@ for i=1:nCPU(nC)
end
for i=1:nC
- if JobsForNode(i)~=0;
+ if JobsForNode(i)~=0
totSLAVES=totSLAVES+1;
end
end
diff --git a/matlab/parallel/dynareParallelDelete.m b/matlab/parallel/dynareParallelDelete.m
index 060a35f13..97f700eed 100644
--- a/matlab/parallel/dynareParallelDelete.m
+++ b/matlab/parallel/dynareParallelDelete.m
@@ -28,20 +28,20 @@ function dynareParallelDelete(fname,pname,Parallel)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-if nargin ==0,
+if nargin ==0
disp('dynareParallelDelete(fname)')
return
end
-if nargin ==1,
+if nargin ==1
pname='';
else
pname=[pname,filesep];
end
-for indPC=1:length(Parallel),
- if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem),
- if ~isempty(Parallel(indPC).Port),
+for indPC=1:length(Parallel)
+ if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem)
+ if ~isempty(Parallel(indPC).Port)
ssh_token = ['-p ',Parallel(indPC).Port];
else
ssh_token = '';
diff --git a/matlab/parallel/dynareParallelDeleteNewFiles.m b/matlab/parallel/dynareParallelDeleteNewFiles.m
index e28cd77da..b2eed497a 100644
--- a/matlab/parallel/dynareParallelDeleteNewFiles.m
+++ b/matlab/parallel/dynareParallelDeleteNewFiles.m
@@ -35,11 +35,11 @@ function dynareParallelDeleteNewFiles(PRCDir,Parallel,PRCDirSnapshot,varargin)
NewFilesFromSlaves={};
% try
-for indPC=1:length(Parallel),
+for indPC=1:length(Parallel)
- if Parallel(indPC).Local==0;
+ if Parallel(indPC).Local==0
[NewFilesFromSlaves, PRCDirSnapshot{indPC}]=dynareParallelFindNewFiles(PRCDirSnapshot{indPC},Parallel(indPC), PRCDir);
- if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem),
+ if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem)
fS='/';
else
fS='\';
@@ -59,7 +59,7 @@ for indPC=1:length(Parallel),
for indexc=1:length(varargin)
exception_flag=exception_flag+(~isempty(strfind(fileaddress{2},varargin{indexc})));
end
- if exception_flag==0,
+ if exception_flag==0
dynareParallelDelete(fileaddress{2},[PRCDir,fS,fileaddress{1}],Parallel(indPC));
disp('New file deleted in remote -->');
diff --git a/matlab/parallel/dynareParallelDir.m b/matlab/parallel/dynareParallelDir.m
index daecfe6cd..445840107 100644
--- a/matlab/parallel/dynareParallelDir.m
+++ b/matlab/parallel/dynareParallelDir.m
@@ -28,10 +28,10 @@ function dirlist = dynareParallelDir(filename,PRCDir,Parallel)
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
dirlist=[];
-for indPC=1:length(Parallel),
- if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem),
- if Parallel(indPC).Local==0,
- if ~isempty(Parallel(indPC).Port),
+for indPC=1:length(Parallel)
+ if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem)
+ if Parallel(indPC).Local==0
+ if ~isempty(Parallel(indPC).Port)
ssh_token = ['-p ',Parallel(indPC).Port];
else
ssh_token = '';
@@ -45,7 +45,7 @@ for indPC=1:length(Parallel),
else
[check, ax]=system(['ssh ',ssh_token,' ',Parallel(indPC).UserName,'@',Parallel(indPC).ComputerName,' ls ',Parallel(indPC).RemoteDirectory,'/',PRCDir,'/',filename]);
end
- if check ~= 0 || ~isempty(strfind(ax,'No such file or directory'));
+ if check ~= 0 || ~isempty(strfind(ax,'No such file or directory'))
ax=[];
else
indax=regexp(ax,'\n');
@@ -61,7 +61,7 @@ for indPC=1:length(Parallel),
% It is necessary to capture the ls warning message and properly manage the jolly char '*'!
[check ax]=system(['ls ' ,filename, ' 2> OctaveStandardOutputMessage.txt']);
- if check ~= 0 || ~isempty(strfind(ax,'No such file or directory'));
+ if check ~= 0 || ~isempty(strfind(ax,'No such file or directory'))
ax=[];
end
else
@@ -75,32 +75,32 @@ for indPC=1:length(Parallel),
end
else
if isoctave % Patch for peculiar behaviour of ls under Windows.
- if Parallel(indPC).Local==0,
+ if Parallel(indPC).Local==0
ax0=dir(['\\',Parallel(indPC).ComputerName,'\',Parallel(indPC).RemoteDrive,'$\',Parallel(indPC).RemoteDirectory,'\',PRCDir,'\',filename]);
else
ax0=dir(filename);
end
- if isempty(ax0),
+ if isempty(ax0)
ax='';
else
clear ax1;
- for jax=1:length(ax0);
+ for jax=1:length(ax0)
ax1{jax}=ax0(jax).name;
end
ax=char(ax1{:});
end
else
- if Parallel(indPC).Local==0,
+ if Parallel(indPC).Local==0
ax=ls(['\\',Parallel(indPC).ComputerName,'\',Parallel(indPC).RemoteDrive,'$\',Parallel(indPC).RemoteDirectory,'\',PRCDir,'\',filename]);
else
ax=ls(filename);
end
end
end
- if isempty(dirlist),
+ if isempty(dirlist)
dirlist=ax;
- elseif ~isempty(ax),
+ elseif ~isempty(ax)
dirlist = char(dirlist, ax);
end
end
diff --git a/matlab/parallel/dynareParallelGetFiles.m b/matlab/parallel/dynareParallelGetFiles.m
index 6dbf0539e..4e23ed6e4 100644
--- a/matlab/parallel/dynareParallelGetFiles.m
+++ b/matlab/parallel/dynareParallelGetFiles.m
@@ -33,26 +33,26 @@ function dynareParallelGetFiles(NamFileInput,PRCDir,Parallel)
NamFileInput0=NamFileInput;
-for indPC=1:length(Parallel),
- if Parallel(indPC).Local==0,
- if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem),
- if ~isempty(Parallel(indPC).Port),
+for indPC=1:length(Parallel)
+ if Parallel(indPC).Local==0
+ if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem)
+ if ~isempty(Parallel(indPC).Port)
ssh_token = ['-p ',Parallel(indPC).Port];
else
ssh_token = '';
end
- if ~isempty(Parallel(indPC).Port),
+ if ~isempty(Parallel(indPC).Port)
scp_token = ['-P ',Parallel(indPC).Port];
else
scp_token = '';
end
- if ischar(NamFileInput0),
- for j=1:size(NamFileInput0,1),
+ if ischar(NamFileInput0)
+ for j=1:size(NamFileInput0,1)
NamFile(j,:)={['./'],deblank(NamFileInput0(j,:))};
end
NamFileInput = NamFile;
end
- for jfil=1:size(NamFileInput,1),
+ for jfil=1:size(NamFileInput,1)
if isoctave % Patch for peculiar behaviour of ls under Linux.
% It is necessary to manage the jolly char '*'!
@@ -92,14 +92,14 @@ for indPC=1:length(Parallel),
end
else
- if ischar(NamFileInput0),
- for j=1:size(NamFileInput0,1),
+ if ischar(NamFileInput0)
+ for j=1:size(NamFileInput0,1)
NamFile(j,:)={['.\'],deblank(NamFileInput0(j,:))};
end
NamFileInput = NamFile;
end
- for jfil=1:size(NamFileInput,1),
- if ~isempty(dynareParallelDir(NamFileInput{jfil,2},[PRCDir,filesep,NamFileInput{jfil,1}],Parallel(indPC))),
+ for jfil=1:size(NamFileInput,1)
+ if ~isempty(dynareParallelDir(NamFileInput{jfil,2},[PRCDir,filesep,NamFileInput{jfil,1}],Parallel(indPC)))
copyfile(['\\',Parallel(indPC).ComputerName,'\',Parallel(indPC).RemoteDrive,'$\',Parallel(indPC).RemoteDirectory,'\',PRCDir,'\',NamFileInput{jfil,1},NamFileInput{jfil,2}],NamFileInput{jfil,1});
end
end
diff --git a/matlab/parallel/dynareParallelGetNewFiles.m b/matlab/parallel/dynareParallelGetNewFiles.m
index 5f7eb43a3..c27711d57 100644
--- a/matlab/parallel/dynareParallelGetNewFiles.m
+++ b/matlab/parallel/dynareParallelGetNewFiles.m
@@ -36,11 +36,11 @@ function [PRCDirSnapshot]=dynareParallelGetNewFiles(PRCDir,Parallel,PRCDirSnapsh
NewFilesFromSlaves={};
% try
-for indPC=1:length(Parallel),
+for indPC=1:length(Parallel)
- if Parallel(indPC).Local==0;
+ if Parallel(indPC).Local==0
[NewFilesFromSlaves, PRCDirSnapshot{indPC}]=dynareParallelFindNewFiles(PRCDirSnapshot{indPC},Parallel(indPC), PRCDir);
- if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem),
+ if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem)
fS='/';
else
fS='\';
diff --git a/matlab/parallel/dynareParallelListAllFiles.m b/matlab/parallel/dynareParallelListAllFiles.m
index 53e893e15..6cb866455 100644
--- a/matlab/parallel/dynareParallelListAllFiles.m
+++ b/matlab/parallel/dynareParallelListAllFiles.m
@@ -37,14 +37,14 @@ if (~ispc || strcmpi('unix',Parallel.OperatingSystem))
fileList={};
currentPath=[];
- if ~isempty(Parallel.Port),
+ if ~isempty(Parallel.Port)
ssh_token = ['-p ',Parallel.Port];
else
ssh_token = '';
end
% Get the data for the current remote directory.
- [Flag fL]=system(['ssh ',ssh_token,' ',' ',Parallel.UserName,'@',Parallel.ComputerName,' ls ',Parallel.RemoteDirectory,'/',PRCDir, ' -R -p -1']);
+ [Flag, fL]=system(['ssh ',ssh_token,' ',' ',Parallel.UserName,'@',Parallel.ComputerName,' ls ',Parallel.RemoteDirectory,'/',PRCDir, ' -R -p -1']);
% Format the return value fL.
diff --git a/matlab/parallel/dynareParallelMkDir.m b/matlab/parallel/dynareParallelMkDir.m
index 9e8d7b7de..3c4466d7b 100644
--- a/matlab/parallel/dynareParallelMkDir.m
+++ b/matlab/parallel/dynareParallelMkDir.m
@@ -29,24 +29,22 @@ function dynareParallelMkDir(PRCDir,Parallel)
-if nargin ==0,
+if nargin ==0
disp('dynareParallelMkDir(dirname,Parallel)')
return
end
for indPC=1:length(Parallel)
- if Parallel(indPC).Local==0,
- if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem),
- if ~isempty(Parallel(indPC).Port),
+ if Parallel(indPC).Local==0
+ if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem)
+ if ~isempty(Parallel(indPC).Port)
ssh_token = ['-p ',Parallel(indPC).Port];
else
ssh_token = '';
end
- [NonServeS NonServeD]=system(['ssh ',ssh_token,' ',Parallel(indPC).UserName,'@',Parallel(indPC).ComputerName,' mkdir -p ',Parallel(indPC).RemoteDirectory,'/',PRCDir]);
+ [NonServeS, NonServeD]=system(['ssh ',ssh_token,' ',Parallel(indPC).UserName,'@',Parallel(indPC).ComputerName,' mkdir -p ',Parallel(indPC).RemoteDirectory,'/',PRCDir]);
else
- [NonServeS NonServeD]=mkdir(['\\',Parallel(indPC).ComputerName,'\',Parallel(indPC).RemoteDrive,'$\',Parallel(indPC).RemoteDirectory,'\',PRCDir]);
+ [NonServeS, NonServeD]=mkdir(['\\',Parallel(indPC).ComputerName,'\',Parallel(indPC).RemoteDrive,'$\',Parallel(indPC).RemoteDirectory,'\',PRCDir]);
end
end
-end
-
-return
\ No newline at end of file
+end
\ No newline at end of file
diff --git a/matlab/parallel/dynareParallelRmDir.m b/matlab/parallel/dynareParallelRmDir.m
index fbf7b7790..03c9082b0 100644
--- a/matlab/parallel/dynareParallelRmDir.m
+++ b/matlab/parallel/dynareParallelRmDir.m
@@ -30,7 +30,7 @@ function dynareParallelRmDir(PRCDir,Parallel)
-if nargin ==0,
+if nargin ==0
disp('dynareParallelRmDir(fname)')
return
end
@@ -45,7 +45,7 @@ ok(5)=~isempty(strfind(PRCDir,'m'));
ok(6)=~isempty(strfind(PRCDir,'s'));
ok(7)=~isempty(PRCDir);
-if sum(ok)<7,
+if sum(ok)<7
error('The name of the remote tmp folder does not comply the security standards!'),
end
@@ -53,34 +53,32 @@ if isoctave
confirm_recursive_rmdir(false, 'local');
end
-for indPC=1:length(Parallel),
+for indPC=1:length(Parallel)
ok(1)=isempty(strfind(Parallel(indPC).RemoteDirectory,'..'));
- if sum(ok)<7,
+ if sum(ok)<7
error('The remote folder path structure does not comply the security standards!'),
end
while (1)
- if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem),
- if ~isempty(Parallel(indPC).Port),
+ if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem)
+ if ~isempty(Parallel(indPC).Port)
ssh_token = ['-p ',Parallel(indPC).Port];
else
ssh_token = '';
end
- [stat NonServe] = system(['ssh ',ssh_token,' ',Parallel(indPC).UserName,'@',Parallel(indPC).ComputerName,' rm -fr ',Parallel(indPC).RemoteDirectory,'/',PRCDir,]);
- break;
+ [stat, NonServe] = system(['ssh ',ssh_token,' ',Parallel(indPC).UserName,'@',Parallel(indPC).ComputerName,' rm -fr ',Parallel(indPC).RemoteDirectory,'/',PRCDir,]);
+ break
else
[stat, mess, id] = rmdir(['\\',Parallel(indPC).ComputerName,'\',Parallel(indPC).RemoteDrive,'$\',Parallel(indPC).RemoteDirectory,'\',PRCDir],'s');
- if stat==1,
- break,
+ if stat==1
+ break
else
- if isempty(dynareParallelDir(PRCDir,'',Parallel));
- break,
+ if isempty(dynareParallelDir(PRCDir,'',Parallel))
+ break
else
pause(1);
end
end
end
end
-end
-
-return
\ No newline at end of file
+end
\ No newline at end of file
diff --git a/matlab/parallel/dynareParallelSendFiles.m b/matlab/parallel/dynareParallelSendFiles.m
index 6f7e645f5..8eed09265 100644
--- a/matlab/parallel/dynareParallelSendFiles.m
+++ b/matlab/parallel/dynareParallelSendFiles.m
@@ -32,31 +32,31 @@ function dynareParallelSendFiles(NamFileInput,PRCDir,Parallel)
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-if ischar(NamFileInput),
- for j=1:size(NamFileInput,1),
+if ischar(NamFileInput)
+ for j=1:size(NamFileInput,1)
NamFile(j,:)={'',deblank(NamFileInput(j,:))};
end
NamFileInput = NamFile;
end
-for indPC=1:length(Parallel),
- if Parallel(indPC).Local==0,
- if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem),
- if ~isempty(Parallel(indPC).Port),
+for indPC=1:length(Parallel)
+ if Parallel(indPC).Local==0
+ if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem)
+ if ~isempty(Parallel(indPC).Port)
ssh_token = ['-p ',Parallel(indPC).Port];
else
ssh_token = '';
end
- if ~isempty(Parallel(indPC).Port),
+ if ~isempty(Parallel(indPC).Port)
scp_token = ['-P ',Parallel(indPC).Port];
else
scp_token = '';
end
- for jfil=1:size(NamFileInput,1),
+ for jfil=1:size(NamFileInput,1)
if ~isempty(NamFileInput{jfil,1})
- [NonServeL NonServeR]=system(['ssh ',ssh_token,' ',Parallel(indPC).UserName,'@',Parallel(indPC).ComputerName,' mkdir -p ',Parallel(indPC).RemoteDirectory,'/',PRCDir,'/',NamFileInput{jfil,1}]);
+ [NonServeL, NonServeR]=system(['ssh ',ssh_token,' ',Parallel(indPC).UserName,'@',Parallel(indPC).ComputerName,' mkdir -p ',Parallel(indPC).RemoteDirectory,'/',PRCDir,'/',NamFileInput{jfil,1}]);
end
- [NonServeL NonServeR]=system(['scp ',scp_token,' ',NamFileInput{jfil,1},NamFileInput{jfil,2},' ',Parallel(indPC).UserName,'@',Parallel(indPC).ComputerName,':',Parallel(indPC).RemoteDirectory,'/',PRCDir,'/',NamFileInput{jfil,1}]);
+ [NonServeL, NonServeR]=system(['scp ',scp_token,' ',NamFileInput{jfil,1},NamFileInput{jfil,2},' ',Parallel(indPC).UserName,'@',Parallel(indPC).ComputerName,':',Parallel(indPC).RemoteDirectory,'/',PRCDir,'/',NamFileInput{jfil,1}]);
end
else
for jfil=1:size(NamFileInput,1)
@@ -74,14 +74,14 @@ for indPC=1:length(Parallel),
NamFileInputTemp=NamFileInput{jfil,1};
while(1)
Bs=strfind(NamFileInputTemp,'/');
- if isempty(Bs),
- break;
+ if isempty(Bs)
+ break
else
NamFileInputTemp(1,Bs)='\';
end
end
- [NonServeL NonServeR]=system(['mkdir \\',Parallel(indPC).ComputerName,'\',Parallel(indPC).RemoteDrive,'$\',Parallel(indPC).RemoteDirectory,'\',PRCDir,'\',NamFileInputTemp]);
+ [NonServeL, NonServeR]=system(['mkdir \\',Parallel(indPC).ComputerName,'\',Parallel(indPC).RemoteDrive,'$\',Parallel(indPC).RemoteDirectory,'\',PRCDir,'\',NamFileInputTemp]);
else
mkdir(['\\',Parallel(indPC).ComputerName,'\',Parallel(indPC).RemoteDrive,'$\',Parallel(indPC).RemoteDirectory,'\',PRCDir,'\',NamFileInput{jfil,1}]);
@@ -100,14 +100,14 @@ for indPC=1:length(Parallel),
NamFileInputTemp=NamFileInput{jfil,1};
while(1)
Bs=strfind(NamFileInputTemp,'/');
- if isempty(Bs),
- break;
+ if isempty(Bs)
+ break
else
NamFileInputTemp(1,Bs)='\';
end
end
- [NonServeS NonServeD]=system(['copy ',NamFileInputTemp, NamFileInput{jfil,2},' \\',Parallel(indPC).ComputerName,'\',Parallel(indPC).RemoteDrive,'$\',Parallel(indPC).RemoteDirectory,'\',PRCDir,'\',NamFileInputTemp]);
+ [NonServeS, NonServeD]=system(['copy ',NamFileInputTemp, NamFileInput{jfil,2},' \\',Parallel(indPC).ComputerName,'\',Parallel(indPC).RemoteDrive,'$\',Parallel(indPC).RemoteDirectory,'\',PRCDir,'\',NamFileInputTemp]);
else
copyfile([NamFileInput{jfil,1},NamFileInput{jfil,2}],['\\',Parallel(indPC).ComputerName,'\',Parallel(indPC).RemoteDrive,'$\',Parallel(indPC).RemoteDirectory,'\',PRCDir,'\',NamFileInput{jfil,1}]);
diff --git a/matlab/parallel/dynareParallelSnapshot.m b/matlab/parallel/dynareParallelSnapshot.m
index 4f07b04df..089dd9154 100644
--- a/matlab/parallel/dynareParallelSnapshot.m
+++ b/matlab/parallel/dynareParallelSnapshot.m
@@ -33,8 +33,8 @@ function [PRCDirSnapshot]=dynareParallelSnapshot(PRCDir,Parallel)
PRCDirSnapshot={};
-for indPC=1:length(Parallel),
- if Parallel(indPC).Local==0;
+for indPC=1:length(Parallel)
+ if Parallel(indPC).Local==0
% The first call ...
PRCDirSnapshot{indPC}=dynareParallelListAllFiles('Root',PRCDir,Parallel(indPC));
diff --git a/matlab/parallel/fMessageStatus.m b/matlab/parallel/fMessageStatus.m
index 6d84705ab..4ce6cc541 100644
--- a/matlab/parallel/fMessageStatus.m
+++ b/matlab/parallel/fMessageStatus.m
@@ -33,7 +33,7 @@ function fMessageStatus(prtfrc, njob, waitbarString, waitbarTitle, Parallel)
global funcName
-if nargin<5,
+if nargin<5
Parallel.Local=1;
end
@@ -44,7 +44,7 @@ end
fslave = dir( ['slaveParallel_input',int2str(njob),'.mat']);
fbreak = dir( ['slaveParallel_break.mat']);
-if isempty(fslave) || ~isempty(fbreak),
+if isempty(fslave) || ~isempty(fbreak)
error('Master asked to break the job');
end
diff --git a/matlab/parallel/fParallel.m b/matlab/parallel/fParallel.m
index 51e6ebe16..d0f1d936d 100644
--- a/matlab/parallel/fParallel.m
+++ b/matlab/parallel/fParallel.m
@@ -53,7 +53,7 @@ load( [fname,'_input'])
if exist('fGlobalVar') && ~isempty (fGlobalVar)
globalVars = fieldnames(fGlobalVar);
- for j=1:length(globalVars),
+ for j=1:length(globalVars)
eval(['global ',globalVars{j},';'])
evalin('base',['global ',globalVars{j},';'])
end
@@ -67,12 +67,12 @@ fInputVar.Parallel = Parallel;
% Launch the routine to be run in parallel.
-try,
- tic,
+try
+ tic
fOutputVar = feval(fname, fInputVar ,fblck, nblck, whoiam, ThisMatlab);
- toc,
- if isfield(fOutputVar,'OutputFileName'),
+ toc
+ if isfield(fOutputVar,'OutputFileName')
OutputFileName = fOutputVar.OutputFileName;
else
OutputFileName = '';
@@ -81,7 +81,7 @@ try,
% Save the output result.
save([ fname,'_output_',int2str(whoiam),'.mat'],'fOutputVar' )
end
- if isfield(fOutputVar,'CloseAllSlaves'),
+ if isfield(fOutputVar,'CloseAllSlaves')
CloseAllSlaves = 1;
fOutputVar = rmfield(fOutputVar,'CloseAllSlaves');
save([ fname,'_output_',int2str(whoiam),'.mat'],'fOutputVar' )
@@ -89,7 +89,7 @@ try,
end
disp(['fParallel ',int2str(whoiam),' completed.'])
-catch,
+catch
theerror = lasterror;
if strfind(theerror.message,'Master asked to break the job')
fOutputVar.message = theerror;
@@ -101,7 +101,7 @@ catch,
save([ fname,'_output_',int2str(whoiam),'.mat'],'fOutputVar' )
waitbarString = theerror.message;
% waitbarTitle=['Metropolis-Hastings ',options_.parallel(ThisMatlab).ComputerName];
- if Parallel(ThisMatlab).Local,
+ if Parallel(ThisMatlab).Local
waitbarTitle='Local ';
else
waitbarTitle=[Parallel(ThisMatlab).ComputerName];
diff --git a/matlab/parallel/masterParallel.m b/matlab/parallel/masterParallel.m
index 902b237dc..7544e85e7 100644
--- a/matlab/parallel/masterParallel.m
+++ b/matlab/parallel/masterParallel.m
@@ -91,11 +91,11 @@ Strategy=Parallel_info.leaveSlaveOpen;
islocal = 1;
isHybridMatlabOctave = Parallel_info.isHybridMatlabOctave;
-for j=1:length(Parallel),
+for j=1:length(Parallel)
islocal=islocal*Parallel(j).Local;
end
if nargin>8 && initialize==1
- if islocal == 0,
+ if islocal == 0
PRCDir=CreateTimeString();
assignin('base','PRCDirTmp',PRCDir),
evalin('base','options_.parallel_info.RemoteTmpFolder=PRCDirTmp;')
@@ -108,7 +108,7 @@ if nargin>8 && initialize==1
end
if isfield(Parallel_info,'local_files')
- if isempty(NamFileInput),
+ if isempty(NamFileInput)
NamFileInput=Parallel_info.local_files;
else
NamFileInput=[NamFileInput;Parallel_info.local_files];
@@ -120,26 +120,26 @@ end
% in Octave!
if isoctave
- warning('off');
+ warning('off')
end
% check if there are function_handles in the input or global vars when
% octave is used
if isHybridMatlabOctave || isoctave
fInputNames = fieldnames(fInputVar);
- for j=1:length(fInputNames),
+ for j=1:length(fInputNames)
TargetVar = fInputVar.(fInputNames{j});
- if isa(TargetVar,'function_handle'),
+ if isa(TargetVar,'function_handle')
TargetVar=func2str(TargetVar);
fInputVar.(fInputNames{j})=TargetVar;
end
end
- if exist('fGlobalVar','var') && ~isempty(fGlobalVar),
+ if exist('fGlobalVar','var') && ~isempty(fGlobalVar)
fInputNames = fieldnames(fGlobalVar);
- for j=1:length(fInputNames),
+ for j=1:length(fInputNames)
TargetVar = fGlobalVar.(fInputNames{j});
- if isa(TargetVar,'function_handle'),
+ if isa(TargetVar,'function_handle')
TargetVar=func2str(TargetVar);
fGlobalVar.(fInputNames{j})=TargetVar;
end
@@ -156,7 +156,7 @@ end
DyMo=pwd;
% fInputVar.DyMo=DyMo;
-if ispc,
+if ispc
[tempo, MasterName]=system('hostname');
MasterName=deblank(MasterName);
end
@@ -170,7 +170,7 @@ switch Strategy
save([fname,'_input.mat'],'fInputVar','Parallel','-append')
case 1
- if exist('fGlobalVar','var'),
+ if exist('fGlobalVar','var')
save(['temp_input.mat'],'fInputVar','fGlobalVar')
else
save(['temp_input.mat'],'fInputVar')
@@ -184,7 +184,7 @@ end
% to run on each CPU.
[nCPU, totCPU, nBlockPerCPU, totSlaves] = distributeJobs(Parallel, fBlock, nBlock);
-for j=1:totSlaves,
+for j=1:totSlaves
PRCDirSnapshot{j}={};
end
offset0 = fBlock-1;
@@ -206,7 +206,7 @@ fid = fopen('ConcurrentCommand1.bat','w+');
% Create the directory devoted to remote computation.
-if isempty(PRCDir) && ~islocal,
+if isempty(PRCDir) && ~islocal
error('PRCDir not initialized!')
else
dynareParallelMkDir(PRCDir,Parallel(1:totSlaves));
@@ -238,7 +238,7 @@ end
% End
-for j=1:totCPU,
+for j=1:totCPU
if Strategy==1
command1 = ' ';
@@ -253,7 +253,7 @@ for j=1:totCPU,
% multithreading limit the performaces when the parallel computing is active.
- if strcmp('true',Parallel(indPC).SingleCompThread),
+ if strcmp('true',Parallel(indPC).SingleCompThread)
compThread = '-singleCompThread';
else
compThread = '';
@@ -273,13 +273,13 @@ for j=1:totCPU,
fid1=fopen(['P_',fname,'_',int2str(j),'End.txt'],'w+');
fclose(fid1);
- if Strategy==1,
+ if Strategy==1
fblck = offset+1;
nblck = sum(nBlockPerCPU(1:j));
save temp_input.mat fblck nblck fname -append;
copyfile('temp_input.mat',['slaveJob',int2str(j),'.mat']);
- if Parallel(indPC).Local ==0,
+ if Parallel(indPC).Local ==0
fid1=fopen(['stayalive',int2str(j),'.txt'],'w+');
fclose(fid1);
dynareParallelSendFiles(['stayalive',int2str(j),'.txt'],PRCDir,Parallel(indPC));
@@ -291,10 +291,10 @@ for j=1:totCPU,
newInstance = 0;
% Check if j CPU is already alive.
- if isempty(dynareParallelDir(['P_slave_',int2str(j),'End.txt'],PRCDir,Parallel(indPC)));
+ if isempty(dynareParallelDir(['P_slave_',int2str(j),'End.txt'],PRCDir,Parallel(indPC)))
fid1=fopen(['P_slave_',int2str(j),'End.txt'],'w+');
fclose(fid1);
- if Parallel(indPC).Local==0,
+ if Parallel(indPC).Local==0
dynareParallelSendFiles(['P_slave_',int2str(j),'End.txt'],PRCDir,Parallel(indPC));
delete(['P_slave_',int2str(j),'End.txt']);
end
@@ -312,7 +312,7 @@ for j=1:totCPU,
save( ['slaveParallel_input',int2str(j),'.mat'],'j');
- if Parallel(indPC).Local==0,
+ if Parallel(indPC).Local==0
dynareParallelSendFiles(['P_',fname,'_',int2str(j),'End.txt'],PRCDir,Parallel(indPC));
delete(['P_',fname,'_',int2str(j),'End.txt']);
@@ -326,7 +326,7 @@ for j=1:totCPU,
% set affinity range on win CPU's
affinity_range = [1:nthreads]+(j-1-nCPU0)*nthreads;
my_affinity = int2str(Parallel(indPC).CPUnbr(affinity_range(1)));
- for jaff=2:length(affinity_range),
+ for jaff=2:length(affinity_range)
my_affinity = [my_affinity ',' int2str(Parallel(indPC).CPUnbr(affinity_range(jaff)))];
end
% % % int2str(Parallel(indPC).CPUnbr(j-nCPU0))
@@ -337,9 +337,9 @@ for j=1:totCPU,
switch Strategy
case 0
- if Parallel(indPC).Local == 1, % 0.1 Run on the local machine (localhost).
+ if Parallel(indPC).Local == 1 % 0.1 Run on the local machine (localhost).
- if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem), % Hybrid computing Windows <-> Unix!
+ if ~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem) % Hybrid computing Windows <-> Unix!
if regexpi([Parallel(indPC).MatlabOctavePath], 'octave') % Hybrid computing Matlab(Master)->Octave(Slaves) and Vice Versa!
command1=[Parallel(indPC).MatlabOctavePath,' -f --eval "default_save_options(''-v7''); addpath(''',Parallel(indPC).DynarePath,'''), dynareroot = dynare_config(); fParallel(',int2str(offset+1),',',int2str(sum(nBlockPerCPU(1:j))),',',int2str(j),',',int2str(indPC),',''',fname,''')" &'];
else
@@ -353,16 +353,18 @@ for j=1:totCPU,
end
end
else % 0.2 Parallel(indPC).Local==0: Run using network on remote machine or also on local machine.
- if j==nCPU0+1,
+ if j==nCPU0+1
dynareParallelSendFiles([fname,'_input.mat'],PRCDir,Parallel(indPC));
dynareParallelSendFiles(NamFileInput,PRCDir,Parallel(indPC));
end
- if (~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem)), % Hybrid computing Windows <-> Unix!
- if ispc, token='start /B ';
- else token = '';
+ if (~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem)) % Hybrid computing Windows <-> Unix!
+ if ispc
+ token='start /B ';
+ else
+ token = '';
end
- if ~isempty(Parallel(indPC).Port),
+ if ~isempty(Parallel(indPC).Port)
ssh_token = ['-p ',Parallel(indPC).Port];
else
ssh_token = '';
@@ -370,7 +372,7 @@ for j=1:totCPU,
% To manage the diferences in Unix/Windows OS syntax.
remoteFile=['remoteDynare',int2str(j)];
fidRemote=fopen([remoteFile,'.m'],'w+');
- if regexpi([Parallel(indPC).MatlabOctavePath], 'octave'),% Hybrid computing Matlab(Master)->Octave(Slaves) and Vice Versa!
+ if regexpi([Parallel(indPC).MatlabOctavePath], 'octave') % Hybrid computing Matlab(Master)->Octave(Slaves) and Vice Versa!
remoteString=['default_save_options(''-v7''); addpath(''',Parallel(indPC).DynarePath,'''), dynareroot = dynare_config(); fParallel(',int2str(offset+1),',',int2str(sum(nBlockPerCPU(1:j))),',',int2str(j),',',int2str(indPC),',''',fname,''')'];
command1=[token, 'ssh ',ssh_token,' ',Parallel(indPC).UserName,'@',Parallel(indPC).ComputerName,' "cd ',Parallel(indPC).RemoteDirectory,'/',PRCDir, '; ',Parallel(indPC).MatlabOctavePath,' -f --eval ',remoteFile,' " &'];
else
@@ -382,7 +384,7 @@ for j=1:totCPU,
dynareParallelSendFiles([remoteFile,'.m'],PRCDir,Parallel(indPC));
delete([remoteFile,'.m']);
else
- if ~strcmpi(Parallel(indPC).ComputerName,MasterName), % 0.3 Run on a remote machine!
+ if ~strcmpi(Parallel(indPC).ComputerName,MasterName) % 0.3 Run on a remote machine!
% Hybrid computing Matlab(Master)-> Octave(Slaves) and Vice Versa!
if regexpi([Parallel(indPC).MatlabOctavePath], 'octave')
command1=['psexec \\',Parallel(indPC).ComputerName,' -d -e -u ',Parallel(indPC).UserName,' -p ',Parallel(indPC).Password,' -W "',Parallel(indPC).RemoteDrive,':\',Parallel(indPC).RemoteDirectory,'\',PRCDir,'\" -a ',my_affinity, ...
@@ -407,8 +409,8 @@ for j=1:totCPU,
case 1
- if Parallel(indPC).Local == 1 && newInstance, % 1.1 Run on the local machine.
- if (~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem)), % Hybrid computing Windows <-> Unix!
+ if Parallel(indPC).Local == 1 && newInstance % 1.1 Run on the local machine.
+ if (~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem)) % Hybrid computing Windows <-> Unix!
if regexpi([Parallel(indPC).MatlabOctavePath], 'octave') % Hybrid computing Matlab(Master)-> Octave(Slaves) and Vice Versa!
command1=[Parallel(indPC).MatlabOctavePath,' -f --eval "default_save_options(''-v7''); addpath(''',Parallel(indPC).DynarePath,'''), dynareroot = dynare_config(); slaveParallel(',int2str(j),',',int2str(indPC),')" &'];
else
@@ -421,21 +423,23 @@ for j=1:totCPU,
command1=['psexec -d -W "',DyMo, '" -a ',my_affinity,' -low ',Parallel(indPC).MatlabOctavePath,' -nosplash -nodesktop -minimize ',compThread,' -r "addpath(''',Parallel(indPC).DynarePath,'''), dynareroot = dynare_config(); slaveParallel(',int2str(j),',',int2str(indPC),')"'];
end
end
- elseif Parallel(indPC).Local==0, % 1.2 Run using network on remote machine or also on local machine.
- if j==nCPU0+1,
+ elseif Parallel(indPC).Local==0 % 1.2 Run using network on remote machine or also on local machine.
+ if j==nCPU0+1
dynareParallelSendFiles(NamFileInput,PRCDir,Parallel(indPC));
end
dynareParallelSendFiles(['P_',fname,'_',int2str(j),'End.txt'],PRCDir,Parallel(indPC));
delete(['P_',fname,'_',int2str(j),'End.txt']);
- if newInstance,
+ if newInstance
dynareParallelSendFiles(['slaveJob',int2str(j),'.mat'],PRCDir,Parallel(indPC));
delete(['slaveJob',int2str(j),'.mat']);
dynareParallelSendFiles(['slaveParallel_input',int2str(j),'.mat'],PRCDir,Parallel(indPC))
- if (~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem)), % Hybrid computing Windows <-> Unix!
- if ispc, token='start /B ';
- else token = '';
+ if (~ispc || strcmpi('unix',Parallel(indPC).OperatingSystem)) % Hybrid computing Windows <-> Unix!
+ if ispc
+ token='start /B ';
+ else
+ token = '';
end
- if ~isempty(Parallel(indPC).Port),
+ if ~isempty(Parallel(indPC).Port)
ssh_token = ['-p ',Parallel(indPC).Port];
else
ssh_token = '';
@@ -455,7 +459,7 @@ for j=1:totCPU,
dynareParallelSendFiles([remoteFile,'.m'],PRCDir,Parallel(indPC));
delete([remoteFile,'.m']);
else
- if ~strcmpi(Parallel(indPC).ComputerName,MasterName), % 1.3 Run on a remote machine.
+ if ~strcmpi(Parallel(indPC).ComputerName,MasterName) % 1.3 Run on a remote machine.
% Hybrid computing Matlab(Master)->Octave(Slaves) and Vice Versa!
if regexpi([Parallel(indPC).MatlabOctavePath], 'octave')
command1=['psexec \\',Parallel(indPC).ComputerName,' -d -e -u ',Parallel(indPC).UserName,' -p ',Parallel(indPC).Password,' -W "',Parallel(indPC).RemoteDrive,':\',Parallel(indPC).RemoteDirectory,'\',PRCDir,'\" -a ',my_affinity, ...
@@ -480,7 +484,7 @@ for j=1:totCPU,
% do PRCDirSnapshot here to to avoid problems of
% synchronization.
- if isempty(PRCDirSnapshot{indPC}),
+ if isempty(PRCDirSnapshot{indPC})
PRCDirSnapshot(indPC)=dynareParallelSnapshot(PRCDir,Parallel(indPC));
PRCDirSnapshotInit(indPC) = PRCDirSnapshot(indPC);
else
@@ -511,12 +515,12 @@ end
% the slaves ...
% If the compuation is 'Local' it is not necessary to do it ...
-if Strategy==0 || newInstance, % See above.
+if Strategy==0 || newInstance % See above.
PRCDirSnapshot=dynareParallelSnapshot(PRCDir,Parallel(1:totSlaves));
PRCDirSnapshotInit = PRCDirSnapshot;
% Run the slaves.
- if ~ispc,
+ if ~ispc
system('sh ConcurrentCommand1.bat &');
pause(1)
else
@@ -569,7 +573,7 @@ else
set(hstatus(1),'Units','normalized'),
vspace = max(0.1,1/totCPU);
vstart = 1-vspace+0.2*vspace;
- for j=1:totCPU,
+ for j=1:totCPU
jrow = mod(j-1,10)+1;
jcol = ceil(j/10);
hstatus(j) = axes('position',[0.05/ncol+(jcol-1)/ncol vstart-vspace*(jrow-1) 0.9/ncol 0.3*vspace], ...
@@ -615,7 +619,7 @@ if options_.console_mode || isoctave
end
for i=1:L
- if fnameTemp(i)=='_';
+ if fnameTemp(i)=='_'
fnameTemp(i)=' ';
end
end
@@ -657,18 +661,18 @@ while (ForEver)
pause(1)
try
- if islocal ==0,
+ if islocal ==0
dynareParallelGetFiles(['comp_status_',fname,'*.mat'],PRCDir,Parallel(1:totSlaves));
end
catch
end
- for j=1:totCPU,
+ for j=1:totCPU
try
if ~isempty(['comp_status_',fname,int2str(j),'.mat'])
load(['comp_status_',fname,int2str(j),'.mat']);
% whoCloseAllSlaves = who(['comp_status_',fname,int2str(j),'.mat','CloseAllSlaves']);
- if exist('CloseAllSlaves') && flag_CloseAllSlaves==0,
+ if exist('CloseAllSlaves') && flag_CloseAllSlaves==0
flag_CloseAllSlaves=1;
whoiamCloseAllSlaves=j;
closeSlave(Parallel(1:totSlaves),PRCDir,1);
@@ -706,7 +710,7 @@ while (ForEver)
end
end
else
- for j=1:totCPU,
+ for j=1:totCPU
try
set(hpat(j),'XData',[0 0 pcerdone(j) pcerdone(j)]);
set(htit(j),'String',[status_Title{j},' - ',status_String{j}]);
@@ -729,9 +733,9 @@ while (ForEver)
PRCDirSnapshot=dynareParallelGetNewFiles(PRCDir,Parallel(1:totSlaves),PRCDirSnapshot);
end
- if isempty(dynareParallelDir(['P_',fname,'_*End.txt'],PRCDir,Parallel(1:totSlaves)));
+ if isempty(dynareParallelDir(['P_',fname,'_*End.txt'],PRCDir,Parallel(1:totSlaves)))
HoTuttiGliOutput=0;
- for j=1:totCPU,
+ for j=1:totCPU
% Checking if the remote computation is finished and if we copied all the output here.
if ~isempty(dir([fname,'_output_',int2str(j),'.mat']))
@@ -742,7 +746,7 @@ while (ForEver)
end
end
- if HoTuttiGliOutput==totCPU,
+ if HoTuttiGliOutput==totCPU
mydelete(['comp_status_',fname,'*.mat']);
if isoctave || options_.console_mode
if isoctave
@@ -754,7 +758,7 @@ while (ForEver)
end
diary on;
else
- close(hfigstatus),
+ close(hfigstatus)
end
break
@@ -770,19 +774,19 @@ end
iscrash = 0;
PRCDirSnapshot=dynareParallelGetNewFiles(PRCDir,Parallel(1:totSlaves),PRCDirSnapshot);
-for j=1:totCPU,
+for j=1:totCPU
indPC=min(find(nCPU>=j));
load([fname,'_output_',int2str(j),'.mat'],'fOutputVar');
delete([fname,'_output_',int2str(j),'.mat']);
- if isfield(fOutputVar,'OutputFileName') && Parallel(indPC).Local==0,
+ if isfield(fOutputVar,'OutputFileName') && Parallel(indPC).Local==0
% Check if input files have been updated!
OutputFileName=fOutputVar.OutputFileName;
tmp0='';
- for i=1:size(NamFileInput,1),
+ for i=1:size(NamFileInput,1)
FileList = regexp(strrep(PRCDirSnapshot{indPC},'\','/'),strrep(strrep([NamFileInput{i,:}],'\','/'),'*','(\w*)'),'match');
- for k=1:length(FileList),
- if ~isempty(FileList{k}),
- if isempty(tmp0),
+ for k=1:length(FileList)
+ if ~isempty(FileList{k})
+ if isempty(tmp0)
tmp0=FileList{k}{1};
else
tmp0=char(tmp0,FileList{k}{1});
@@ -790,74 +794,74 @@ for j=1:totCPU,
end
end
end
- for i=1:size(OutputFileName,1),
+ for i=1:size(OutputFileName,1)
tmp1='';
FileList = regexp(cellstr(tmp0),strrep(strrep([OutputFileName{i,:}],'\','/'),'*','(\w*)'),'match');
FileList0 = regexp(cellstr(tmp0),strrep([OutputFileName{i,2}],'*','(\w*)'),'match');
- for k=1:length(FileList),
- if ~isempty(FileList{k}),
- if isempty(tmp1),
+ for k=1:length(FileList)
+ if ~isempty(FileList{k})
+ if isempty(tmp1)
tmp1=FileList0{k}{1};
else
tmp1=char(tmp1,FileList0{k}{1});
end
end
end
- for k=1:size(tmp1,1),
+ for k=1:size(tmp1,1)
dynareParallelGetFiles([OutputFileName(i,1) {tmp1(k,:)}],PRCDir,Parallel(indPC));
end
end
% check if some output file is missing!
- for i=1:size(OutputFileName,1),
+ for i=1:size(OutputFileName,1)
tmp1=dynareParallelDir([OutputFileName{i,:}],PRCDir,Parallel(indPC));
tmp1 = regexp(cellstr(tmp1),strrep([OutputFileName{i,2}],'*','(\w*)'),'match');
tmp1 = char(tmp1{:});
tmp2=ls([OutputFileName{i,:}]);
- for ij=1:size(tmp1,1),
+ for ij=1:size(tmp1,1)
icheck = regexp(cellstr(tmp2),tmp1(ij,:),'once');
isOutputFileMissing=1;
- for ik=1:size(tmp2,1),
- if ~isempty(icheck{ik}),
+ for ik=1:size(tmp2,1)
+ if ~isempty(icheck{ik})
isOutputFileMissing=0;
end
end
- if isOutputFileMissing,
+ if isOutputFileMissing
dynareParallelGetFiles([OutputFileName(i,1) {tmp1(ij,:)}],PRCDir,Parallel(indPC));
end
end
end
end
- if isfield(fOutputVar,'error'),
+ if isfield(fOutputVar,'error')
disp(['Job number ',int2str(j),' crashed with error:']);
iscrash=1;
disp([fOutputVar.error.message]);
for jstack=1:length(fOutputVar.error.stack)
- fOutputVar.error.stack(jstack),
+ fOutputVar.error.stack(jstack)
end
- elseif flag_CloseAllSlaves==0,
+ elseif flag_CloseAllSlaves==0
fOutVar(j)=fOutputVar;
- elseif j==whoiamCloseAllSlaves,
+ elseif j==whoiamCloseAllSlaves
fOutVar=fOutputVar;
end
end
-if flag_CloseAllSlaves==1,
+if flag_CloseAllSlaves==1
closeSlave(Parallel(1:totSlaves),PRCDir,-1);
end
-if iscrash,
+if iscrash
error('Remote jobs crashed');
end
-pause(1), % Wait for all remote diary off completed
+pause(1) % Wait for all remote diary off completed
% Cleanup.
dynareParallelGetFiles('*.log',PRCDir,Parallel(1:totSlaves));
switch Strategy
case 0
- for indPC=1:min(find(nCPU>=totCPU)),
+ for indPC=1:min(find(nCPU>=totCPU))
if Parallel(indPC).Local == 0
dynareParallelRmDir(PRCDir,Parallel(indPC));
end
@@ -879,21 +883,21 @@ switch Strategy
delete ConcurrentCommand1.bat
case 1
delete(['temp_input.mat'])
- if newInstance,
+ if newInstance
if isempty(dir('dynareParallelLogFiles'))
[A B C]=rmdir('dynareParallelLogFiles');
mkdir('dynareParallelLogFiles');
end
end
copyfile('*.log','dynareParallelLogFiles');
- if newInstance,
+ if newInstance
delete ConcurrentCommand1.bat
end
dynareParallelDelete(['comp_status_',fname,'*.mat'],PRCDir,Parallel);
- for indPC=1:min(find(nCPU>=totCPU)),
- if Parallel(indPC).Local == 0,
+ for indPC=1:min(find(nCPU>=totCPU))
+ if Parallel(indPC).Local == 0
dynareParallelDeleteNewFiles(PRCDir,Parallel(indPC),PRCDirSnapshotInit(indPC),'.log');
- for ifil=1:size(NamFileInput,1),
+ for ifil=1:size(NamFileInput,1)
dynareParallelDelete([NamFileInput{ifil,:}],PRCDir,Parallel(indPC));
end
end
diff --git a/matlab/parallel/slaveParallel.m b/matlab/parallel/slaveParallel.m
index d7275a4fd..6b4acdce4 100644
--- a/matlab/parallel/slaveParallel.m
+++ b/matlab/parallel/slaveParallel.m
@@ -48,9 +48,9 @@ dynareroot = dynare_config();
load( ['slaveParallel_input',int2str(whoiam)]);
%Loads fGlobalVar Parallel.
-if exist('fGlobalVar'),
+if exist('fGlobalVar')
globalVars = fieldnames(fGlobalVar);
- for j=1:length(globalVars),
+ for j=1:length(globalVars)
eval(['global ',globalVars{j},';']);
evalin('base',['global ',globalVars{j},';']);
end
@@ -65,17 +65,17 @@ end
t0=clock;
fslave = dir( ['slaveParallel_input',int2str(whoiam),'.mat']);
-while (etime(clock,t0)<1200 && ~isempty(fslave)) || ~isempty(dir(['stayalive',int2str(whoiam),'.txt'])),
- if ~isempty(dir(['stayalive',int2str(whoiam),'.txt'])),
+while (etime(clock,t0)<1200 && ~isempty(fslave)) || ~isempty(dir(['stayalive',int2str(whoiam),'.txt']))
+ if ~isempty(dir(['stayalive',int2str(whoiam),'.txt']))
t0=clock;
delete(['stayalive',int2str(whoiam),'.txt']);
end
% I wait for 20 min or while mater asks to exit (i.e. it cancels fslave file)
- pause(1);
+ pause(1)
fjob = dir(['slaveJob',int2str(whoiam),'.mat']);
- if ~isempty(fjob),
+ if ~isempty(fjob)
clear fGlobalVar fInputVar fblck nblck fname
while(1)
@@ -85,7 +85,7 @@ while (etime(clock,t0)<1200 && ~isempty(fslave)) || ~isempty(dir(['stayalive',in
if Go>0
fclose(Go);
- pause(1);
+ pause(1)
load(['slaveJob',int2str(whoiam),'.mat']);
break
else
@@ -106,9 +106,9 @@ while (etime(clock,t0)<1200 && ~isempty(fslave)) || ~isempty(dir(['stayalive',in
if exist('fGlobalVar') && ~isempty (fGlobalVar)
globalVars = fieldnames(fGlobalVar);
- for j=1:length(globalVars),
+ for j=1:length(globalVars)
info_whos = whos(globalVars{j});
- if isempty(info_whos) || ~info_whos.global,
+ if isempty(info_whos) || ~info_whos.global
eval(['global ',globalVars{j},';']);
evalin('base',['global ',globalVars{j},';']);
end
@@ -122,11 +122,11 @@ while (etime(clock,t0)<1200 && ~isempty(fslave)) || ~isempty(dir(['stayalive',in
fInputVar.Parallel = Parallel;
% Launch the routine to be run in parallel.
- try,
- tic,
+ try
+ tic
fOutputVar = feval(fname, fInputVar ,fblck, nblck, whoiam, ThisMatlab);
- toc,
- if isfield(fOutputVar,'OutputFileName'),
+ toc
+ if isfield(fOutputVar,'OutputFileName')
OutputFileName = fOutputVar.OutputFileName;
else
OutputFileName = '';
@@ -137,7 +137,7 @@ while (etime(clock,t0)<1200 && ~isempty(fslave)) || ~isempty(dir(['stayalive',in
% Save the output result.
save([ fname,'_output_',int2str(whoiam),'.mat'],'fOutputVar' );
% keyboard,
- if isfield(fOutputVar,'CloseAllSlaves'),
+ if isfield(fOutputVar,'CloseAllSlaves')
CloseAllSlaves = 1;
fOutputVar = rmfield(fOutputVar,'CloseAllSlaves');
save([ fname,'_output_',int2str(whoiam),'.mat'],'fOutputVar' )
@@ -150,7 +150,7 @@ while (etime(clock,t0)<1200 && ~isempty(fslave)) || ~isempty(dir(['stayalive',in
disp(['Job ',fname,' on CPU ',int2str(whoiam),' completed.']);
t0 =clock; % Re-set waiting time of 20 mins
- catch,
+ catch
theerror = lasterror;
if strfind(theerror.message,'Master asked to break the job')
disp(['Job ',fname,' on CPU ',int2str(whoiam),' broken from master.']);
@@ -162,7 +162,7 @@ while (etime(clock,t0)<1200 && ~isempty(fslave)) || ~isempty(dir(['stayalive',in
fOutputVar.error = lasterror;
save([ fname,'_output_',int2str(whoiam),'.mat'],'fOutputVar' );
waitbarString = fOutputVar.error.message;
- if Parallel(ThisMatlab).Local,
+ if Parallel(ThisMatlab).Local
waitbarTitle='Local ';
else
waitbarTitle=[Parallel(ThisMatlab).ComputerName];
diff --git a/matlab/parallel/storeGlobalVars.m b/matlab/parallel/storeGlobalVars.m
index cd0470c37..ce80ec189 100644
--- a/matlab/parallel/storeGlobalVars.m
+++ b/matlab/parallel/storeGlobalVars.m
@@ -32,12 +32,12 @@ function storeGlobalVars(fname,append)
GlobalNames = who('global');
% varlist = '';
-for j=1:length(GlobalNames);
+for j=1:length(GlobalNames)
eval(['global ',GlobalNames{j},';']);
eval(['fGlobalVar.',GlobalNames{j},'=',GlobalNames{j},';']);
end
-if nargin<2,
+if nargin<2
save(fname,'fGlobalVar');
else
save(fname,'fGlobalVar','-append');
diff --git a/matlab/parallel/struct2local.m b/matlab/parallel/struct2local.m
index fbe9666f0..e77fa2274 100644
--- a/matlab/parallel/struct2local.m
+++ b/matlab/parallel/struct2local.m
@@ -30,6 +30,6 @@ function struct2local(S)
vnam = fieldnames(S);
-for j=1:length(vnam),
+for j=1:length(vnam)
assignin('caller',vnam{j},getfield(S,vnam{j}));
end
diff --git a/matlab/partial_information/PCL_Part_info_irf.m b/matlab/partial_information/PCL_Part_info_irf.m
index 2fc0ff1d8..31162930c 100644
--- a/matlab/partial_information/PCL_Part_info_irf.m
+++ b/matlab/partial_information/PCL_Part_info_irf.m
@@ -132,7 +132,7 @@ stderr=diag(M_.Sigma_e^0.5);
irfmat=zeros(size(dr.PI_TT1 ,1),irfpers+1);
irfst=zeros(size(GG,1),irfpers+1);
irfst(:,1)=stderr(ii)*imp(:,ii);
-for jj=2:irfpers+1;
+for jj=2:irfpers+1
irfst(:,jj)=GG*irfst(:,jj-1);
irfmat(:,jj-1)=VV*irfst(NX+1:ss-FL_RANK,jj);
end
diff --git a/matlab/partial_information/PCL_Part_info_moments.m b/matlab/partial_information/PCL_Part_info_moments.m
index fdebe317f..d81a2bfe1 100644
--- a/matlab/partial_information/PCL_Part_info_moments.m
+++ b/matlab/partial_information/PCL_Part_info_moments.m
@@ -48,7 +48,7 @@ LL = sparse(1:NOBS,OBS,ones(NOBS,1),NY,NY);
if exist( 'irfpers')==1
if ~isempty(irfpers)
- if irfpers<=0, irfpers=20, end;
+ if irfpers<=0, irfpers=20, end
else
irfpers=20;
end
@@ -170,7 +170,7 @@ ar = options_.ar;
if ar > 0
COV_YRk= zeros(nn,ar);
AutoCOR_YRk= zeros(nn,ar);
- for k=1:ar;
+ for k=1:ar
COV_P=GAM*COV_P;
COV_OMEGA= COV_P( end-nn+1:end, end-nn+1:end);
COV_YRk = VV*COV_OMEGA*VV';
diff --git a/matlab/partial_information/PI_gensys.m b/matlab/partial_information/PI_gensys.m
index c46d45d07..eb8ba6a94 100644
--- a/matlab/partial_information/PI_gensys.m
+++ b/matlab/partial_information/PI_gensys.m
@@ -96,7 +96,7 @@ try
else
warning('PI_gensys: Evading inversion of zero matrix UAVinv=inv(U02''*a1*V02)!');
eu=[0,0];
- return;
+ return
end
end
catch
@@ -171,7 +171,7 @@ if(options_.ACES_solver==1)
zeros(num_inst,size(E3,2)), II;
];
eu =[1; 1], nmat=[], gev=[];
- return; % do not check B&K compliancy
+ return % do not check B&K compliancy
end
G0pi=eye(n+FL_RANK+NX);
diff --git a/matlab/partial_information/PI_gensys_singularC.m b/matlab/partial_information/PI_gensys_singularC.m
index 5dc26ec63..426a05d6a 100644
--- a/matlab/partial_information/PI_gensys_singularC.m
+++ b/matlab/partial_information/PI_gensys_singularC.m
@@ -86,7 +86,4 @@ catch
[errmsg, errcode]=lasterr;
warning(['error callig PI_gensys_singularC: ' errmsg ],'errcode');
error('errcode',['error callig PI_gensys_singularC: ' errmsg ]);
-end
-
-return;
-
+end
\ No newline at end of file
diff --git a/matlab/partial_information/add_auxiliary_variables_to_steadystate.m b/matlab/partial_information/add_auxiliary_variables_to_steadystate.m
index d99e36ebb..3524dae18 100644
--- a/matlab/partial_information/add_auxiliary_variables_to_steadystate.m
+++ b/matlab/partial_information/add_auxiliary_variables_to_steadystate.m
@@ -21,7 +21,7 @@ function ys1 = add_auxiliary_variables_to_steadystate(ys,aux_vars,fname, ...
n = length(aux_vars);
ys1 = [ys;zeros(n,1)];
-for i=1:n+1;
+for i=1:n+1
if byte_code
[info, res] = bytecode('static','evaluate',ys1,...
[exo_steady_state; ...
@@ -30,7 +30,7 @@ for i=1:n+1;
res = feval([fname '_static'],ys1,...
[exo_steady_state; ...
exo_det_steady_state],params);
- end;
+ end
for j=1:n
el = aux_vars(j).endo_index;
ys1(el) = ys1(el)-res(el);
diff --git a/matlab/partial_information/dr1_PI.m b/matlab/partial_information/dr1_PI.m
index 0475d4bef..2fca86272 100644
--- a/matlab/partial_information/dr1_PI.m
+++ b/matlab/partial_information/dr1_PI.m
@@ -451,6 +451,4 @@ end % end if useAIM and...
% TODO:
% if options_.loglinear == 1
- % if exogenous deterministic variables
-
- return;
+ % if exogenous deterministic variables
\ No newline at end of file
diff --git a/matlab/perfect-foresight-models/det_cond_forecast.m b/matlab/perfect-foresight-models/det_cond_forecast.m
index 38d72d345..4b143f3f5 100644
--- a/matlab/perfect-foresight-models/det_cond_forecast.m
+++ b/matlab/perfect-foresight-models/det_cond_forecast.m
@@ -35,7 +35,7 @@ initial_conditions = oo_.steady_state;
verbosity = options_.verbosity;
if options_.periods == 0
options_.periods = 25;
-end;
+end
%We have to get an initial guess for the conditional forecast
% and terminal conditions for the non-stationary variables, we
% use the first order approximation of the rational expectation solution.
@@ -64,7 +64,7 @@ if length(varargin) > 3
nvars = length(constrained_vars);
for i = 1:max_periods_simulation
constraint_index{i} = 1:nvars;
- end;
+ end
direct_mode = 0;
shocks_present = 0;
controlled_varexo = options_cond_fcst.controlled_varexo;
@@ -193,24 +193,24 @@ else
end
end
data_set = merge(dset(dset.dates(1):(plan.date(1)-1)), data_set);
- return;
+ return
union_names = union(data_set.name, dset.name);
dif = setdiff(union_names, data_set.name);
data_set_nobs = data_set.nobs;
for i = 1:length(dif)
data_set{dif{i}} = dseries(nan(data_set_nobs,1),plan.date(1), dif(i), dif(i));
- end;
+ end
dif = setdiff(union_names, dset.name);
dset_nobs = dset.nobs;
for i = 1:length(dif)
dset{dif{i}} = dseries(nan(dset_nobs,1),dset.dates(1), dif(i), dif(i));
- end;
+ end
data_set = [dset(dset.dates(1):(plan.date(1)-1)) ; data_set];
- return;
- end;
+ return
+ end
else
error('impossible case');
- end;
+ end
else
oo_.exo_simul = repmat(oo_.exo_steady_state',options_.periods+2,1);
@@ -235,7 +235,7 @@ else
total_periods = plan.date;
-end;
+end
if ~isfield(options_cond_fcst,'periods') || isempty(options_cond_fcst.periods)
options_cond_fcst.periods = 100;
@@ -260,7 +260,7 @@ if direct_mode == 1
else
init_periods = period_i;
tp_end = period_i;
- end;
+ end
tp0 = tp;
while tp < init_periods
tp = tp + 1;
@@ -271,18 +271,18 @@ if direct_mode == 1
constrained_paths(i, tp - tp0 + 1) = constrained_paths_cell{i}(j + 1);
tp = tp + 1;
j = j + 1;
- end;
+ end
if tp - tp0 > max_periods_simulation
max_periods_simulation = tp - tp0;
- end;
+ end
end
n_nnz = length(sum(is_constraint,2));
if n_nnz > 0
constraint_index = cell(n_nnz,1);
for i= 1:n_nnz
constraint_index{i} = find(is_constraint(i,:));
- end;
- end;
+ end
+ end
if shocks_present
n_periods = length(shock_periods);
shock_paths_cell = shock_paths;
@@ -299,7 +299,7 @@ if direct_mode == 1
else
init_periods = period_i;
tp_end = period_i;
- end;
+ end
tp0 = tp;
while tp < init_periods
tp = tp + 1;
@@ -310,17 +310,17 @@ if direct_mode == 1
shock_paths(i, tp - tp0 + 1) = shock_paths_cell{i}(j + 1);
tp = tp + 1;
j = j + 1;
- end;
+ end
if tp - tp0 > max_periods_simulation
max_periods_simulation = tp - tp0;
- end;
- end;
+ end
+ end
n_nnz = length(sum(is_shock,2));
if n_nnz > 0
shock_index = cell(n_nnz, 1);
for i= 1:n_nnz
shock_index{i} = find(is_shock(i,:));
- end;
+ end
end
end
else
@@ -342,10 +342,10 @@ if isfield(options_cond_fcst,'controlled_varexo')
n_control_exo = size(options_cond_fcst.controlled_varexo, 1);
if n_control_exo ~= n_endo_constrained
error(['det_cond_forecast: the number of exogenous controlled variables (' int2str(n_control_exo) ') has to be equal to the number of constrained endogenous variabes (' int2str(n_endo_constrained) ')'])
- end;
+ end
else
error('det_cond_forecast: to run a deterministic conditional forecast you have to specified the exogenous variables controlled using the option controlled_varexo in forecast command');
-end;
+end
% if n_endo_constrained == 0
% options_.ep.use_bytecode = options_.bytecode;
@@ -377,14 +377,14 @@ if isempty(indx_endo_solve_pf)
pf = 0;
else
pf = length(indx_endo_solve_pf);
-end;
+end
indx_endo_solve_surprise = setdiff(constrained_vars, indx_endo_solve_pf);
if isempty(indx_endo_solve_surprise)
surprise = 0;
else
surprise = length(indx_endo_solve_surprise);
-end;
+end
eps = options_.solve_tolf;
@@ -414,7 +414,7 @@ if pf && ~surprise
for j = 1:length(constrained_vars)
indx_endo(col_count : col_count + constrained_periods - 1) = constrained_vars(j) + (time_index_constraint - 1) * ny;
col_count = col_count + constrained_periods;
- end;
+ end
oo_=make_ex_(M_,options_,oo_);
oo_=make_y_(M_,options_,oo_);
it = 1;
@@ -436,9 +436,9 @@ if pf && ~surprise
y = oo_.endo_simul(constrained_vars(j), time_index_constraint);
r(col_count:col_count+constrained_periods - 1) = (y - constrained_paths(j,1:constrained_periods))';
col_count = col_count + constrained_periods;
- end;
+ end
normr = norm(r, 1);
- end;
+ end
if (~oo_.deterministic_simulation.status || ~result || normr > normra) && it > 1
not_achieved = 1;
alpha = alpha / 2;
@@ -446,13 +446,13 @@ if pf && ~surprise
for j = controlled_varexo'
oo_.exo_simul(time_index_constraint,j) = (old_exo(:,j) + alpha * D_exo(col_count: (col_count + constrained_periods - 1)));
col_count = col_count + constrained_periods;
- end;
+ end
disp(['Divergence in Newton: reducing the path length alpha=' num2str(alpha)]);
oo_.endo_simul = repmat(oo_.steady_state, 1, options_cond_fcst.periods + 2);
else
not_achieved = 0;
- end;
- end;
+ end
+ end
per = 30;
z = oo_.endo_simul(:, 1 : per + 2 );
@@ -473,7 +473,7 @@ if pf && ~surprise
else
data1 = M_;
Size = 1;
- end;
+ end
data1 = M_;
if (options_.bytecode)
[chck, zz, data1]= bytecode('dynamic','evaluate', z, zx, M_.params, oo_.steady_state, k, data1);
@@ -482,16 +482,16 @@ if pf && ~surprise
data1.g1_x = g1b(:,end - M_.exo_nbr + 1:end);
data1.g1 = g1b(:,1 : end - M_.exo_nbr);
chck = 0;
- end;
+ end
mexErrCheck('bytecode', chck);
- end;
+ end
if k == 1
g1(1:M_.endo_nbr,-M_.endo_nbr + [cur_indx lead_indx]) = data1.g1(:,M_.nspred + 1:end);
elseif k == per
g1(M_.endo_nbr * (k - 1) + 1 :M_.endo_nbr * k,M_.endo_nbr * (k -2) + [lag_indx cur_indx]) = data1.g1(:,1:M_.nspred + M_.endo_nbr);
else
g1(M_.endo_nbr * (k - 1) + 1 :M_.endo_nbr * k, M_.endo_nbr * (k -2) + [lag_indx cur_indx lead_indx]) = data1.g1;
- end;
+ end
l2 = 1;
pf_c = 1;
if k <= constrained_periods
@@ -504,16 +504,16 @@ if pf && ~surprise
for ii = 2:constrained_periods
indx_x(l2) = length(controlled_varexo) + pf * (ii - 2) + constraint_index{k + ii - 1}(pf_c);
l2 = l2 + 1;
- end;
+ end
pf_c = pf_c + 1;
cum_index_d_y_x = [cum_index_d_y_x; constrained_vars(l)];
else
cum_index_d_y_x = [cum_index_d_y_x; constrained_vars(l) + (k - 1) * M_.endo_nbr];
end
cum_l1 = cum_l1 + length(l1);
- end;
- end;
- end;
+ end
+ end
+ end
d_y_x = - g1 \ g1_x;
@@ -533,7 +533,7 @@ if pf && ~surprise
cum_l1 = cum_l1 + length(l1);
end
cum_l1 = cum_l1 + length(constrained_vars(j1));
- end;
+ end
% col_count = 1;
@@ -545,8 +545,8 @@ if pf && ~surprise
% J1(:,col_count) = (oo_.endo_simul(indx_endo) - ys) / eps1;
% oo_.exo_simul(time,j) = saved;
% col_count = col_count + 1;
-% end;
-% end;
+% end
+% end
% J1
% sdfmlksdf;
@@ -564,11 +564,11 @@ if pf && ~surprise
for j = controlled_varexo'
oo_.exo_simul(time_index_constraint,j) = oo_.exo_simul(time_index_constraint,j) + D_exo(col_count: (col_count + constrained_periods - 1));
col_count = col_count + constrained_periods - 1;
- end;
- end;
+ end
+ end
it = it + 1;
normra = normr;
- end;
+ end
endo = oo_.endo_simul';
exo = oo_.exo_simul;
else
@@ -581,7 +581,7 @@ else
pf = 0;
else
pf = length(indx_endo_solve_pf);
- end;
+ end
[pos_constrained_surprise, junk] = find((1-constrained_perfect_foresight) .* is_constraint(t, :)');
indx_endo_solve_surprise = constrained_vars(pos_constrained_surprise);
@@ -590,8 +590,8 @@ else
surprise = 0;
else
surprise = length(indx_endo_solve_surprise);
- end;
- end;
+ end
+ end
if direct_mode && ~isempty(is_shock)
[pos_shock_pf, junk] = find(shock_perfect_foresight .* is_shock(t, :)');
@@ -600,7 +600,7 @@ else
b_pf = 0;
else
b_pf = length(indx_endo_solve_pf);
- end;
+ end
[pos_shock_surprise, junk] = find((1-shock_perfect_foresight) .* is_shock(t, :)');
indx_endo_solve_surprise = shock_vars(pos_shock_surprise);
@@ -609,8 +609,8 @@ else
b_surprise = 0;
else
b_surprise = length(indx_endo_solve_surprise);
- end;
- end;
+ end
+ end
disp('===============================================================================================');
disp(['t=' int2str(t) ' conditional (surprise=' int2str(surprise) ' perfect foresight=' int2str(pf) ') unconditional (surprise=' int2str(b_surprise) ' perfect foresight=' int2str(b_pf) ')']);
@@ -623,7 +623,7 @@ else
exo_init = zeros(size(oo_.exo_simul));
end
oo_=make_y_(M_,options_,oo_);
- end;
+ end
%exo_init
oo_.exo_simul = exo_init;
oo_.endo_simul(:,1) = initial_conditions;
@@ -668,8 +668,8 @@ else
else
indx_endo(col_count) = constrained_vars(j) + maximum_lag * ny;
col_count = col_count + 1;
- end;
- end;
+ end
+ end
r = zeros(second_system_size,1);
@@ -696,17 +696,17 @@ else
else
oo_.exo_simul(maximum_lag + 1,j) = old_exo(maximum_lag + 1,j) + alpha * D_exo(col_count);
col_count = col_count + 1;
- end;
- end;
+ end
+ end
disp(['Divergence in Newton: reducing the path length alpha=' num2str(alpha) ' result=' num2str(result) ' sum(sum)=' num2str(sum(sum(isfinite(oo_.endo_simul(:,time_index_constraint))))) ' ny * length(time_index_constraint)=' num2str(ny * length(time_index_constraint)) ' oo_.deterministic_simulation.status=' num2str(oo_.deterministic_simulation.status)]);
oo_.endo_simul = [initial_conditions repmat(oo_.steady_state, 1, options_cond_fcst.periods + 1)];
else
not_achieved = 0;
- end;
- end;
+ end
+ end
if t==constrained_periods
ycc = oo_.endo_simul;
- end;
+ end
yc = oo_.endo_simul(:,maximum_lag + 1);
ys = oo_.endo_simul(indx_endo);
@@ -720,7 +720,7 @@ else
y = yc(constrained_vars(j));
r(col_count) = y - constrained_paths(j,t);
col_count = col_count + 1;
- end;
+ end
end
disp('computation of derivatives w.r. to exogenous shocks');
@@ -745,7 +745,7 @@ else
else
data1 = M_;
Size = 1;
- end;
+ end
data1 = M_;
if (options_.bytecode)
[chck, zz, data1]= bytecode('dynamic','evaluate', z, zx, M_.params, oo_.steady_state, k, data1);
@@ -754,16 +754,16 @@ else
data1.g1_x = g1b(:,end - M_.exo_nbr + 1:end);
data1.g1 = g1b(:,1 : end - M_.exo_nbr);
chck = 0;
- end;
+ end
mexErrCheck('bytecode', chck);
- end;
+ end
if k == 1
g1(1:M_.endo_nbr,-M_.endo_nbr + [cur_indx lead_indx]) = data1.g1(:,M_.nspred + 1:end);
elseif k == per
g1(M_.endo_nbr * (k - 1) + 1 :M_.endo_nbr * k,M_.endo_nbr * (k -2) + [lag_indx cur_indx]) = data1.g1(:,1:M_.nspred + M_.endo_nbr);
else
g1(M_.endo_nbr * (k - 1) + 1 :M_.endo_nbr * k, M_.endo_nbr * (k -2) + [lag_indx cur_indx lead_indx]) = data1.g1;
- end;
+ end
l2 = 1;
pf_c = 1;
@@ -779,21 +779,21 @@ else
for ii = 2:constrained_periods - t + 1
indx_x(l2) = length(controlled_varexo) + pf * (ii - 2) + constraint_index{k + ii - 1}(pf_c);
l2 = l2 + 1;
- end;
+ end
pf_c = pf_c + 1;
else
indx_x(l2) = l;
l2 = l2 + 1;
- end;
+ end
cum_index_d_y_x = [cum_index_d_y_x; constrained_vars_t(l)];
else
cum_index_d_y_x = [cum_index_d_y_x; constrained_vars_t(l) + (k - 1) * M_.endo_nbr];
end
cum_l1 = cum_l1 + length(l1);
- end;
- end;
- end;
- end;
+ end
+ end
+ end
+ end
d_y_x = - g1 \ g1_x;
@@ -819,7 +819,7 @@ else
count_col = count_col + 1;
end
cum_l1 = cum_l1 + length(constrained_vars_t(j1));
- end;
+ end
% % Numerical computation of the derivatives in the second systme
@@ -835,7 +835,7 @@ else
% J1(:,col_count) = (oo_.endo_simul(indx_endo) - ys) / eps1;
% oo_.exo_simul(time,j_pos) = saved;
% col_count = col_count + 1;
-% end;
+% end
% else
% saved = oo_.exo_simul(maximum_lag+1,j_pos);
% oo_.exo_simul(maximum_lag+1,j_pos) = oo_.exo_simul(maximum_lag+1,j_pos) + eps1;
@@ -845,8 +845,8 @@ else
% % J(:,col_count) = (oo_.endo_simul((pp - 1) * M_.endo_nbr + 1: pp * M_.endo_nbr) - ys) / eps1;
% oo_.exo_simul(maximum_lag+1,j_pos) = saved;
% col_count = col_count + 1;
-% end;
-% end;
+% end
+% end
% disp('J1');
% disp(full(J1));
% sdfmlk;
@@ -870,7 +870,7 @@ else
z_root = find(abs(ev) < 1e-4);
z_root
disp(V(:,z_root));
- end;
+ end
old_exo = oo_.exo_simul;
col_count = 1;
for j = constraint_index_t
@@ -881,14 +881,14 @@ else
else
oo_.exo_simul(maximum_lag + 1,j_pos) = oo_.exo_simul(maximum_lag + 1,j_pos) + D_exo(col_count);
col_count = col_count + 1;
- end;
- end;
- end;
+ end
+ end
+ end
it = it + 1;
- end;
+ end
if ~convg
error(['convergence not achived at time ' int2str(t) ' after ' int2str(it) ' iterations']);
- end;
+ end
for j = constraint_index_t
j_pos=controlled_varexo(j);
if constrained_perfect_foresight(j)
@@ -900,20 +900,20 @@ else
end
else
exo(maximum_lag + t,j_pos) = oo_.exo_simul(maximum_lag + 1,j_pos);
- end;
- end;
+ end
+ end
past_val = past_val + length(time_index_constraint);
if t < constrained_periods
endo(maximum_lag + t,:) = yc;
else
endo(maximum_lag + t :maximum_lag + options_cond_fcst.periods ,:) = ycc(:,maximum_lag + 1:maximum_lag + options_cond_fcst.periods - constrained_periods + 1)';
- end;
+ end
initial_conditions = yc;
if maximum_lag > 0
exo_init(1,:) = exo(maximum_lag + t,:);
- end;
- end;
-end;
+ end
+ end
+end
options_.periods = save_options_periods;
options_.dynatol.f = save_options_dynatol_f;
options_.initval_file = save_options_initval_file;
@@ -922,4 +922,4 @@ oo_.endo_simul = endo';
oo_.exo_simul = exo;
if direct_mode
data_set = dseries([endo(2:end,1:M_.orig_endo_nbr) exo(2:end,:)], total_periods(1), {plan.endo_names{:} plan.exo_names{:}}, {plan.endo_names{:} plan.exo_names{:}});
-end;
+end
diff --git a/matlab/perfect-foresight-models/solve_stacked_problem.m b/matlab/perfect-foresight-models/solve_stacked_problem.m
index 7a1835ba6..66fa99ffe 100644
--- a/matlab/perfect-foresight-models/solve_stacked_problem.m
+++ b/matlab/perfect-foresight-models/solve_stacked_problem.m
@@ -1,4 +1,4 @@
-function [endogenousvariables, info] = solve_stacked_problem(endogenousvariables, exogenousvariables, steadystate, M, options);
+function [endogenousvariables, info] = solve_stacked_problem(endogenousvariables, exogenousvariables, steadystate, M, options)
% [endogenousvariables, info] = solve_stacked_problem(endogenousvariables, exogenousvariables, steadystate, M, options);
% Solves the perfect foresight model using dynare_solve
%
diff --git a/matlab/plot_identification.m b/matlab/plot_identification.m
index f699d2e42..116909bb2 100644
--- a/matlab/plot_identification.m
+++ b/matlab/plot_identification.m
@@ -58,7 +58,7 @@ siLREnorm = idelre.siLREnorm;
% end
tittxt1=regexprep(tittxt, ' ', '_');
tittxt1=strrep(tittxt1, '.', '');
-if SampleSize == 1,
+if SampleSize == 1
siJ = idemoments.siJ;
hh = dyn_figure(options_.nodisplay,'Name',[tittxt, ' - Identification using info from observables']);
subplot(211)
@@ -72,7 +72,7 @@ if SampleSize == 1,
set(gca,'xlim',[0 nparam+1])
set(gca,'xticklabel','')
dy = get(gca,'ylim');
- for ip=1:nparam,
+ for ip=1:nparam
text(ip,dy(1),name{is(ip)},'rotation',90,'HorizontalAlignment','right','interpreter','none')
end
if ~all(isnan(idehess.ide_strength_J_prior))
@@ -80,7 +80,7 @@ if SampleSize == 1,
else
legend('relative to param value','Location','Best')
end
- if idehess.flag_score,
+ if idehess.flag_score
title('Identification strength with asymptotic Information matrix (log-scale)')
else
title('Identification strength with moments Information matrix (log-scale)')
@@ -96,7 +96,7 @@ if SampleSize == 1,
set(gca,'xlim',[0 nparam+1])
set(gca,'xticklabel','')
dy = get(gca,'ylim');
- for ip=1:nparam,
+ for ip=1:nparam
text(ip,dy(1),name{is(ip)},'rotation',90,'HorizontalAlignment','right','interpreter','none')
end
if ~all(isnan(idehess.deltaM_prior))
@@ -104,7 +104,7 @@ if SampleSize == 1,
else
legend('relative to param value','Location','Best')
end
- if idehess.flag_score,
+ if idehess.flag_score
title('Sensitivity component with asymptotic Information matrix (log-scale)')
else
title('Sensitivity component with moments Information matrix (log-scale)')
@@ -124,8 +124,8 @@ if SampleSize == 1,
end
dyn_saveas(hh,[IdentifDirectoryName '/' M_.fname '_ident_strength_' tittxt1],options_.nodisplay,options_.graph_format);
- if advanced,
- if ~options_.nodisplay,
+ if advanced
+ if ~options_.nodisplay
skipline()
disp('Press ENTER to plot advanced diagnostics'), pause(5),
end
@@ -146,7 +146,7 @@ if SampleSize == 1,
set(gca,'xlim',[0 nparam+1])
set(gca,'xticklabel','')
dy = get(gca,'ylim');
- for ip=1:nparam,
+ for ip=1:nparam
text(ip,dy(1),name{is(ip)},'rotation',90,'HorizontalAlignment','right','interpreter','none')
end
legend('Moments','Model','LRE model','Location','Best')
@@ -167,16 +167,16 @@ if SampleSize == 1,
end
end
% identificaton patterns
- for j=1:size(idemoments.cosnJ,2),
+ for j=1:size(idemoments.cosnJ,2)
pax=NaN(nparam,nparam);
% fprintf('\n')
% disp(['Collinearity patterns with ', int2str(j) ,' parameter(s)'])
% fprintf('%-15s [%-*s] %10s\n','Parameter',(15+1)*j,' Expl. params ','cosn')
- for i=1:nparam,
+ for i=1:nparam
namx='';
- for in=1:j,
+ for in=1:j
dumpindx = idemoments.pars{i,j}(in);
- if isnan(dumpindx),
+ if isnan(dumpindx)
namx=[namx ' ' sprintf('%-15s','--')];
else
namx=[namx ' ' sprintf('%-15s',name{dumpindx})];
@@ -189,7 +189,7 @@ if SampleSize == 1,
imagesc(pax,[0 1]);
set(gca,'xticklabel','')
set(gca,'yticklabel','')
- for ip=1:nparam,
+ for ip=1:nparam
text(ip,(0.5),name{ip},'rotation',90,'HorizontalAlignment','left','interpreter','none')
text(0.5,ip,name{ip},'rotation',0,'HorizontalAlignment','right','interpreter','none')
end
@@ -198,7 +198,7 @@ if SampleSize == 1,
ax=colormap;
ax(1,:)=[0.9 0.9 0.9];
colormap(ax);
- if nparam>10,
+ if nparam>10
set(gca,'xtick',(5:5:nparam))
set(gca,'ytick',(5:5:nparam))
end
@@ -223,8 +223,8 @@ if SampleSize == 1,
skipline()
[U,S,V]=svd(idehess.AHess,0);
S=diag(S);
- if idehess.flag_score,
- if nparam<5,
+ if idehess.flag_score
+ if nparam<5
f1 = dyn_figure(options_.nodisplay,'Name',[tittxt,' - Identification patterns (Information matrix)']);
tex_tit_1=[tittxt,' - Identification patterns (Information matrix)'];
else
@@ -236,7 +236,7 @@ if SampleSize == 1,
else
% S = idemoments.S;
% V = idemoments.V;
- if nparam<5,
+ if nparam<5
f1 = dyn_figure(options_.nodisplay,'Name',[tittxt,' - Identification patterns (moments Information matrix)']);
tex_tit_1=[tittxt,' - Identification patterns (moments Information matrix)'];
else
@@ -246,25 +246,25 @@ if SampleSize == 1,
tex_tit_2=[tittxt,' - Identification patterns (moments Information matrix): HIGHEST SV'];
end
end
- for j=1:min(nparam,8),
- if j<5,
+ for j=1:min(nparam,8)
+ if j<5
set(0,'CurrentFigure',f1),
jj=j;
else
set(0,'CurrentFigure',f2),
jj=j-4;
end
- subplot(4,1,jj),
+ subplot(4,1,jj)
if j<5
- bar(abs(V(:,end-j+1))),
+ bar(abs(V(:,end-j+1)))
Stit = S(end-j+1);
else
bar(abs(V(:,jj))),
Stit = S(jj);
end
set(gca,'xticklabel','')
- if j==4 || j==nparam || j==8,
- for ip=1:nparam,
+ if j==4 || j==nparam || j==8
+ for ip=1:nparam
text(ip,-0.02,name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
end
end
@@ -284,7 +284,7 @@ if SampleSize == 1,
fprintf(fidTeX,'%% End Of TeX file. \n');
fclose(fidTeX);
end
- if nparam>4,
+ if nparam>4
dyn_saveas(f2,[ IdentifDirectoryName '/' M_.fname '_ident_pattern_' tittxt1 '_2' ],options_.nodisplay,options_.graph_format);
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fidTeX = fopen([ IdentifDirectoryName '/' M_.fname '_ident_pattern_' tittxt1 '_2.tex'],'w');
@@ -309,7 +309,7 @@ else
[ss, is] = sort(mmm);
mmm = mean(siJnorm)';
mmm = mmm./max(mmm);
- if advanced,
+ if advanced
mmm1 = mean(siHnorm)';
mmm=[mmm mmm1./max(mmm1)];
mmm1 = mean(siLREnorm)';
@@ -322,10 +322,10 @@ else
set(gca,'xlim',[0 nparam+1])
set(gca,'xticklabel','')
dy = get(gca,'ylim');
- for ip=1:nparam,
+ for ip=1:nparam
text(ip,dy(1),name{is(ip)},'rotation',90,'HorizontalAlignment','right','interpreter','none')
end
- if advanced,
+ if advanced
legend('Moments','Model','LRE model','Location','Best')
end
title('MC mean of sensitivity measures')
@@ -344,7 +344,7 @@ else
fclose(fidTeX);
end
- if advanced,
+ if advanced
if ~options_.nodisplay,
skipline()
disp('Press ENTER to display advanced diagnostics'), pause(5),
@@ -397,7 +397,7 @@ else
% [proba, dproba] = stab_map_1(params, is(1:ncut), is(ncut+1:end), ['MC_HighestMultiCollinearity_',name{j}], 1, [], IdentifDirectoryName, 0.15);
% end
- if nparam<5,
+ if nparam<5
f1 = dyn_figure(options_.nodisplay,'Name',[tittxt,' - MC Identification patterns (moments): HIGHEST SV']);
tex_tit_1=[tittxt,' - MC Identification patterns (moments): HIGHEST SV'];
else
@@ -407,13 +407,13 @@ else
tex_tit_2=[tittxt,' - MC Identification patterns (moments): HIGHEST SV'];
end
nplots=min(nparam,8);
- if nplots>4,
+ if nplots>4
nsubplo=ceil(nplots/2);
else
nsubplo=nplots;
end
- for j=1:nplots,
- if (nparam>4 && j<=ceil(nplots/2)) || nparam<5,
+ for j=1:nplots
+ if (nparam>4 && j<=ceil(nplots/2)) || nparam<5
set(0,'CurrentFigure',f1),
jj=j;
VVV=squeeze(abs(idemoments.V(:,:,end-j+1)));
@@ -424,8 +424,8 @@ else
VVV=squeeze(abs(idemoments.V(:,:,jj)));
SSS = idemoments.S(:,jj);
end
- subplot(nsubplo,1,jj),
- for i=1:nparam,
+ subplot(nsubplo,1,jj)
+ for i=1:nparam
[post_mean, post_median(:,i), post_var, hpd_interval(i,:), post_deciles] = posterior_moments(VVV(:,i),0,0.9);
end
bar(post_median)
@@ -433,8 +433,8 @@ else
Stit=mean(SSS);
set(gca,'xticklabel','')
- if j==4 || j==nparam || j==8,
- for ip=1:nparam,
+ if j==4 || j==nparam || j==8
+ for ip=1:nparam
text(ip,-0.02,name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
end
end
@@ -454,7 +454,7 @@ else
fprintf(fidTeX,'%% End Of TeX file. \n');
fclose(fidTeX);
end
- if nparam>4,
+ if nparam>4
dyn_saveas(f2,[ IdentifDirectoryName '/' M_.fname '_MC_ident_pattern_2' ],options_.nodisplay,options_.graph_format);
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fidTeX = fopen([ IdentifDirectoryName '/' M_.fname '_MC_ident_pattern_2.tex'],'w');
diff --git a/matlab/plot_priors.m b/matlab/plot_priors.m
index 04f371566..2b2fc83f6 100644
--- a/matlab/plot_priors.m
+++ b/matlab/plot_priors.m
@@ -42,7 +42,7 @@ if TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
fprintf(fidTeX,' \n');
end
-for plt = 1:nbplt,
+for plt = 1:nbplt
hplt = dyn_figure(options_.nodisplay,'Name',figurename);
if TeX
TeXNAMES = [];
@@ -73,7 +73,7 @@ for plt = 1:nbplt,
dyn_saveas(hplt,[M_.fname '_Priors' int2str(plt)],options_.nodisplay,options_.graph_format);
if TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fprintf(fidTeX,'\\begin{figure}[H]\n');
- for jj = 1:nstar0,
+ for jj = 1:nstar0
fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(jj,:)),deblank(TeXNAMES(jj,:)));
end
fprintf(fidTeX,'\\centering\n');
diff --git a/matlab/plot_shock_decomposition.m b/matlab/plot_shock_decomposition.m
index 698192a91..b7d3675fc 100644
--- a/matlab/plot_shock_decomposition.m
+++ b/matlab/plot_shock_decomposition.m
@@ -55,7 +55,7 @@ fig_name='';
% steadystate=0;
% write_xls=0;
-if isfield(options_.plot_shock_decomp,'expand'), % private trap for uimenu calls
+if isfield(options_.plot_shock_decomp,'expand') % private trap for uimenu calls
expand=options_.plot_shock_decomp.expand;
else
expand=0;
@@ -72,15 +72,15 @@ forecast_ = options_.shock_decomp.forecast;
steadystate = options_.plot_shock_decomp.steadystate;
write_xls = options_.plot_shock_decomp.write_xls;
-if vintage_,
+if vintage_
forecast_ = min(forecast_,options_.nobs-vintage_);
end
initial_date = options_.initial_date;
-if isfield(options_.plot_shock_decomp,'q2a'), % private trap for aoa calls
+if isfield(options_.plot_shock_decomp,'q2a') % private trap for aoa calls
q2a=options_.plot_shock_decomp.q2a;
- if isstruct(q2a) && isempty(fieldnames(q2a)),
+ if isstruct(q2a) && isempty(fieldnames(q2a))
q2a=0;
end
else
@@ -126,12 +126,12 @@ end
steady_state = oo_.steady_state;
if isequal(type,'aoa') && isstruct(q2a) && realtime_
- if isempty(initial_date),
+ if isempty(initial_date)
t0=1;
initial_date = dates('1Y');
else
initial_date0 = dates([int2str(initial_date.time(1)) 'Y']);
- if initial_date.time(2)==1,
+ if initial_date.time(2)==1
t0=1;
initial_date1=initial_date0;
else
@@ -142,22 +142,22 @@ if isequal(type,'aoa') && isstruct(q2a) && realtime_
t0=min(options_.plot_shock_decomp.save_realtime);
ini1 = initial_date+t0-1;
t0=t0+(4-ini1.time(2));
- if ~isfield(q2a,'var_type'), % private trap for aoa calls
+ if ~isfield(q2a,'var_type') % private trap for aoa calls
q2a.var_type=1;
end
- if ~isfield(q2a,'islog'), % private trap for aoa calls
+ if ~isfield(q2a,'islog') % private trap for aoa calls
q2a.islog=0;
end
- if ~isfield(q2a,'GYTREND0'), % private trap for aoa calls
+ if ~isfield(q2a,'GYTREND0') % private trap for aoa calls
q2a.GYTREND0=0;
end
- if ~isfield(q2a,'aux'), % private trap for aoa calls
+ if ~isfield(q2a,'aux') % private trap for aoa calls
q2a.aux=0;
end
- if ~isfield(q2a,'cumfix'), % private trap for aoa calls
+ if ~isfield(q2a,'cumfix') % private trap for aoa calls
q2a.cumfix=1;
end
- if ~isfield(q2a,'plot'), % private trap for aoa calls
+ if ~isfield(q2a,'plot') % private trap for aoa calls
q2a.plot=1; % growth rate
end
@@ -189,7 +189,7 @@ if options_.plot_shock_decomp.use_shock_groups
ngroups = length(shock_ind);
fig_name=[fig_name ' group ' options_.plot_shock_decomp.use_shock_groups];
shock_names = shock_ind;
- for i=1:ngroups,
+ for i=1:ngroups
shock_names{i} = (shock_groups.(shock_ind{i}).label);
end
zz = zeros(endo_nbr,ngroups+2,gend);
@@ -206,7 +206,7 @@ if options_.plot_shock_decomp.use_shock_groups
shock_groups.(['group' int2str(ngroups+1)]).label = 'Others';
shock_groups.(['group' int2str(ngroups+1)]).shocks = cellstr(M_.exo_names(find(~ismember([1:M_.exo_nbr],kcum)),:))';
M_.shock_groups.(options_.plot_shock_decomp.use_shock_groups)=shock_groups;
- if any(any(zothers)),
+ if any(any(zothers))
shock_names = [shock_names; {'Others + Initial Values'}];
end
zz(:,ngroups+1,:) = sum(z(:,1:nshocks+1,:),2);
@@ -222,7 +222,7 @@ end
MAP(end,:) = [0.7 0.7 0.7];
% MAP = [MAP; [0.7 0.7 0.7]; [0.3 0.3 0.3]];
-if isempty(options_.plot_shock_decomp.colormap),
+if isempty(options_.plot_shock_decomp.colormap)
options_.plot_shock_decomp.colormap = MAP;
end
@@ -243,12 +243,12 @@ switch type
case 'aoa'
- if isempty(initial_date),
+ if isempty(initial_date)
t0=4;
initial_date = dates('1Y');
else
initial_date0 = dates([int2str(initial_date.time(1)) 'Y']);
- if initial_date.time(2)==1,
+ if initial_date.time(2)==1
t0=1;
initial_date1=initial_date0;
else
@@ -258,22 +258,22 @@ switch type
end
if isstruct(q2a)
if realtime_ == 0
- if ~isfield(q2a,'var_type'), % private trap for aoa calls
+ if ~isfield(q2a,'var_type') % private trap for aoa calls
q2a.var_type=1;
end
- if ~isfield(q2a,'islog'), % private trap for aoa calls
+ if ~isfield(q2a,'islog') % private trap for aoa calls
q2a.islog=0;
end
- if ~isfield(q2a,'GYTREND0'), % private trap for aoa calls
+ if ~isfield(q2a,'GYTREND0') % private trap for aoa calls
q2a.GYTREND0=0;
end
- if ~isfield(q2a,'aux'), % private trap for aoa calls
+ if ~isfield(q2a,'aux') % private trap for aoa calls
q2a.aux=0;
end
- if ~isfield(q2a,'cumfix'), % private trap for aoa calls
+ if ~isfield(q2a,'cumfix') % private trap for aoa calls
q2a.cumfix=1;
end
- if ~isfield(q2a,'plot'), % private trap for aoa calls
+ if ~isfield(q2a,'plot') % private trap for aoa calls
q2a.plot=1; % growth rate
end
@@ -341,7 +341,7 @@ z = z(:,:,a:b);
options_.plot_shock_decomp.fig_name=fig_name;
options_.plot_shock_decomp.orig_varlist = varlist;
-if detail_plot,
+if detail_plot
graph_decomp_detail(z,shock_names,M_.endo_names,i_var,my_initial_date,M_,options_)
else
graph_decomp(z,shock_names,M_.endo_names,i_var,my_initial_date,M_,options_);
diff --git a/matlab/pm3.m b/matlab/pm3.m
index ae0f474d1..2417f8c05 100644
--- a/matlab/pm3.m
+++ b/matlab/pm3.m
@@ -60,7 +60,7 @@ else
end
end
if options_.TeX
- if isempty(tit_tex),
+ if isempty(tit_tex)
tit_tex=names1;
end
@@ -321,13 +321,13 @@ nvar0=nvar;
if ~isoctave
% Commenting for testing!
- if isnumeric(options_.parallel) || ceil(size(varlist,1)/MaxNumberOfPlotsPerFigure)<4,
+ if isnumeric(options_.parallel) || ceil(size(varlist,1)/MaxNumberOfPlotsPerFigure)<4
fout = pm3_core(localVars,1,nvar,0);
% Parallel execution!
else
isRemoteOctave = 0;
- for indPC=1:length(options_.parallel),
+ for indPC=1:length(options_.parallel)
isRemoteOctave = isRemoteOctave + (findstr(options_.parallel(indPC).MatlabOctavePath, 'octave'));
end
if isRemoteOctave
@@ -356,12 +356,12 @@ if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
nvar0=cumsum(nvar0);
i=0;
- for j=1:length(nvar0),
+ for j=1:length(
NAMES = [];
TEXNAMES = [];
nvar=nvar0(j);
- while i<nvar,
+ while i<nvar
i=i+1;
if max(abs(Mean(:,i))) > 10^(-6)
subplotnum = subplotnum+1;
diff --git a/matlab/pm3_core.m b/matlab/pm3_core.m
index 32052f83c..e484304a8 100644
--- a/matlab/pm3_core.m
+++ b/matlab/pm3_core.m
@@ -30,7 +30,7 @@ function myoutput=pm3_core(myinputs,fpar,nvar,whoiam, ThisMatlab)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-if nargin<4,
+if nargin<4
whoiam=0;
end
@@ -66,7 +66,7 @@ figunumber = 0;
subplotnum = 0;
hh = dyn_figure(options_.nodisplay,'Name',[tit1 ' ' int2str(figunumber+1)]);
RemoteFlag = 0;
-if whoiam,
+if whoiam
if Parallel(ThisMatlab).Local ==0
RemoteFlag=1;
end
@@ -101,7 +101,7 @@ for i=fpar:nvar
end
end
- if whoiam,
+ if whoiam
if Parallel(ThisMatlab).Local==0
DirectoryName = CheckPath('Output',M_.dname);
end
@@ -109,7 +109,7 @@ for i=fpar:nvar
if subplotnum == MaxNumberOfPlotsPerFigure || i == nvar
dyn_saveas(hh,[M_.dname '/Output/' M_.fname '_' name3 '_' deblank(tit3(i,:))],options_.nodisplay,options_.graph_format);
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName = [OutputFileName; {[M_.dname, filesep, 'Output',filesep], [M_.fname '_' name3 '_' deblank(tit3(i,:)) '.*']}];
end
subplotnum = 0;
@@ -119,7 +119,7 @@ for i=fpar:nvar
end
end
- if whoiam,
+ if whoiam
% waitbarString = [ 'Variable ' int2str(i) '/' int2str(nvar) ' done.'];
% fMessageStatus((i-fpar+1)/(nvar-fpar+1),whoiam,waitbarString, waitbarTitle, Parallel(ThisMatlab));
dyn_waitbar((i-fpar+1)/(nvar-fpar+1),h);
@@ -128,7 +128,7 @@ for i=fpar:nvar
end
-if whoiam,
+if whoiam
dyn_waitbar_close(h);
end
myoutput.OutputFileName=OutputFileName;
diff --git a/matlab/posterior_sampler.m b/matlab/posterior_sampler.m
index be512d140..5afed9575 100644
--- a/matlab/posterior_sampler.m
+++ b/matlab/posterior_sampler.m
@@ -107,7 +107,7 @@ localVars = struct('TargetFun', TargetFun, ...
'oo_', oo_,...
'varargin',[]);
-if strcmp(sampler_options.posterior_sampling_method,'tailored_random_block_metropolis_hastings');
+if strcmp(sampler_options.posterior_sampling_method,'tailored_random_block_metropolis_hastings')
localVars.options_.silent_optimizer=1; %locally set optimizer to silent mode
if ~isempty(sampler_options.optim_opt)
localVars.options_.optim_opt=sampler_options.optim_opt; %locally set options for optimizer
@@ -117,7 +117,7 @@ end
% User doesn't want to use parallel computing, or wants to compute a
% single chain compute sequentially.
-if isnumeric(options_.parallel) || (nblck-fblck)==0,
+if isnumeric(options_.parallel) || (nblck-fblck)==0
fout = posterior_sampler_core(localVars, fblck, nblck, 0);
record = fout.record;
% Parallel in Local or remote machine.
@@ -128,20 +128,20 @@ else
NamFileInput(1,:) = {'',[ModelName '_static.m']};
NamFileInput(2,:) = {'',[ModelName '_dynamic.m']};
NamFileInput(3,:) = {'',[M_.fname '_set_auxiliary_variables.m']};
- if options_.steadystate_flag,
- if options_.steadystate_flag == 1,
+ if options_.steadystate_flag
+ if options_.steadystate_flag == 1
NamFileInput(length(NamFileInput)+1,:)={'',[M_.fname '_steadystate.m']};
else
NamFileInput(length(NamFileInput)+1,:)={'',[M_.fname '_steadystate2.m']};
end
end
- if (options_.load_mh_file~=0) && any(fline>1) ,
+ if (options_.load_mh_file~=0) && any(fline>1)
NamFileInput(length(NamFileInput)+1,:)={[M_.dname '/metropolis/'],[ModelName '_mh' int2str(NewFile(1)) '_blck*.mat']};
end
% from where to get back results
% NamFileOutput(1,:) = {[M_.dname,'/metropolis/'],'*.*'};
[fout, nBlockPerCPU, totCPU] = masterParallel(options_.parallel, fblck, nblck,NamFileInput,'posterior_sampler_core', localVars, globalVars, options_.parallel_info);
- for j=1:totCPU,
+ for j=1:totCPU
offset = sum(nBlockPerCPU(1:j-1))+fblck-1;
record.LastLogPost(offset+1:sum(nBlockPerCPU(1:j)))=fout(j).record.LastLogPost(offset+1:sum(nBlockPerCPU(1:j)));
record.LastParameters(offset+1:sum(nBlockPerCPU(1:j)),:)=fout(j).record.LastParameters(offset+1:sum(nBlockPerCPU(1:j)),:);
diff --git a/matlab/posterior_sampler_core.m b/matlab/posterior_sampler_core.m
index d88ae742a..125cb872d 100644
--- a/matlab/posterior_sampler_core.m
+++ b/matlab/posterior_sampler_core.m
@@ -53,7 +53,7 @@ function myoutput = posterior_sampler_core(myinputs,fblck,nblck,whoiam, ThisMatl
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-if nargin<4,
+if nargin<4
whoiam=0;
end
@@ -108,7 +108,7 @@ end
%
sampler_options.xparam1 = xparam1;
-if ~isempty(d),
+if ~isempty(d)
sampler_options.proposal_covariance_Cholesky_decomposition = d*diag(bayestopt_.jscale);
%store information for load_mh_file
record.ProposalCovariance=d;
@@ -117,7 +117,7 @@ end
block_iter=0;
-for curr_block = fblck:nblck,
+for curr_block = fblck:nblck
LastSeeds=[];
block_iter=block_iter+1;
try
@@ -192,7 +192,7 @@ for curr_block = fblck:nblck,
end
if (draw_index_current_file == InitSizeArray(curr_block)) || (draw_iter == nruns(curr_block)) % Now I save the simulations, either because the current file is full or the chain is done
[LastSeeds.(['file' int2str(NewFile(curr_block))]).Unifor, LastSeeds.(['file' int2str(NewFile(curr_block))]).Normal] = get_dynare_random_generator_state();
- if save_tmp_file,
+ if save_tmp_file
delete([BaseName '_mh_tmp_blck' int2str(curr_block) '.mat']);
end
save([BaseName '_mh' int2str(NewFile(curr_block)) '_blck' int2str(curr_block) '.mat'],'x2','logpo2','LastSeeds');
diff --git a/matlab/posterior_sampler_initialization.m b/matlab/posterior_sampler_initialization.m
index f7927a173..7d84bed96 100644
--- a/matlab/posterior_sampler_initialization.m
+++ b/matlab/posterior_sampler_initialization.m
@@ -112,7 +112,7 @@ if ~options_.load_mh_file && ~options_.mh_recover
fprintf(fidlog,[' Number of blocks...............: ' int2str(NumberOfBlocks) '\n']);
fprintf(fidlog,[' Number of simulations per block: ' int2str(nruns(1)) '\n']);
fprintf(fidlog,' \n');
- if isempty(d),
+ if isempty(d)
prior_draw(bayestopt_,options_.prior_trunc);
end
% Find initial values for the NumberOfBlocks chains...
@@ -127,7 +127,7 @@ if ~options_.load_mh_file && ~options_.mh_recover
init_iter = 0;
trial = 1;
while validate == 0 && trial <= 10
- if isempty(d),
+ if isempty(d)
candidate = prior_draw();
else
candidate = rand_multivariate_normal( transpose(xparam1), d * options_.mh_init_scale, npar);
@@ -234,7 +234,7 @@ if ~options_.load_mh_file && ~options_.mh_recover
fprintf(fidlog,[' Expected number of files per block.......: ' int2str(AnticipatedNumberOfFiles) '.\n']);
fprintf(fidlog,[' Expected number of lines in the last file: ' int2str(AnticipatedNumberOfLinesInTheLastFile) '.\n']);
fprintf(fidlog,['\n']);
- for j = 1:NumberOfBlocks,
+ for j = 1:NumberOfBlocks
fprintf(fidlog,[' Initial state of the Gaussian random number generator for chain number ',int2str(j),':\n']);
for i=1:length(record.InitialSeeds(j).Normal)
fprintf(fidlog,[' ' num2str(record.InitialSeeds(j).Normal(i)') '\n']);
@@ -243,7 +243,7 @@ if ~options_.load_mh_file && ~options_.mh_recover
for i=1:length(record.InitialSeeds(j).Unifor)
fprintf(fidlog,[' ' num2str(record.InitialSeeds(j).Unifor(i)') '\n']);
end
- end,
+ end
fprintf(fidlog,' \n');
fclose(fidlog);
elseif options_.load_mh_file && ~options_.mh_recover
diff --git a/matlab/prior_draw.m b/matlab/prior_draw.m
index 4eb628df9..5beea3f7d 100644
--- a/matlab/prior_draw.m
+++ b/matlab/prior_draw.m
@@ -110,7 +110,7 @@ end
if uniform_draws
pdraw(uniform_index) = rand(length(uniform_index),1).*(p4(uniform_index)-p3(uniform_index)) + p3(uniform_index);
out_of_bound = find( (pdraw(uniform_index)'>ub(uniform_index)) | (pdraw(uniform_index)'<lb(uniform_index)));
- while ~isempty(out_of_bound),
+ while ~isempty(out_of_bound)
pdraw(uniform_index) = rand(length(uniform_index),1).*(p4(uniform_index)-p3(uniform_index)) + p3(uniform_index);
out_of_bound = find( (pdraw(uniform_index)'>ub(uniform_index)) | (pdraw(uniform_index)'<lb(uniform_index)));
end
@@ -119,7 +119,7 @@ end
if gaussian_draws
pdraw(gaussian_index) = randn(length(gaussian_index),1).*p7(gaussian_index) + p6(gaussian_index);
out_of_bound = find( (pdraw(gaussian_index)'>ub(gaussian_index)) | (pdraw(gaussian_index)'<lb(gaussian_index)));
- while ~isempty(out_of_bound),
+ while ~isempty(out_of_bound)
pdraw(gaussian_index(out_of_bound)) = randn(length(gaussian_index(out_of_bound)),1).*p7(gaussian_index(out_of_bound)) + p6(gaussian_index(out_of_bound));
out_of_bound = find( (pdraw(gaussian_index)'>ub(gaussian_index)) | (pdraw(gaussian_index)'<lb(gaussian_index)));
end
@@ -128,7 +128,7 @@ end
if gamma_draws
pdraw(gamma_index) = gamrnd(p6(gamma_index),p7(gamma_index))+p3(gamma_index);
out_of_bound = find( (pdraw(gamma_index)'>ub(gamma_index)) | (pdraw(gamma_index)'<lb(gamma_index)));
- while ~isempty(out_of_bound),
+ while ~isempty(out_of_bound)
pdraw(gamma_index(out_of_bound)) = gamrnd(p6(gamma_index(out_of_bound)),p7(gamma_index(out_of_bound)))+p3(gamma_index(out_of_bound));
out_of_bound = find( (pdraw(gamma_index)'>ub(gamma_index)) | (pdraw(gamma_index)'<lb(gamma_index)));
end
@@ -137,7 +137,7 @@ end
if beta_draws
pdraw(beta_index) = (p4(beta_index)-p3(beta_index)).*betarnd(p6(beta_index),p7(beta_index))+p3(beta_index);
out_of_bound = find( (pdraw(beta_index)'>ub(beta_index)) | (pdraw(beta_index)'<lb(beta_index)));
- while ~isempty(out_of_bound),
+ while ~isempty(out_of_bound)
pdraw(beta_index(out_of_bound)) = (p4(beta_index(out_of_bound))-p3(beta_index(out_of_bound))).*betarnd(p6(beta_index(out_of_bound)),p7(beta_index(out_of_bound)))+p3(beta_index(out_of_bound));
out_of_bound = find( (pdraw(beta_index)'>ub(beta_index)) | (pdraw(beta_index)'<lb(beta_index)));
end
@@ -147,7 +147,7 @@ if inverse_gamma_1_draws
pdraw(inverse_gamma_1_index) = ...
sqrt(1./gamrnd(p7(inverse_gamma_1_index)/2,2./p6(inverse_gamma_1_index)))+p3(inverse_gamma_1_index);
out_of_bound = find( (pdraw(inverse_gamma_1_index)'>ub(inverse_gamma_1_index)) | (pdraw(inverse_gamma_1_index)'<lb(inverse_gamma_1_index)));
- while ~isempty(out_of_bound),
+ while ~isempty(out_of_bound)
pdraw(inverse_gamma_1_index(out_of_bound)) = ...
sqrt(1./gamrnd(p7(inverse_gamma_1_index(out_of_bound))/2,2./p6(inverse_gamma_1_index(out_of_bound))))+p3(inverse_gamma_1_index(out_of_bound));
out_of_bound = find( (pdraw(inverse_gamma_1_index)'>ub(inverse_gamma_1_index)) | (pdraw(inverse_gamma_1_index)'<lb(inverse_gamma_1_index)));
@@ -158,7 +158,7 @@ if inverse_gamma_2_draws
pdraw(inverse_gamma_2_index) = ...
1./gamrnd(p7(inverse_gamma_2_index)/2,2./p6(inverse_gamma_2_index))+p3(inverse_gamma_2_index);
out_of_bound = find( (pdraw(inverse_gamma_2_index)'>ub(inverse_gamma_2_index)) | (pdraw(inverse_gamma_2_index)'<lb(inverse_gamma_2_index)));
- while ~isempty(out_of_bound),
+ while ~isempty(out_of_bound)
pdraw(inverse_gamma_2_index(out_of_bound)) = ...
1./gamrnd(p7(inverse_gamma_2_index(out_of_bound))/2,2./p6(inverse_gamma_2_index(out_of_bound)))+p3(inverse_gamma_2_index(out_of_bound));
out_of_bound = find( (pdraw(inverse_gamma_2_index)'>ub(inverse_gamma_2_index)) | (pdraw(inverse_gamma_2_index)'<lb(inverse_gamma_2_index)));
@@ -168,7 +168,7 @@ end
if weibull_draws
pdraw(weibull_index) = wblrnd(p7(weibull_index), p6(weibull_index)) + p3(weibull_index);
out_of_bound = find( (pdraw(weibull_index)'>ub(weibull_index)) | (pdraw(weibull_index)'<lb(weibull_index)));
- while ~isempty(out_of_bound),
+ while ~isempty(out_of_bound)
pdraw(weibull_index(out_of_bound)) = wblrnd(p7(weibull_index(out_of_bound)),p6(weibull_index(out_of_bound)))+p3(weibull_index(out_of_bound));
out_of_bound = find( (pdraw(weibull_index)'>ub(weibull_index)) | (pdraw(weibull_index)'<lb(weibull_index)));
end
diff --git a/matlab/prior_posterior_statistics.m b/matlab/prior_posterior_statistics.m
index b3cfdc933..e81f8024a 100644
--- a/matlab/prior_posterior_statistics.m
+++ b/matlab/prior_posterior_statistics.m
@@ -79,7 +79,7 @@ elseif strcmpi(type,'gsa')
DirectoryName = CheckPath(['gsa',filesep,'mc'],M_.dname);
load([ RootDirectoryName filesep M_.fname '_mc.mat'],'lpmat0','lpmat','istable')
end
- if ~isempty(lpmat0),
+ if ~isempty(lpmat0)
x=[lpmat0(istable,:) lpmat(istable,:)];
else
x=lpmat(istable,:);
@@ -207,7 +207,7 @@ localVars.MAX_momentsno = MAX_momentsno;
localVars.ifil=ifil;
localVars.DirectoryName = DirectoryName;
-if strcmpi(type,'posterior'),
+if strcmpi(type,'posterior')
BaseName = [DirectoryName filesep M_.fname];
load_last_mh_history_file(DirectoryName, M_.fname);
FirstMhFile = record.KeepedDraws.FirstMhFile;
@@ -217,7 +217,7 @@ if strcmpi(type,'posterior'),
TotalNumberOfMhDraws = sum(record.MhDraws(:,1));
NumberOfDraws = TotalNumberOfMhDraws-floor(options_.mh_drop*TotalNumberOfMhDraws);
mh_nblck = options_.mh_nblck;
- if B==NumberOfDraws*mh_nblck,
+ if B==NumberOfDraws*mh_nblck
% we load all retained MH runs !
logpost=GetAllPosteriorDraws(0, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
for column=1:npar
@@ -232,18 +232,18 @@ if strcmpi(type,'posterior'),
localVars.logpost=logpost;
end
-if ~strcmpi(type,'prior'),
+if ~strcmpi(type,'prior')
localVars.x=x;
end
% Like sequential execution!
-if isnumeric(options_.parallel),
+if isnumeric(options_.parallel)
[fout] = prior_posterior_statistics_core(localVars,1,B,0);
% Parallel execution!
else
[nCPU, totCPU, nBlockPerCPU] = distributeJobs(options_.parallel, 1, B);
ifil=zeros(n_variables_to_fill,totCPU);
- for j=1:totCPU-1,
+ for j=1:totCPU-1
if run_smoother
nfiles = ceil(nBlockPerCPU(j)/MAX_nsmoo);
ifil(1,j+1) =ifil(1,j)+nfiles;
@@ -295,8 +295,8 @@ else
NamFileInput(1,:) = {'',[M_.fname '_static.m']};
NamFileInput(2,:) = {'',[M_.fname '_dynamic.m']};
NamFileInput(3,:) = {'',[M_.fname '_set_auxiliary_variables.m']};
- if options_.steadystate_flag,
- if options_.steadystate_flag == 1,
+ if options_.steadystate_flag
+ if options_.steadystate_flag == 1
NamFileInput(length(NamFileInput)+1,:)={'',[M_.fname '_steadystate.m']};
else
NamFileInput(length(NamFileInput)+1,:)={'',[M_.fname '_steadystate2.m']};
@@ -397,9 +397,9 @@ if options_.filter_covariance
end
-if ~isnumeric(options_.parallel),
+if ~isnumeric(options_.parallel)
options_.parallel_info.leaveSlaveOpen = leaveSlaveOpen;
- if leaveSlaveOpen == 0,
+ if leaveSlaveOpen == 0
closeSlave(options_.parallel,options_.parallel_info.RemoteTmpFolder),
end
end
\ No newline at end of file
diff --git a/matlab/prior_posterior_statistics_core.m b/matlab/prior_posterior_statistics_core.m
index 3e8e31436..ba505f656 100644
--- a/matlab/prior_posterior_statistics_core.m
+++ b/matlab/prior_posterior_statistics_core.m
@@ -49,7 +49,7 @@ function myoutput=prior_posterior_statistics_core(myinputs,fpar,B,whoiam, ThisMa
global options_ oo_ M_ bayestopt_ estim_params_
-if nargin<4,
+if nargin<4
whoiam=0;
end
@@ -103,9 +103,9 @@ MAX_nruns=myinputs.MAX_nruns;
MAX_momentsno = myinputs.MAX_momentsno;
ifil=myinputs.ifil;
-if ~strcmpi(type,'prior'),
+if ~strcmpi(type,'prior')
x=myinputs.x;
- if strcmpi(type,'posterior'),
+ if strcmpi(type,'posterior')
logpost=myinputs.logpost;
end
end
@@ -128,7 +128,7 @@ end
RemoteFlag = 0;
if whoiam
- if Parallel(ThisMatlab).Local==0,
+ if Parallel(ThisMatlab).Local==0
RemoteFlag =1;
end
ifil=ifil(:,whoiam);
@@ -138,7 +138,7 @@ else
end
h = dyn_waitbar(prct0,['Taking ',type,' subdraws...']);
-if RemoteFlag==1,
+if RemoteFlag==1
OutputFileName_smooth = {};
OutputFileName_update = {};
OutputFileName_inno = {};
@@ -345,14 +345,14 @@ for b=fpar:B
irun = irun + ones(13,1);
- if run_smoother && (irun(1) > MAX_nsmoo || b == B),
+ if run_smoother && (irun(1) > MAX_nsmoo || b == B)
stock = stock_smooth(:,:,1:irun(1)-1);
ifil(1) = ifil(1) + 1;
save([DirectoryName '/' M_.fname '_smooth' int2str(ifil(1)) '.mat'],'stock');
stock = stock_update(:,:,1:irun(1)-1);
save([DirectoryName '/' M_.fname '_update' int2str(ifil(1)) '.mat'],'stock');
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_smooth = [OutputFileName_smooth; {[DirectoryName filesep], [M_.fname '_smooth' int2str(ifil(1)) '.mat']}];
OutputFileName_update = [OutputFileName_update; {[DirectoryName filesep], [M_.fname '_update' int2str(ifil(1)) '.mat']}];
end
@@ -363,7 +363,7 @@ for b=fpar:B
stock = stock_innov(:,:,1:irun(2)-1);
ifil(2) = ifil(2) + 1;
save([DirectoryName '/' M_.fname '_inno' int2str(ifil(2)) '.mat'],'stock');
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_inno = [OutputFileName_inno; {[DirectoryName filesep], [M_.fname '_inno' int2str(ifil(2)) '.mat']}];
end
irun(2) = 1;
@@ -373,7 +373,7 @@ for b=fpar:B
stock = stock_error(:,:,1:irun(3)-1);
ifil(3) = ifil(3) + 1;
save([DirectoryName '/' M_.fname '_error' int2str(ifil(3)) '.mat'],'stock');
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_error = [OutputFileName_error; {[DirectoryName filesep], [M_.fname '_error' int2str(ifil(3)) '.mat']}];
end
irun(3) = 1;
@@ -383,7 +383,7 @@ for b=fpar:B
stock = stock_filter_step_ahead(:,:,:,1:irun(4)-1);
ifil(4) = ifil(4) + 1;
save([DirectoryName '/' M_.fname '_filter_step_ahead' int2str(ifil(4)) '.mat'],'stock');
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_filter_step_ahead = [OutputFileName_filter_step_ahead; {[DirectoryName filesep], [M_.fname '_filter_step_ahead' int2str(ifil(4)) '.mat']}];
end
irun(4) = 1;
@@ -395,7 +395,7 @@ for b=fpar:B
stock_ys = stock_ys(1:irun(5)-1,:);
ifil(5) = ifil(5) + 1;
save([DirectoryName '/' M_.fname '_param' int2str(ifil(5)) '.mat'],'stock','stock_logpo','stock_ys');
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_param = [OutputFileName_param; {[DirectoryName filesep], [M_.fname '_param' int2str(ifil(5)) '.mat']}];
end
irun(5) = 1;
@@ -405,7 +405,7 @@ for b=fpar:B
stock = stock_forcst_mean(:,:,1:irun(6)-1);
ifil(6) = ifil(6) + 1;
save([DirectoryName '/' M_.fname '_forc_mean' int2str(ifil(6)) '.mat'],'stock');
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_forc_mean = [OutputFileName_forc_mean; {[DirectoryName filesep], [M_.fname '_forc_mean' int2str(ifil(6)) '.mat']}];
end
irun(6) = 1;
@@ -415,7 +415,7 @@ for b=fpar:B
stock = stock_forcst_point(:,:,1:irun(7)-1);
ifil(7) = ifil(7) + 1;
save([DirectoryName '/' M_.fname '_forc_point' int2str(ifil(7)) '.mat'],'stock');
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_forc_point = [OutputFileName_forc_point; {[DirectoryName filesep], [M_.fname '_forc_point' int2str(ifil(7)) '.mat']}];
end
irun(7) = 1;
@@ -425,7 +425,7 @@ for b=fpar:B
stock = stock_filter_covariance(:,:,:,1:irun(8)-1);
ifil(8) = ifil(8) + 1;
save([DirectoryName '/' M_.fname '_filter_covar' int2str(ifil(8)) '.mat'],'stock');
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_filter_covar = [OutputFileName_filter_covar; {[DirectoryName filesep], [M_.fname '_filter_covar' int2str(ifil(8)) '.mat']}];
end
irun(8) = 1;
@@ -436,7 +436,7 @@ for b=fpar:B
stock = stock_trend_coeff(:,1:irun(irun_index)-1);
ifil(irun_index) = ifil(irun_index) + 1;
save([DirectoryName '/' M_.fname '_trend_coeff' int2str(ifil(irun_index)) '.mat'],'stock');
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_trend_coeff = [OutputFileName_trend_coeff; {[DirectoryName filesep], [M_.fname '_trend_coeff' int2str(ifil(irun_index)) '.mat']}];
end
irun(irun_index) = 1;
@@ -447,7 +447,7 @@ for b=fpar:B
stock = stock_smoothed_constant(:,:,1:irun(irun_index)-1);
ifil(irun_index) = ifil(irun_index) + 1;
save([DirectoryName '/' M_.fname '_smoothed_constant' int2str(ifil(irun_index)) '.mat'],'stock');
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_smoothed_constant = [OutputFileName_smoothed_constant; {[DirectoryName filesep], [M_.fname '_smoothed_constant' int2str(ifil(irun_index)) '.mat']}];
end
irun(irun_index) = 1;
@@ -458,7 +458,7 @@ for b=fpar:B
stock = stock_smoothed_trend(:,:,1:irun(irun_index)-1);
ifil(irun_index) = ifil(irun_index) + 1;
save([DirectoryName '/' M_.fname '_smoothed_trend' int2str(ifil(irun_index)) '.mat'],'stock');
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_smoothed_trend = [OutputFileName_smoothed_trend; {[DirectoryName filesep], [M_.fname '_smoothed_trend' int2str(ifil(irun_index)) '.mat']}];
end
irun(irun_index) = 1;
@@ -469,7 +469,7 @@ for b=fpar:B
stock = stock_forcst_point_ME(:,:,1:irun(irun_index)-1);
ifil(irun_index) = ifil(irun_index) + 1;
save([DirectoryName '/' M_.fname '_forc_point_ME' int2str(ifil(irun_index)) '.mat'],'stock');
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_forc_point_ME = [OutputFileName_forc_point_ME; {[DirectoryName filesep], [M_.fname '_forc_point_ME' int2str(ifil(irun_index)) '.mat']}];
end
irun(irun_index) = 1;
@@ -480,7 +480,7 @@ for b=fpar:B
stock = stock_smoothed_uncert(:,:,:,1:irun(irun_index)-1);
ifil(irun_index) = ifil(irun_index) + 1;
save([DirectoryName '/' M_.fname '_state_uncert' int2str(ifil(irun_index)) '.mat'],'stock');
- if RemoteFlag==1,
+ if RemoteFlag==1
OutputFileName_state_uncert = [OutputFileName_state_uncert; {[DirectoryName filesep], [M_.fname '_state_uncert' int2str(ifil(irun_index)) '.mat']}];
end
irun(irun_index) = 1;
@@ -490,7 +490,7 @@ for b=fpar:B
end
myoutput.ifil=ifil;
-if RemoteFlag==1,
+if RemoteFlag==1
myoutput.OutputFileName = [OutputFileName_smooth;
OutputFileName_update;
OutputFileName_inno;
diff --git a/matlab/priordens.m b/matlab/priordens.m
index f760680cf..866ae11a3 100644
--- a/matlab/priordens.m
+++ b/matlab/priordens.m
@@ -94,7 +94,7 @@ if tt1
end
return
end
- if nargout == 2,
+ if nargout == 2
[tmp, dlprior(id1)]=lpdfgbeta(x(id1),p6(id1),p7(id1),p3(id1),p4(id1));
elseif nargout == 3
[tmp, dlprior(id1), d2lprior(id1)]=lpdfgbeta(x(id1),p6(id1),p7(id1),p3(id1),p4(id1));
@@ -109,7 +109,7 @@ if tt2
end
return
end
- if nargout == 2,
+ if nargout == 2
[tmp, dlprior(id2)]=lpdfgam(x(id2)-p3(id2),p6(id2),p7(id2));
elseif nargout == 3
[tmp, dlprior(id2), d2lprior(id2)]=lpdfgam(x(id2)-p3(id2),p6(id2),p7(id2));
@@ -118,7 +118,7 @@ end
if tt3
logged_prior_density = logged_prior_density + sum(lpdfnorm(x(id3),p6(id3),p7(id3))) ;
- if nargout == 2,
+ if nargout == 2
[tmp, dlprior(id3)]=lpdfnorm(x(id3),p6(id3),p7(id3));
elseif nargout == 3
[tmp, dlprior(id3), d2lprior(id3)]=lpdfnorm(x(id3),p6(id3),p7(id3));
@@ -133,7 +133,7 @@ if tt4
end
return
end
- if nargout == 2,
+ if nargout == 2
[tmp, dlprior(id4)]=lpdfig1(x(id4)-p3(id4),p6(id4),p7(id4));
elseif nargout == 3
[tmp, dlprior(id4), d2lprior(id4)]=lpdfig1(x(id4)-p3(id4),p6(id4),p7(id4));
@@ -149,7 +149,7 @@ if tt5
return
end
logged_prior_density = logged_prior_density + sum(log(1./(p4(id5)-p3(id5)))) ;
- if nargout >1,
+ if nargout >1
dlprior(id5)=zeros(length(id5),1);
end
if nargout == 3
@@ -165,7 +165,7 @@ if tt6
end
return
end
- if nargout == 2,
+ if nargout == 2
[tmp, dlprior(id6)]=lpdfig2(x(id6)-p3(id6),p6(id6),p7(id6));
elseif nargout == 3
[tmp, dlprior(id6), d2lprior(id6)]=lpdfig2(x(id6)-p3(id6),p6(id6),p7(id6));
@@ -187,7 +187,7 @@ if tt8
end
end
-if nargout==3,
+if nargout==3
d2lprior = diag(d2lprior);
end
diff --git a/matlab/qzdiv.m b/matlab/qzdiv.m
index 2c88184f1..3641808a1 100644
--- a/matlab/qzdiv.m
+++ b/matlab/qzdiv.m
@@ -27,7 +27,7 @@ function [A,B,Q,Z] = qzdiv(stake,A,B,Q,Z)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-[n jnk] = size(A);
+[n, jnk] = size(A);
root = abs([diag(A) diag(B)]);
root(:,1) = root(:,1)-(root(:,1)<1.e-13).*(root(:,1)+root(:,2));
root(:,2) = root(:,2)./root(:,1);
@@ -43,7 +43,7 @@ for i = n:-1:1
return
end
for k=m:1:i-1
- [A B Q Z] = qzswitch(k,A,B,Q,Z);
+ [A, B, Q, Z] = qzswitch(k,A,B,Q,Z);
tmp = root(k,2);
root(k,2) = root(k+1,2);
root(k+1,2) = tmp;
diff --git a/matlab/realtime_shock_decomposition.m b/matlab/realtime_shock_decomposition.m
index 2cdb6d949..84b73b217 100644
--- a/matlab/realtime_shock_decomposition.m
+++ b/matlab/realtime_shock_decomposition.m
@@ -69,13 +69,13 @@ if isempty(parameter_set)
end
presample = max(1,options_.presample);
-if isfield(options_.shock_decomp,'presample'),
+if isfield(options_.shock_decomp,'presample')
presample = max(presample,options_.shock_decomp.presample);
end
% forecast_=0;
forecast_ = options_.shock_decomp.forecast;
forecast_params=0;
-if forecast_ && isfield(options_.shock_decomp,'forecast_params'),
+if forecast_ && isfield(options_.shock_decomp,'forecast_params')
forecast_params = options_.shock_decomp.forecast_params;
end
@@ -96,14 +96,14 @@ options_.plot_priors=0;
init=1;
nobs = options_.nobs;
-if forecast_ && any(forecast_params),
+if forecast_ && any(forecast_params)
M1=M_;
M1.params = forecast_params;
[junk1,junk2,junk3,junk4,junk5,junk6,oo1] = dynare_resolve(M1,options_,oo_);
clear junk1 junk2 junk3 junk4 junk5 junk6
end
-for j=presample+1:nobs,
+for j=presample+1:nobs
% evalin('base',['options_.nobs=' int2str(j) ';'])
options_.nobs=j;
[oo, M_, junk2, junk3, Smoothed_Variables_deviation_from_mean] = evaluate_smoother(parameter_set,varlist,M_,oo_,options_,bayestopt_,estim_params_);
@@ -120,8 +120,8 @@ for j=presample+1:nobs,
A = dr.ghx;
B = dr.ghu;
- if forecast_,
- if any(forecast_params),
+ if forecast_
+ if any(forecast_params)
Af = oo1.dr.ghx;
Bf = oo1.dr.ghu;
else
@@ -146,7 +146,7 @@ for j=presample+1:nobs,
k2 = dr.kstate(find(dr.kstate(:,2) <= maximum_lag+1),[1 2]);
i_state = order_var(k2(:,1))+(min(i,maximum_lag)+1-k2(:,2))*M_.endo_nbr;
- for i=1:gend+forecast_,
+ for i=1:gend+forecast_
if i > 1 && i <= maximum_lag+1
lags = min(i-1,maximum_lag):-1:1;
end
@@ -173,7 +173,7 @@ for j=presample+1:nobs,
%% conditional shock decomp 1 step ahead
z1 = zeros(endo_nbr,nshocks+2);
z1(:,end) = Smoothed_Variables_deviation_from_mean(:,gend);
- for i=gend,
+ for i=gend
z1(:,1:nshocks) = z1(:,1:nshocks) + B(inv_order_var,:).*repmat(epsilon(:,i)',endo_nbr,1);
z1(:,nshocks+1) = z1(:,nshocks+2) - sum(z1(:,1:nshocks),2);
@@ -181,10 +181,10 @@ for j=presample+1:nobs,
%%
%% conditional shock decomp k step ahead
- if forecast_ && forecast_<j,
+ if forecast_ && forecast_<j
zn = zeros(endo_nbr,nshocks+2,forecast_+1);
zn(:,end,1:forecast_+1) = Smoothed_Variables_deviation_from_mean(:,gend-forecast_:gend);
- for i=1:forecast_+1,
+ for i=1:forecast_+1
if i > 1 && i <= maximum_lag+1
lags = min(i-1,maximum_lag):-1:1;
end
@@ -205,7 +205,7 @@ for j=presample+1:nobs,
end
%%
- if init,
+ if init
zreal(:,:,1:j) = z(:,:,1:j);
else
zreal(:,:,j) = z(:,:,gend);
@@ -229,7 +229,7 @@ for j=presample+1:nobs,
zreal(:,end,j-forecast_:j);
if j==nobs
- for my_forecast_=(forecast_-1):-1:1,
+ for my_forecast_=(forecast_-1):-1:1
oo_.realtime_conditional_shock_decomposition.(['time_' int2str(j-my_forecast_)]) = ...
zreal(:,:,j-my_forecast_:j) - ...
oo_.realtime_forecast_shock_decomposition.(['time_' int2str(j-my_forecast_)])(:,:,1:my_forecast_+1);
diff --git a/matlab/reduced_rank_cholesky.m b/matlab/reduced_rank_cholesky.m
index 1af9ec609..99e9ea2ec 100644
--- a/matlab/reduced_rank_cholesky.m
+++ b/matlab/reduced_rank_cholesky.m
@@ -87,7 +87,7 @@ end
%$ catch
%$ t(1) = 0;
%$ T = all(t);
-%$ return;
+%$ return
%$ end
%$
%$
diff --git a/matlab/resol.m b/matlab/resol.m
index 0fae31a9e..b1e770f90 100644
--- a/matlab/resol.m
+++ b/matlab/resol.m
@@ -93,7 +93,7 @@ function [dr,info,M,options,oo] = resol(check_flag,M,options,oo)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-if isfield(oo,'dr');
+if isfield(oo,'dr')
dr = oo.dr;
end
diff --git a/matlab/rotated_slice_sampler.m b/matlab/rotated_slice_sampler.m
index 66908d77d..ce6b18235 100644
--- a/matlab/rotated_slice_sampler.m
+++ b/matlab/rotated_slice_sampler.m
@@ -45,13 +45,13 @@ theta=theta(:);
npar = length(theta);
neval = zeros(npar,1);
W1=[];
-if isfield(sampler_options,'WR'),
+if isfield(sampler_options,'WR')
W1 = sampler_options.WR;
end
-if ~isempty(sampler_options.mode),
+if ~isempty(sampler_options.mode)
mm = sampler_options.mode;
n = length(mm);
- for j=1:n,
+ for j=1:n
distance(j)=sqrt(sum((theta-mm(j).m).^2));
end
[m, im] = min(distance);
@@ -59,8 +59,8 @@ if ~isempty(sampler_options.mode),
r=im;
V1 = mm(r).m;
jj=0;
- for j=1:n,
- if j~=r,
+ for j=1:n
+ if j~=r
jj=jj+1;
tmp=mm(j).m-mm(r).m;
%tmp=mm(j).m-theta;
@@ -102,7 +102,7 @@ else
end
npar=size(V1,2);
-for it=1:npar,
+for it=1:npar
theta0 = theta;
neval(it) = 0;
xold = 0;
@@ -111,7 +111,7 @@ for it=1:npar,
tb=sort([(thetaprior(:,1)-theta)./V1(:,it) (thetaprior(:,2)-theta)./V1(:,it)],2);
XLB=max(tb(:,1));
XUB=min(tb(:,2));
- if isempty(W1),
+ if isempty(W1)
W = (XUB-XLB); %*0.8;
else
W = W1(it);
@@ -141,7 +141,7 @@ for it=1:npar,
fxl = -feval(objective_function,theta,varargin{:});
neval(it) = neval(it) + 1;
if (fxl <= Z)
- break;
+ break
end
L = max(XLB,L-W);
end
@@ -151,7 +151,7 @@ for it=1:npar,
fxr = -feval(objective_function,theta,varargin{:});
neval(it) = neval(it) + 1;
if (fxr <= Z)
- break;
+ break
end
R = min(XUB,R+W);
end
diff --git a/matlab/select_from_table.m b/matlab/select_from_table.m
index cc657e934..fa61003f1 100644
--- a/matlab/select_from_table.m
+++ b/matlab/select_from_table.m
@@ -18,7 +18,7 @@ function [indices] = select_from_table(table,key,value)
candidates = table(strmatch(key,table(:,2),'exact'),:);
if nargin == 2
indices = cell2mat( candidates(:,1) );
- return;
+ return
end
indices = candidates(strmatch(value, candidates(:,3), 'exact'),1);
indices = cell2mat(indices);
diff --git a/matlab/set_state_space.m b/matlab/set_state_space.m
index a7d108165..a99a556f5 100644
--- a/matlab/set_state_space.m
+++ b/matlab/set_state_space.m
@@ -73,7 +73,7 @@ if DynareOptions.block == 1
order_var = DynareModel.block_structure.variable_reordered;
else
order_var = [ stat_var(:); pred_var(:); both_var(:); fwrd_var(:)];
-end;
+end
inv_order_var(order_var) = (1:endo_nbr);
% building kmask for z state vector in t+1
diff --git a/matlab/simulated_moment_uncertainty.m b/matlab/simulated_moment_uncertainty.m
index 042f9914a..ef9358a75 100644
--- a/matlab/simulated_moment_uncertainty.m
+++ b/matlab/simulated_moment_uncertainty.m
@@ -94,17 +94,17 @@ else
end
-for j=1:replic;
+for j=1:replic
[ys, oo_] = simult(y0,oo_.dr,M_,options_,oo_);%do simulation
oo_=disp_moments(ys,char(options_.varobs),M_,options_,oo_); %get moments
dum=[oo_.mean; dyn_vech(oo_.var)];
sd = sqrt(diag(oo_.var));
- for i=1:options_.ar;
+ for i=1:options_.ar
dum=[dum; vec(oo_.autocorr{i}.*(sd*sd'))];
end
mm(:,j)=dum(indx);
dyn_waitbar(j/replic,h,['Simulated moment uncertainty. Replic ',int2str(j),'/',int2str(replic)])
-end;
+end
dyn_waitbar_close(h);
if logged_steady_state_indicator
diff --git a/matlab/simulated_moments_estimation.m b/matlab/simulated_moments_estimation.m
index 314122d83..62f077de8 100644
--- a/matlab/simulated_moments_estimation.m
+++ b/matlab/simulated_moments_estimation.m
@@ -282,7 +282,7 @@ fprintf(fid,[' time_series = extended_path([],' int2str(sample_size) ',1);\n'
fprintf(fid,[' data = time_series([' int2str(observed_variables_idx) '],' int2str(burn_in_periods) '+1:' int2str(sample_size) ');\n']);
fprintf(fid,[' eval(''tmp = ' moments_file_name '(data);'');\n']);
fprintf(fid,[' simulated_moments = simulated_moments + tmp;\n']);
-fprintf(fid,['end;\n\n']);
+fprintf(fid,['end\n\n']);
fprintf(fid,['simulated_moments = simulated_moments/' int2str(number_of_simulations) ';\n']);
fprintf(fid,['save(''simulated_moments_slave_' int2str(slave_number) '.dat'',''simulated_moments'',''-ascii'');\n']);
diff --git a/matlab/simult_.m b/matlab/simult_.m
index 31daa3a6c..ff0b42f9e 100644
--- a/matlab/simult_.m
+++ b/matlab/simult_.m
@@ -77,14 +77,14 @@ else
k2 = dr.state_var;
else
k2 = [];
- end;
+ end
order_var = 1:endo_nbr;
dr.order_var = order_var;
else
k2 = dr.kstate(find(dr.kstate(:,2) <= M_.maximum_lag+1),[1 2]);
k2 = k2(:,1)+(M_.maximum_lag+1-k2(:,2))*endo_nbr;
order_var = dr.order_var;
- end;
+ end
switch iorder
case 1
diff --git a/matlab/slice_sampler.m b/matlab/slice_sampler.m
index e454d5936..ef524fd4e 100644
--- a/matlab/slice_sampler.m
+++ b/matlab/slice_sampler.m
@@ -43,8 +43,8 @@ function [theta, fxsim, neval] = slice_sampler(objective_function,theta,thetapri
if sampler_options.rotated %&& ~isempty(sampler_options.V1),
[theta, fxsim, neval] = rotated_slice_sampler(objective_function,theta,thetaprior,sampler_options,varargin{:});
- if isempty(sampler_options.mode), % jumping
- return,
+ if isempty(sampler_options.mode) % jumping
+ return
else
nevalR=sum(neval);
end
@@ -55,7 +55,7 @@ npar = length(theta);
W1 = sampler_options.W1;
neval = zeros(npar,1);
-for it=1:npar,
+for it=1:npar
neval(it) = 0;
W = W1(it);
xold = theta(it);
@@ -85,7 +85,7 @@ for it=1:npar,
fxl = -feval(objective_function,theta,varargin{:});
neval(it) = neval(it) + 1;
if (fxl <= Z)
- break;
+ break
end
L = max(XLB,L-W);
end
@@ -95,7 +95,7 @@ for it=1:npar,
fxr = -feval(objective_function,theta,varargin{:});
neval(it) = neval(it) + 1;
if (fxr <= Z)
- break;
+ break
end
R = min(XUB,R+W);
end
@@ -118,6 +118,6 @@ for it=1:npar,
end
-if sampler_options.rotated && ~isempty(sampler_options.mode), % jumping
+if sampler_options.rotated && ~isempty(sampler_options.mode) % jumping
neval=sum(neval)+nevalR;
end
diff --git a/matlab/smm_objective.m b/matlab/smm_objective.m
index 030cb98d9..46a941b47 100644
--- a/matlab/smm_objective.m
+++ b/matlab/smm_objective.m
@@ -68,7 +68,7 @@ end
if penalty>0
flag = 0;
r = priorObjectiveValue + penalty;
- return;
+ return
end
save('estimated_parameters.mat','xparams');
diff --git a/matlab/solve1.m b/matlab/solve1.m
index 5d5241fce..6ce89ca62 100644
--- a/matlab/solve1.m
+++ b/matlab/solve1.m
@@ -59,7 +59,7 @@ if ~isempty(i)
'equation(s) resulted in a non-finite number:'])
disp(j1(i)')
check = 1;
- return;
+ return
end
f = 0.5*(fvec'*fvec) ;
diff --git a/matlab/solve_one_boundary.m b/matlab/solve_one_boundary.m
index 2ce90c7bc..261ab3018 100644
--- a/matlab/solve_one_boundary.m
+++ b/matlab/solve_one_boundary.m
@@ -387,7 +387,7 @@ for it_=start:incr:finish
oo_.deterministic_simulation.block(Block_Num).status = 0;% Convergency failed.
oo_.deterministic_simulation.block(Block_Num).error = max_res;
oo_.deterministic_simulation.block(Block_Num).iterations = iter;
- end;
+ end
info = -Block_Num*10;
return
end
diff --git a/matlab/solve_perfect_foresight_model.m b/matlab/solve_perfect_foresight_model.m
index 5de112ad8..02a6c234f 100644
--- a/matlab/solve_perfect_foresight_model.m
+++ b/matlab/solve_perfect_foresight_model.m
@@ -34,7 +34,7 @@ function [flag,endo_simul,err] = solve_perfect_foresight_model(endo_simul,exo_si
if pfm.use_bytecode
[flag, endo_simul]=bytecode(Y, exo_simul, pfm.params);
- return;
+ return
end
z = Y(find(pfm.lead_lag_incidence'));
diff --git a/matlab/solve_two_boundaries.m b/matlab/solve_two_boundaries.m
index 136d3e1ac..7f0df6530 100644
--- a/matlab/solve_two_boundaries.m
+++ b/matlab/solve_two_boundaries.m
@@ -92,7 +92,7 @@ while ~(cvg==1 || iter>maxit_)
[max_res, max_indx]=max(max(abs(r')));
if ~isreal(r)
max_res = (-max_res^2)^0.5;
- end;
+ end
if ~isreal(max_res) || isnan(max_res)
cvg = 0;
elseif(is_linear && iter>0)
@@ -123,7 +123,7 @@ while ~(cvg==1 || iter>maxit_)
end
dx = (g1aa+correcting_factor*speye(periods*Blck_size))\ba- ya;
y(1+y_kmin:periods+y_kmin,y_index)=reshape((ya_save+lambda*dx)',length(y_index),periods)';
- continue;
+ continue
else
disp('The singularity of the jacobian matrix could not be corrected');
return
@@ -178,7 +178,7 @@ while ~(cvg==1 || iter>maxit_)
B1_inv = inv(g1a(Elem, Elem));
if (t < periods)
S1 = B1_inv * g1a(Elem, Elem_1);
- end;
+ end
g1a(Elem, Elem_1) = S1;
b(Elem) = B1_inv * b(Elem);
g1a(Elem, Elem) = ones(Blck_size, Blck_size);
diff --git a/matlab/stoch_simul.m b/matlab/stoch_simul.m
index 5465eaa96..b77cacc3a 100644
--- a/matlab/stoch_simul.m
+++ b/matlab/stoch_simul.m
@@ -324,7 +324,7 @@ if options_.irf
end
hh = dyn_figure(options_.nodisplay,'Name',['Orthogonalized shock to ' tit(i,:) ' figure ' int2str(nbplt) '.']);
m = 0;
- for plt = 1:number_of_plots_to_draw-(nbplt-1)*nstar;
+ for plt = 1:number_of_plots_to_draw-(nbplt-1)*nstar
m = m+1;
subplot(lr,lc,m);
plot(1:options_.irf,transpose(irfs((nbplt-1)*nstar+plt,:)),'-k','linewidth',1);
diff --git a/matlab/stochastic_solvers.m b/matlab/stochastic_solvers.m
index 7332654a8..b7da41258 100644
--- a/matlab/stochastic_solvers.m
+++ b/matlab/stochastic_solvers.m
@@ -85,7 +85,7 @@ if M_.maximum_endo_lead==0 && M_.exo_det_nbr~=0
error(['var_exo_det not implemented for purely backwards models'])
end
-if options_.k_order_solver;
+if options_.k_order_solver
if options_.risky_steadystate
[dr,info] = dyn_risky_steadystate_solver(oo_.steady_state,M_,dr, ...
options_,oo_);
@@ -96,7 +96,7 @@ if options_.k_order_solver;
[dr,info] = k_order_pert(dr,M_,options_);
options_.order = orig_order;
end
- return;
+ return
end
klen = M_.maximum_lag + M_.maximum_lead + 1;
@@ -120,7 +120,7 @@ if local_order == 1
else
[junk,jacobia_] = feval([M_.fname '_dynamic'],z(iyr0),exo_simul, ...
M_.params, dr.ys, it_);
- end;
+ end
elseif local_order == 2
if (options_.bytecode)
[chck, junk, loc_dr] = bytecode('dynamic','evaluate', z,exo_simul, ...
@@ -130,7 +130,7 @@ elseif local_order == 2
[junk,jacobia_,hessian1] = feval([M_.fname '_dynamic'],z(iyr0),...
exo_simul, ...
M_.params, dr.ys, it_);
- end;
+ end
if options_.use_dll
% In USE_DLL mode, the hessian is in the 3-column sparse representation
hessian1 = sparse(hessian1(:,1), hessian1(:,2), hessian1(:,3), ...
@@ -263,7 +263,7 @@ else
else % use original Dynare solver
[dr,info] = dyn_first_order_solver(jacobia_,M_,dr,options_,task);
if info(1) || task
- return;
+ return
end
end
diff --git a/matlab/th_autocovariances.m b/matlab/th_autocovariances.m
index 966ece834..cac209729 100644
--- a/matlab/th_autocovariances.m
+++ b/matlab/th_autocovariances.m
@@ -114,7 +114,7 @@ else
trend = 1:M_.endo_nbr;
inv_order_var = trend(M_.block_structure.variable_reordered);
ghu1(1:length(dr.state_var),:) = ghu(dr.state_var,:);
-end;
+end
b = ghu1*M_.Sigma_e*ghu1';
@@ -122,7 +122,7 @@ if options_.block == 0
ipred = nstatic+(1:nspred)';
else
ipred = dr.state_var;
-end;
+end
% state space representation for state variables only
[A,B] = kalman_transition_matrix(dr,ipred,1:nx,M_.exo_nbr);
% Compute stationary variables (before HP filtering),
@@ -134,7 +134,7 @@ if options_.order == 2 || options_.hp_filter == 0
iky = inv_order_var(ivar);
else
iky = ivar;
- end;
+ end
stationary_vars = (1:length(ivar))';
if ~isempty(u)
x = abs(ghx*u);
@@ -233,7 +233,7 @@ else% ==> Theoretical filters.
IA = eye(size(A,1));
IE = eye(M_.exo_nbr);
for ig = 1:ngrid
- if filter_gain(ig)==0,
+ if filter_gain(ig)==0
f_hp = zeros(length(ivar),length(ivar));
else
f_omega =(1/(2*pi))*([(IA-A*tneg(ig))\ghu1;IE]...
@@ -242,7 +242,7 @@ else% ==> Theoretical filters.
f_hp = filter_gain(ig)^2*g_omega; % spectral density of selected filtered series; top formula Uhlig (2001), p. 21;
end
mathp_col(ig,:) = (f_hp(:))'; % store as matrix row for ifft
- end;
+ end
% Covariance of filtered series
imathp_col = real(ifft(mathp_col))*(2*pi); % Inverse Fast Fourier Transformation; middle formula Uhlig (2001), p. 21;
Gamma_y{1} = reshape(imathp_col(1,:),nvar,nvar);
@@ -269,7 +269,7 @@ else% ==> Theoretical filters.
IA = eye(size(A,1));
IE = eye(M_.exo_nbr);
for ig = 1:ngrid
- if filter_gain(ig)==0,
+ if filter_gain(ig)==0
f_hp = zeros(length(ivar),length(ivar));
else
f_omega =(1/(2*pi))*( [(IA-A*tneg(ig))\b1;IE]...
@@ -278,14 +278,14 @@ else% ==> Theoretical filters.
f_hp = filter_gain(ig)^2*g_omega; % spectral density of selected filtered series; top formula Uhlig (2001), p. 21;
end
mathp_col(ig,:) = (f_hp(:))'; % store as matrix row for ifft
- end;
+ end
imathp_col = real(ifft(mathp_col))*(2*pi);
vv = diag(reshape(imathp_col(1,:),nvar,nvar));
for i=1:M_.exo_nbr
mathp_col = NaN(ngrid,length(ivar)^2);
SSi = cs(:,i)*cs(:,i)';
for ig = 1:ngrid
- if filter_gain(ig)==0,
+ if filter_gain(ig)==0
f_hp = zeros(length(ivar),length(ivar));
else
f_omega =(1/(2*pi))*( [(IA-A*tneg(ig))\b1;IE]...
@@ -294,7 +294,7 @@ else% ==> Theoretical filters.
f_hp = filter_gain(ig)^2*g_omega; % spectral density of selected filtered series; top formula Uhlig (2001), p. 21;
end
mathp_col(ig,:) = (f_hp(:))'; % store as matrix row for ifft
- end;
+ end
imathp_col = real(ifft(mathp_col))*(2*pi);
Gamma_y{nar+2}(:,i) = abs(diag(reshape(imathp_col(1,:),nvar,nvar)))./vv;
end
diff --git a/matlab/thet2tau.m b/matlab/thet2tau.m
index 929193ca4..2fc9625c8 100644
--- a/matlab/thet2tau.m
+++ b/matlab/thet2tau.m
@@ -20,22 +20,22 @@ function tau = thet2tau(params, estim_params_, M_, oo_, indx, indexo, flagmoment
global options_
-if nargin==1,
+if nargin==1
indx = [1:M_.param_nbr];
indexo = [];
end
-if nargin<7,
+if nargin<7
flagmoments=0;
end
-if nargin<10 || isempty(useautocorr),
+if nargin<10 || isempty(useautocorr)
useautocorr=0;
end
-if nargin<11 || isempty(iv),
+if nargin<11 || isempty(iv)
iv=[1:M_.endo_nbr];
end
-if length(params)>length(indx),
+if length(params)>length(indx)
M_ = set_all_parameters(params,estim_params_,M_);
else
M_.params(indx) = params;
@@ -44,7 +44,7 @@ end
% M_.Sigma_e(indexo,indexo) = diag(params(1:length(indexo)).^2);
% end
[A,B,tele,tubbies,M_,options_,oo_] = dynare_resolve(M_,options_,oo_);
-if flagmoments==0,
+if flagmoments==0
ys=oo_.dr.ys(oo_.dr.order_var);
tau = [ys(iv); vec(A(iv,iv)); dyn_vech(B(iv,:)*M_.Sigma_e*B(iv,:)')];
elseif flagmoments==-1
@@ -58,7 +58,7 @@ else
GAM = lyapunov_symm(A,B*M_.Sigma_e*B',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,[],options_.debug);
k = find(abs(GAM) < 1e-12);
GAM(k) = 0;
- if useautocorr,
+ if useautocorr
sy = sqrt(diag(GAM));
sy = sy*sy';
sy0 = sy-diag(diag(sy))+eye(length(sy));
@@ -69,7 +69,7 @@ else
end
for ii = 1:nlags
dum = A^(ii)*GAM;
- if useautocorr,
+ if useautocorr
dum = dum./sy;
end
tau = [tau;vec(dum(mf,mf))];
diff --git a/matlab/trust_region.m b/matlab/trust_region.m
index 02acae0c5..5e21d0fbb 100644
--- a/matlab/trust_region.m
+++ b/matlab/trust_region.m
@@ -150,7 +150,7 @@ while (niter < maxiter && ~info)
else
info = -3;
end
- break;
+ break
end
elseif (abs (1-ratio) <= 0.1)
delta = 1.4142*sn;
diff --git a/matlab/user_has_matlab_license.m b/matlab/user_has_matlab_license.m
index 86b8c94bd..190589392 100644
--- a/matlab/user_has_matlab_license.m
+++ b/matlab/user_has_matlab_license.m
@@ -31,7 +31,7 @@ function [hasLicense] = user_has_matlab_license(toolbox)
if matlab_ver_less_than('7.12')
hasLicense = license('test', toolbox);
else
- [hasLicense junk] = license('checkout',toolbox);
+ [hasLicense, junk] = license('checkout',toolbox);
end
if ~hasLicense
return
@@ -50,7 +50,7 @@ end
hasInstallation=check_toolbox_installation(n);
if ~hasInstallation
hasLicense=0;
- return;
+ return
end
end
diff --git a/matlab/utilities/dataset/lagged.m b/matlab/utilities/dataset/lagged.m
index 31a58909a..fa84577e2 100644
--- a/matlab/utilities/dataset/lagged.m
+++ b/matlab/utilities/dataset/lagged.m
@@ -1,4 +1,4 @@
-function xlag = lagged(x, n);
+function xlag = lagged(x, n)
% xlag = lagged(x, n);
% applies n-lags backward shift operator to x
%
@@ -26,7 +26,9 @@ function xlag = lagged(x, n);
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-if nargin==1, n=1; end
+if nargin==1
+ n=1;
+end
x=x(:);
-xlag=[NaN(n,1); x(1:end-n)];
+xlag=[NaN(n,1); x(1:end-n)];
\ No newline at end of file
diff --git a/matlab/utilities/dataset/quarterly2annual.m b/matlab/utilities/dataset/quarterly2annual.m
index cc655f1e0..c74111bf9 100644
--- a/matlab/utilities/dataset/quarterly2annual.m
+++ b/matlab/utilities/dataset/quarterly2annual.m
@@ -43,18 +43,18 @@ function [ya, yass, gya, gyass] = quarterly2annual(y,yss,GYTREND0,type,islog,aux
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-if nargin ==0,
+if nargin ==0
disp('[ya, yass, gya, gyass] = quarterly2annual(y,yss,GYTREND0,type,islog);')
return
end
-if nargin<4 || isempty(type),
+if nargin<4 || isempty(type)
type=1;
end
-if nargin<5 || isempty(islog),
+if nargin<5 || isempty(islog)
islog=0;
end
-if isstruct(aux),
+if isstruct(aux)
yaux=aux.y;
yauxss=aux.yss;
islogaux=aux.islog;
@@ -65,10 +65,10 @@ if isstruct(aux),
yauxss=exp(yauxss);
yaux=yaux-yauxss;
end
-elseif type > 4,
+elseif type > 4
error('TYPE>4 requires auxiliary variable!')
end
-if islog == 2,
+if islog == 2
% construct loglevel out of growth rate
y = cumsum(y);
yss=0;
@@ -80,28 +80,23 @@ if islog == 1
y=y-yss;
end
switch type
-
case 1
yass = yss*(exp(-GYTREND0*3)+exp(-GYTREND0*2)+exp(-GYTREND0)+1);
tmp = lagged(y,3)*exp(-GYTREND0*3)+lagged(y,2)*exp(-GYTREND0*2)+lagged(y,1)*exp(-GYTREND0)+y; % annualized level
ya = tmp(4:4:end);
-
case 2
yass = yss*(exp(-GYTREND0*3)+exp(-GYTREND0*2)+exp(-GYTREND0)+1)/4;
tmp = (lagged(y,3)*exp(-GYTREND0*3)+lagged(y,2)*exp(-GYTREND0*2)+lagged(y,1)*exp(-GYTREND0)+y)/4; % annualized level
ya = tmp(4:4:end);
-
case 3
yass=yss;
tmp = y;
ya = tmp(4:4:end);
-
case 4
yass = yss*(exp(-GYTREND0*3/2));
tmp = (lagged(y+yss,3)*exp(-GYTREND0*3).*lagged(y+yss,2)*exp(-GYTREND0*2).*lagged(y+yss,1)*exp(-GYTREND0).*(y+yss)).^(1/4); % annualized level
tmp = tmp - yass;
ya = tmp(4:4:end);
-
case 5
% nominal series
yn = (y+yss).*(yaux+yauxss) - yss.*yauxss;
@@ -111,7 +106,6 @@ switch type
% deflator
yass = ynass/yrass;
ya = (yna+ynass)./(yr+yrass)-yass;
-
case 6
% nominal series
yn = (y+yss).*(yaux+yauxss) - yss.*yauxss;
@@ -121,13 +115,11 @@ switch type
% real series
yass = ynass/pass;
ya = (yna+ynass)./(pa+pass)-yass;
-
case 7
% nominal series
yn = (y+yss).*(yaux+yauxss) - yss.*yauxss;
[ya, yass] = quarterly2annual(yn,yss.*yauxss,GYTREND0+GYTREND0aux,typeaux,0,0);
GYTREND0=GYTREND0+GYTREND0aux;
-
otherwise
error('Wrong type input')
end
diff --git a/matlab/utilities/graphics/colorspace.m b/matlab/utilities/graphics/colorspace.m
index dc46d5e85..a26091472 100644
--- a/matlab/utilities/graphics/colorspace.m
+++ b/matlab/utilities/graphics/colorspace.m
@@ -155,7 +155,7 @@ else
varargout = {Image};
end
-return;
+return
function [SrcSpace,DestSpace] = parse(Str)
@@ -186,7 +186,7 @@ else
DestSpace = Conversion;
if any(size(Conversion) ~= 3), error('Transformation matrix must be 3x3.'); end
end
-return;
+return
function Space = alias(Space)
@@ -204,9 +204,9 @@ case {'hsv','hsb'}
case {'hsl','hsi','hls'}
Space = 'hsl';
case {'rgb','yuv','yiq','ydbdr','ycbcr','jpegycbcr','xyz','lab','luv','lch'}
- return;
+ return
end
-return;
+return
function T = gettransform(Space)
@@ -240,14 +240,14 @@ case {'rgb','xyz','hsv','hsl','lab','luv','lch','cat02lms'}
otherwise
error(['Unknown color space, ''',Space,'''.']);
end
-return;
+return
function Image = rgb(Image,SrcSpace)
% Convert to sRGB from 'SrcSpace'
switch SrcSpace
case 'rgb'
- return;
+ return
case 'hsv'
% Convert HSV to sRGB
Image = huetorgb((1 - Image(:,:,2)).*Image(:,:,3),Image(:,:,3),Image(:,:,1));
@@ -287,7 +287,7 @@ end
% Clip to [0,1]
Image = min(max(Image,0),1);
-return;
+return
function Image = xyz(Image,SrcSpace)
@@ -296,7 +296,7 @@ WhitePoint = [0.950456,1,1.088754];
switch SrcSpace
case 'xyz'
- return;
+ return
case 'luv'
% Convert CIE L*uv to XYZ
WhitePointU = (4*WhitePoint(1))./(WhitePoint(1) + 15*WhitePoint(2) + 3*WhitePoint(3));
@@ -340,7 +340,7 @@ otherwise % Convert from some gamma-corrected space
Image(:,:,2) = T(2)*R + T(5)*G + T(8)*B; % Y
Image(:,:,3) = T(3)*R + T(6)*G + T(9)*B; % Z
end
-return;
+return
function Image = hsv(Image,SrcSpace)
@@ -351,7 +351,7 @@ S = (V - min(Image,[],3))./(V + (V == 0));
Image(:,:,1) = rgbtohue(Image);
Image(:,:,2) = S;
Image(:,:,3) = V;
-return;
+return
function Image = hsl(Image,SrcSpace)
@@ -377,7 +377,7 @@ otherwise
Image(:,:,2) = S;
Image(:,:,3) = L;
end
-return;
+return
function Image = lab(Image,SrcSpace)
@@ -386,7 +386,7 @@ WhitePoint = [0.950456,1,1.088754];
switch SrcSpace
case 'lab'
- return;
+ return
case 'lch'
% Convert CIE L*CH to CIE L*ab
C = Image(:,:,2);
@@ -405,7 +405,7 @@ otherwise
Image(:,:,2) = 500*(fX - fY); % a*
Image(:,:,3) = 200*(fY - fZ); % b*
end
-return;
+return
function Image = luv(Image,SrcSpace)
@@ -423,7 +423,7 @@ L = 116*f(Y) - 16;
Image(:,:,1) = L; % L*
Image(:,:,2) = 13*L.*(U - WhitePointU); % u*
Image(:,:,3) = 13*L.*(V - WhitePointV); % v*
-return;
+return
function Image = lch(Image,SrcSpace)
@@ -433,7 +433,7 @@ H = atan2(Image(:,:,3),Image(:,:,2));
H = H*180/pi + 360*(H < 0);
Image(:,:,2) = sqrt(Image(:,:,2).^2 + Image(:,:,3).^2); % C
Image(:,:,3) = H; % H
-return;
+return
function Image = cat02lms(Image,SrcSpace)
@@ -446,7 +446,7 @@ Z = Image(:,:,3);
Image(:,:,1) = T(1)*X + T(4)*Y + T(7)*Z; % L
Image(:,:,2) = T(2)*X + T(5)*Y + T(8)*Z; % M
Image(:,:,3) = T(3)*X + T(6)*Y + T(9)*Z; % S
-return;
+return
function Image = huetorgb(m0,m2,H)
@@ -461,7 +461,7 @@ Num = length(m0);
j = [2 1 0;1 2 0;0 2 1;0 1 2;1 0 2;2 0 1;2 1 0]*Num;
k = floor(H) + 1;
Image = reshape([M(j(k,1)+(1:Num).'),M(j(k,2)+(1:Num).'),M(j(k,3)+(1:Num).')],[N,3]);
-return;
+return
function H = rgbtohue(Image)
@@ -482,7 +482,7 @@ k = (i == 3);
H(k) = 4 + (R(k) - G(k))./Delta(k);
H = 60*H + 360*(H < 0);
H(Delta == 0) = nan;
-return;
+return
function Rp = gammacorrection(R)
@@ -490,7 +490,7 @@ Rp = zeros(size(R));
i = (R <= 0.0031306684425005883);
Rp(i) = 12.92*R(i);
Rp(~i) = real(1.055*R(~i).^0.416666666666666667 - 0.055);
-return;
+return
function R = invgammacorrection(Rp)
@@ -498,18 +498,18 @@ R = zeros(size(Rp));
i = (Rp <= 0.0404482362771076);
R(i) = Rp(i)/12.92;
R(~i) = real(((Rp(~i) + 0.055)/1.055).^2.4);
-return;
+return
function fY = f(Y)
fY = real(Y.^(1/3));
i = (Y < 0.008856);
fY(i) = Y(i)*(841/108) + (4/29);
-return;
+return
function Y = invf(fY)
Y = fY.^3;
i = (Y < 0.008856);
Y(i) = (fY(i) - 4/29)*(108/841);
-return;
+return
diff --git a/matlab/utilities/graphics/distinguishable_colors.m b/matlab/utilities/graphics/distinguishable_colors.m
index 0b9fb7a33..cf45e582d 100644
--- a/matlab/utilities/graphics/distinguishable_colors.m
+++ b/matlab/utilities/graphics/distinguishable_colors.m
@@ -162,9 +162,9 @@ k = find(cspec==c(1));
if isempty(k)
error('MATLAB:InvalidColorString','Unknown color string.');
end
-if k~=3 || length(c)==1,
+if k~=3 || length(c)==1
c = rgbspec(k,:);
-elseif length(c)>2,
+elseif length(c)>2
if strcmpi(c(1:3),'bla')
c = [0 0 0];
elseif strcmpi(c(1:3),'blu')
diff --git a/matlab/ver_greater_than.m b/matlab/ver_greater_than.m
index 1fef34bf2..9388d15ef 100644
--- a/matlab/ver_greater_than.m
+++ b/matlab/ver_greater_than.m
@@ -36,27 +36,27 @@ ver2 = strsplit(ver2, {'.', '-'});
maj_ver1 = str2double(ver1{1});
maj_ver2 = str2double(ver2{1});
if maj_ver1 > maj_ver2
- return;
+ return
end
min_ver1 = str2double(ver1{2});
min_ver2 = str2double(ver2{2});
if (maj_ver1 == maj_ver2) && (min_ver1 > min_ver2)
- return;
+ return
end
if (length(ver1) == length(ver2) && length(ver1) == 3)
ismaster1 = isnan(str2double(ver1{3}));
ismaster2 = isnan(str2double(ver2{3}));
if (maj_ver1 == maj_ver2) && (min_ver1 == min_ver2) && (ismaster1 && ~ismaster2)
- return;
+ return
end
if ~ismaster1 && ~ismaster2
rev_ver1 = str2double(ver1{3});
rev_ver2 = str2double(ver2{3});
if (maj_ver1 == maj_ver2) && (min_ver1 == min_ver2) && (rev_ver1 > rev_ver2)
- return;
+ return
end
end
end
diff --git a/matlab/ver_less_than.m b/matlab/ver_less_than.m
index e953ed8a2..d67ad82ff 100644
--- a/matlab/ver_less_than.m
+++ b/matlab/ver_less_than.m
@@ -36,27 +36,27 @@ ver2 = strsplit(ver2, {'.', '-'});
maj_ver1 = str2double(ver1{1});
maj_ver2 = str2double(ver2{1});
if maj_ver1 < maj_ver2
- return;
+ return
end
min_ver1 = str2double(ver1{2});
min_ver2 = str2double(ver2{2});
if (maj_ver1 == maj_ver2) && (min_ver1 < min_ver2)
- return;
+ return
end
if (length(ver1) == length(ver2) && length(ver1) == 3)
ismaster1 = isnan(str2double(ver1{3}));
ismaster2 = isnan(str2double(ver2{3}));
if (maj_ver1 == maj_ver2) && (min_ver1 == min_ver2) && (~ismaster1 && ismaster2)
- return;
+ return
end
if ~ismaster1 && ~ismaster2
rev_ver1 = str2double(ver1{3});
rev_ver2 = str2double(ver2{3});
if (maj_ver1 == maj_ver2) && (min_ver1 == min_ver2) && (rev_ver1 < rev_ver2)
- return;
+ return
end
end
end
diff --git a/matlab/write_latex_parameter_table.m b/matlab/write_latex_parameter_table.m
index c2d739801..423d00128 100644
--- a/matlab/write_latex_parameter_table.m
+++ b/matlab/write_latex_parameter_table.m
@@ -29,7 +29,7 @@ function write_latex_parameter_table
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-global M_;
+global M_
if ~isequal(M_.param_names,M_.param_names_long)
Long_names_present=1;
@@ -38,7 +38,7 @@ else
end
fid = fopen([M_.fname '_latex_parameters.tex'], 'w');
fprintf(fid, '\\begin{center}\n');
-if Long_names_present==1;
+if Long_names_present==1
fprintf(fid, '\\begin{longtable}{ccc}\n');
else
fprintf(fid, '\\begin{longtable}{cc}\n');
@@ -48,7 +48,7 @@ fprintf(fid, ['\\caption{Parameter Values}\\\\%%\n']);
fprintf(fid, '\\toprule%%\n');
fprintf(fid, '\\multicolumn{1}{c}{\\textbf{Parameter}} &\n');
fprintf(fid, '\\multicolumn{1}{c}{\\textbf{Value}} ');
-if Long_names_present==1;
+if Long_names_present==1
fprintf(fid, '&\n \\multicolumn{1}{c}{\\textbf{Description}}\\\\%%\n');
else
fprintf(fid, ' \\\\%%\n');
@@ -56,7 +56,7 @@ end
fprintf(fid, '\\midrule%%\n');
fprintf(fid, '\\endfirsthead\n');
-if Long_names_present==1;
+if Long_names_present==1
fprintf(fid, '\\multicolumn{3}{c}{{\\tablename} \\thetable{} -- Continued}\\\\%%\n');
else
fprintf(fid, '\\multicolumn{2}{c}{{\\tablename} \\thetable{} -- Continued}\\\\%%\n');
@@ -64,7 +64,7 @@ end
fprintf(fid, '\\midrule%%\n');
fprintf(fid, '\\multicolumn{1}{c}{\\textbf{Parameter}} &\n');
fprintf(fid, '\\multicolumn{1}{c}{\\textbf{Value}} ');
-if Long_names_present==1;
+if Long_names_present==1
fprintf(fid, '&\n \\multicolumn{1}{c}{\\textbf{Description}}\\\\%%\n');
else
fprintf(fid, '\\\\%%\n');
@@ -75,7 +75,7 @@ fprintf(fid, '\\endhead\n');
tex = M_.param_names_tex;
long = M_.param_names_long;
for j=1:size(tex,1)
-if Long_names_present==1;
+if Long_names_present==1
% replace underscores
long_names_temp=regexprep(strtrim(long(j,:)), '_', '\\_');
% replace percent
diff --git a/matlab/writedata_text.m b/matlab/writedata_text.m
index 5af543e9c..9def1a107 100644
--- a/matlab/writedata_text.m
+++ b/matlab/writedata_text.m
@@ -32,7 +32,7 @@ S=[fname '_endo.dat'];
fid = fopen(S,'w');
for i = 1:size(M_.endo_names,1)
fprintf(fid,'%s ',M_.endo_names(i,:)');
-end;
+end
fprintf(fid,'\n');
for i = 1:size(oo_.endo_simul,2)
fprintf(fid,'%15.7f ',oo_.endo_simul(:,i));
@@ -44,11 +44,10 @@ S=[fname '_exo.dat'];
fid = fopen(S,'w');
for i = 1:size(M_.exo_names,1)
fprintf(fid,'%s ',M_.exo_names(i,:));
-end;
+end
fprintf(fid,'\n');
for i = 1:size(oo_.exo_simul,1)
fprintf(fid,'%15.7f ',oo_.exo_simul(i,:));
fprintf(fid,'\n');
end
-fclose(fid);
-return;
\ No newline at end of file
+fclose(fid);
\ No newline at end of file
--
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