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Use cells of strings instead of char arrays.

time-shift
Stéphane Adjemian (Scylla) 2017-10-10 10:05:59 +02:00 committed by Stéphane Adjemian (Charybdis)
parent 2be12bd50d
commit 7be8f10e0e
188 changed files with 2024 additions and 2181 deletions
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6
examples/NK_baseline_steadystate.m
View File

@ -17,7 +17,7 @@ global M_
% read out parameters to access them with their name
NumberOfParameters = M_.param_nbr;
for ii = 1:NumberOfParameters
paramname = deblank(M_.param_names(ii,:));
paramname = M_.param_names{ii};
eval([ paramname ' = M_.params(' int2str(ii) ');']);
end
% initialize indicator
@ -96,11 +96,11 @@ g2=epsilon/(epsilon-1)*g1;
%% end own model equations
for iter = 1:length(M_.params) %update parameters set in the file
eval([ 'M_.params(' num2str(iter) ') = ' M_.param_names(iter,:) ';' ])
eval([ 'M_.params(' num2str(iter) ') = ' M_.param_names{iter} ';' ])
end
NumberOfEndogenousVariables = M_.orig_endo_nbr; %auxiliary variables are set automatically
for ii = 1:NumberOfEndogenousVariables
varname = deblank(M_.endo_names(ii,:));
varname = M_.endo_names{ii};
eval(['ys(' int2str(ii) ') = ' varname ';']);
end

252
matlab/GetPosteriorParametersStatistics.m
View File

@ -8,7 +8,7 @@ function oo_ = GetPosteriorParametersStatistics(estim_params_, M_, options_, bay
% options_ [structure]
% bayestopt_ [structure]
% oo_ [structure]
% pnames [char] Array of char, names of the prior shapes available
% pnames [cell] cell of strings, names of the prior shapes available
%
% OUTPUTS
% oo_ [structure]
@ -16,7 +16,7 @@ function oo_ = GetPosteriorParametersStatistics(estim_params_, M_, options_, bay
% SPECIAL REQUIREMENTS
% None.
% Copyright (C) 2006-2017 Dynare Team
% Copyright (C) 2006-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -60,7 +60,7 @@ FirstMhFile = record.KeepedDraws.FirstMhFile;
NumberOfDraws = TotalNumberOfMhDraws-floor(options_.mh_drop*TotalNumberOfMhDraws);
clear record;
header_width = row_header_width(M_,estim_params_,bayestopt_);
header_width = row_header_width(M_, estim_params_, bayestopt_);
hpd_interval=[num2str(options_.mh_conf_sig*100), '% HPD interval'];
tit2 = sprintf('%-*s %12s %12s %23s %8s %12s\n',header_width,' ','prior mean','post. mean',hpd_interval,'prior','pstdev');
pformat = '%-*s %12.3f % 12.4f %11.4f %11.4f %7s %12.4f';
@ -70,23 +70,26 @@ disp('ESTIMATION RESULTS')
skipline()
try
disp(sprintf('Log data density is %f.',oo_.MarginalDensity.ModifiedHarmonicMean))
disp(sprintf('Log data density is %f.', oo_.MarginalDensity.ModifiedHarmonicMean))
catch
[marginal,oo_] = marginal_density(M_, options_, estim_params_, oo_, bayestopt_);
disp(sprintf('Log data density is %f.',oo_.MarginalDensity.ModifiedHarmonicMean))
disp(sprintf('Log data density is %f.', oo_.MarginalDensity.ModifiedHarmonicMean))
end
num_draws=NumberOfDraws*options_.mh_nblck;
hpd_draws = round((1-options_.mh_conf_sig)*num_draws);
if hpd_draws<2
fprintf('posterior_moments: There are not enough draws computes to compute HPD Intervals. Skipping their computation.\n')
end
if num_draws<9
fprintf('posterior_moments: There are not enough draws computes to compute deciles. Skipping their computation.\n')
end
if np
type = 'parameters';
if TeX
fid = TeXBegin(OutputFolder,M_.fname,1,type);
fid = TeXBegin(OutputFolder, M_.fname, 1, type);
end
skipline()
disp(type)
@ -94,44 +97,42 @@ if np
ip = nvx+nvn+ncx+ncn+1;
for i=1:np
if options_.mh_replic
Draws = GetAllPosteriorDraws(ip,FirstMhFile,FirstLine,TotalNumberOfMhFiles,NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, ...
density] = posterior_moments(Draws,1,options_.mh_conf_sig);
Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws, 1, options_.mh_conf_sig);
name = bayestopt_.name{ip};
oo_ = Filloo(oo_,name,type,post_mean,hpd_interval,post_median,post_var,post_deciles,density);
oo_ = Filloo(oo_, name, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
else
try
name = bayestopt_.name{ip};
[post_mean,hpd_interval,post_var] = Extractoo(oo_,name,type);
[post_mean, hpd_interval, post_var] = Extractoo(oo_, name, type);
catch
Draws = GetAllPosteriorDraws(ip,FirstMhFile,FirstLine,TotalNumberOfMhFiles,NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, ...
density] = posterior_moments(Draws,1,options_.mh_conf_sig);
Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws, 1, options_.mh_conf_sig);
name = bayestopt_.name{ip};
oo_ = Filloo(oo_,name,type,post_mean,hpd_interval,post_median,post_var,post_deciles,density);
oo_ = Filloo(oo_, name, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
end
end
disp(sprintf(pformat,header_width,name,bayestopt_.p1(ip),...
disp(sprintf(pformat, header_width, name, bayestopt_.p1(ip),...
post_mean, ...
hpd_interval, ...
pnames(bayestopt_.pshape(ip)+1,:), ...
pnames{bayestopt_.pshape(ip)+1}, ...
bayestopt_.p2(ip)));
if TeX
k = estim_params_.param_vals(i,1);
name = deblank(M_.param_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);
name = M_.param_names_tex{k};
TeXCore(fid, name, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p1(ip), bayestopt_.p2(ip), post_mean, sqrt(post_var), hpd_interval);
end
ip = ip+1;
end
if TeX
TeXEnd(fid,1,type);
TeXEnd(fid, 1, type);
end
end
if nvx
type = 'shocks_std';
if TeX
fid = TeXBegin(OutputFolder,FileName,2,'standard deviation of structural shocks');
fid = TeXBegin(OutputFolder, FileName,2, 'standard deviation of structural shocks');
end
ip = 1;
skipline()
@ -139,45 +140,43 @@ if nvx
disp(tit2)
for i=1:nvx
if options_.mh_replic
Draws = GetAllPosteriorDraws(ip,FirstMhFile,FirstLine,TotalNumberOfMhFiles,NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
posterior_moments(Draws,1,options_.mh_conf_sig);
Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws, 1, options_.mh_conf_sig);
k = estim_params_.var_exo(i,1);
name = deblank(M_.exo_names(k,:));
oo_ = Filloo(oo_,name,type,post_mean,hpd_interval,post_median,post_var,post_deciles,density);
name = M_.exo_names{k};
oo_ = Filloo(oo_, name, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
M_.Sigma_e(k,k) = post_mean*post_mean;
else
try
k = estim_params_.var_exo(i,1);
name = deblank(M_.exo_names(k,:));
[post_mean,hpd_interval,post_var] = Extractoo(oo_,name,type);
name = M_.exo_names{k};
[post_mean, hpd_interval, post_var] = Extractoo(oo_, name, type);
catch
Draws = GetAllPosteriorDraws(ip,FirstMhFile,FirstLine,TotalNumberOfMhFiles,NumberOfDraws);
Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
posterior_moments(Draws,1,options_.mh_conf_sig);
posterior_moments(Draws, 1, options_.mh_conf_sig);
k = estim_params_.var_exo(i,1);
name = deblank(M_.exo_names(k,:));
oo_ = Filloo(oo_,name,type,post_mean,hpd_interval,post_median,post_var,post_deciles,density);
name = M_.exo_names{k};
oo_ = Filloo(oo_, name, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
M_.Sigma_e(k,k) = post_mean*post_mean;
end
end
disp(sprintf(pformat,header_width,name,bayestopt_.p1(ip),post_mean,hpd_interval,...
pnames(bayestopt_.pshape(ip)+1,:),bayestopt_.p2(ip)));
disp(sprintf(pformat,header_width,name, bayestopt_.p1(ip), post_mean, hpd_interval, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p2(ip)));
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);
name = M_.exo_names_tex{k};
TeXCore(fid,name, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p1(ip), bayestopt_.p2(ip), post_mean, sqrt(post_var), hpd_interval);
end
ip = ip+1;
end
if TeX
TeXEnd(fid,2,'standard deviation of structural shocks');
TeXEnd(fid, 2, 'standard deviation of structural shocks');
end
end
if nvn
type = 'measurement_errors_std';
if TeX
fid = TeXBegin(OutputFolder,FileName,3,'standard deviation of measurement errors');
fid = TeXBegin(OutputFolder, FileName, 3, 'standard deviation of measurement errors');
end
skipline()
disp('standard deviation of measurement errors')
@ -185,37 +184,34 @@ if nvn
ip = nvx+1;
for i=1:nvn
if options_.mh_replic
Draws = GetAllPosteriorDraws(ip,FirstMhFile,FirstLine,TotalNumberOfMhFiles,NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
posterior_moments(Draws,1,options_.mh_conf_sig);
Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws, 1, options_.mh_conf_sig);
name = options_.varobs{estim_params_.nvn_observable_correspondence(i,1)};
oo_ = Filloo(oo_,name,type,post_mean,hpd_interval,post_median,post_var,post_deciles,density);
oo_ = Filloo(oo_, name, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
else
try
name = options_.varobs{estim_params_.nvn_observable_correspondence(i,1)};
[post_mean,hpd_interval,post_var] = Extractoo(oo_,name,type);
catch
Draws = GetAllPosteriorDraws(ip,FirstMhFile,FirstLine,TotalNumberOfMhFiles,NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
posterior_moments(Draws,1,options_.mh_conf_sig);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws,1,options_.mh_conf_sig);
name = options_.varobs{estim_params_.nvn_observable_correspondence(i,1)};
oo_ = Filloo(oo_,name,type,post_mean,hpd_interval,post_median,post_var,post_deciles,density);
end
end
disp(sprintf(pformat,header_width,name,bayestopt_.p1(ip),post_mean,hpd_interval, ...
pnames(bayestopt_.pshape(ip)+1,:),bayestopt_.p2(ip)));
disp(sprintf(pformat, header_width, name,bayestopt_.p1(ip), post_mean, hpd_interval, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p2(ip)));
if TeX
k = estim_params_.var_endo(i,1);
name = deblank(M_.endo_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);
name = M_.endo_names_tex{k};
TeXCore(fid, name, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p1(ip), bayestopt_.p2(ip), post_mean, sqrt(post_var), hpd_interval);
end
ip = ip+1;
end
if TeX
TeXEnd(fid,3,'standard deviation of measurement errors');
TeXEnd(fid, 3, 'standard deviation of measurement errors');
end
end
if ncx
type = 'shocks_corr';
if TeX
@ -227,53 +223,49 @@ if ncx
ip = nvx+nvn+1;
for i=1:ncx
if options_.mh_replic
Draws = GetAllPosteriorDraws(ip,FirstMhFile,FirstLine,TotalNumberOfMhFiles,NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
posterior_moments(Draws,1,options_.mh_conf_sig);
Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws,1,options_.mh_conf_sig);
k1 = estim_params_.corrx(i,1);
k2 = estim_params_.corrx(i,2);
name = [deblank(M_.exo_names(k1,:)) ',' deblank(M_.exo_names(k2,:))];
NAME = [deblank(M_.exo_names(k1,:)) '_' deblank(M_.exo_names(k2,:))];
oo_ = Filloo(oo_,NAME,type,post_mean,hpd_interval,post_median,post_var,post_deciles,density);
name = sprintf('%s,%s', M_.exo_names{k1}, M_.exo_names{k2});
NAME = sprintf('%s_%s', M_.exo_names{k1}, M_.exo_names{k2});
oo_ = Filloo(oo_, NAME, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
M_.Sigma_e(k1,k2) = post_mean*sqrt(M_.Sigma_e(k1,k1)*M_.Sigma_e(k2,k2));
M_.Sigma_e(k2,k1) = M_.Sigma_e(k1,k2);
else
try
k1 = estim_params_.corrx(i,1);
k2 = estim_params_.corrx(i,2);
name = [deblank(M_.exo_names(k1,:)) ',' deblank(M_.exo_names(k2,:))];
NAME = [deblank(M_.exo_names(k1,:)) '_' deblank(M_.exo_names(k2,:))];
[post_mean,hpd_interval,post_var] = Extractoo(oo_,NAME,type);
name = sprintf('%s,%s', M_.exo_names{k1}, M_.exo_names{k2});
NAME = sprintf('%s_%s', M_.exo_names{k1}, M_.exo_names{k2});
[post_mean,hpd_interval,post_var] = Extractoo(oo_, NAME, type);
catch
Draws = GetAllPosteriorDraws(ip,FirstMhFile,FirstLine,TotalNumberOfMhFiles,NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
posterior_moments(Draws,1,options_.mh_conf_sig);
Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws, 1, options_.mh_conf_sig);
k1 = estim_params_.corrx(i,1);
k2 = estim_params_.corrx(i,2);
name = [deblank(M_.exo_names(k1,:)) ',' deblank(M_.exo_names(k2,:))];
NAME = [deblank(M_.exo_names(k1,:)) '_' deblank(M_.exo_names(k2,:))];
oo_ = Filloo(oo_,NAME,type,post_mean,hpd_interval,post_median,post_var,post_deciles,density);
name = sprintf('%s,%s', M_.exo_names{k1}, M_.exo_names{k2});
NAME = sprintf('%s_%s', M_.exo_names{k1}, M_.exo_names{k2});
oo_ = Filloo(oo_, NAME, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
M_.Sigma_e(k1,k2) = post_mean*sqrt(M_.Sigma_e(k1,k1)*M_.Sigma_e(k2,k2));
M_.Sigma_e(k2,k1) = M_.Sigma_e(k1,k2);
end
end
disp(sprintf(pformat, header_width,name,bayestopt_.p1(ip),post_mean,hpd_interval, ...
pnames(bayestopt_.pshape(ip)+1,:),bayestopt_.p2(ip)));
disp(sprintf(pformat, header_width,name, bayestopt_.p1(ip), post_mean, hpd_interval, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p2(ip)));
if TeX
name = ['(',deblank(M_.exo_names_tex(k1,:)) ',' deblank(M_.exo_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);
name = sprintf('(%s,%s)', M_.exo_names_tex{k1}, M_.exo_names_tex{k2});
TeXCore(fid, name, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p1(ip), bayestopt_.p2(ip), post_mean, sqrt(post_var), hpd_interval);
end
ip = ip+1;
end
if TeX
TeXEnd(fid,4,'correlation of structural shocks');
TeXEnd(fid, 4, 'correlation of structural shocks');
end
end
if ncn
type = 'measurement_errors_corr';
if TeX
fid = TeXBegin(OutputFolder,FileName,5,'correlation of measurement errors');
fid = TeXBegin(OutputFolder, FileName, 5, 'correlation of measurement errors');
end
skipline()
disp('correlation of measurement errors')
@ -282,44 +274,38 @@ if ncn
for i=1:ncn
if options_.mh_replic
Draws = GetAllPosteriorDraws(ip,FirstMhFile,FirstLine,TotalNumberOfMhFiles,NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
posterior_moments(Draws,1,options_.mh_conf_sig);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws, 1, options_.mh_conf_sig);
k1 = estim_params_.corrn(i,1);
k2 = estim_params_.corrn(i,2);
name = [deblank(M_.endo_names(k1,:)) ',' deblank(M_.endo_names(k2,:))];
NAME = [deblank(M_.endo_names(k1,:)) '_' deblank(M_.endo_names(k2,:))];
oo_ = Filloo(oo_,NAME,type,post_mean,hpd_interval,...
post_median,post_var,post_deciles,density);
name = sprintf('%s,%s', M_.endo_names{k1}, M_.endo_names{k2});
NAME = sprintf('%s_%s', M_.endo_names{k1}, M_.endo_names{k2});
oo_ = Filloo(oo_, NAME, type, post_mean, hpd_interval, post_median, post_var, post_deciles,density);
else
try
k1 = estim_params_.corrn(i,1);
k2 = estim_params_.corrn(i,2);
name = [deblank(M_.endo_names(k1,:)) ',' deblank(M_.endo_names(k2,:))];
NAME = [deblank(M_.endo_names(k1,:)) '_' deblank(M_.endo_names(k2,:))];
[post_mean,hpd_interval,post_var] = Extractoo(oo_,NAME,type);
name = sprintf('%s,%s', M_.endo_names{k1}, M_.endo_names{k2});
NAME = sprintf('%s_%s', M_.endo_names{k1}, M_.endo_names{k2});
[post_mean,hpd_interval,post_var] = Extractoo(oo_, NAME, type);
catch
Draws = GetAllPosteriorDraws(ip,FirstMhFile,FirstLine,TotalNumberOfMhFiles,NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
posterior_moments(Draws,1,options_.mh_conf_sig);
Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws, 1, options_.mh_conf_sig);
k1 = estim_params_.corrn(i,1);
k2 = estim_params_.corrn(i,2);
name = [deblank(M_.endo_names(k1,:)) ',' deblank(M_.endo_names(k2,:))];
NAME = [deblank(M_.endo_names(k1,:)) '_' deblank(M_.endo_names(k2,:))];
oo_ = Filloo(oo_,NAME,type,post_mean,hpd_interval,...
post_median,post_var,post_deciles,density);
name = sprintf('%s,%s', M_.endo_names{k1}, M_.endo_names{k2});
NAME = sprintf('%s_%s', M_.endo_names{k1}, M_.endo_names{k2});
oo_ = Filloo(oo_, NAME, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
end
end
disp(sprintf(pformat, header_width,name,bayestopt_.p1(ip),post_mean,hpd_interval, ...
pnames(bayestopt_.pshape(ip)+1,:),bayestopt_.p2(ip)));
disp(sprintf(pformat, header_width, name, bayestopt_.p1(ip), post_mean, hpd_interval, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p2(ip)));
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);
name = sprintf('(%s,%s)', M_.endo_names_tex{k1}, M_.endo_names_tex{k2});
TeXCore(fid, name, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p1(ip), bayestopt_.p2(ip), post_mean, sqrt(post_var), hpd_interval);
end
ip = ip+1;
end
if TeX
TeXEnd(fid,5,'correlation of measurement errors');
TeXEnd(fid, 5, 'correlation of measurement errors');
end
end
@ -327,57 +313,57 @@ end
%
%% subfunctions:
%
function fid = TeXBegin(directory,fname,fnum,title)
function fid = TeXBegin(directory, fname, fnum, title)
TeXfile = [directory '/' fname '_Posterior_Mean_' int2str(fnum) '.tex'];
fidTeX = fopen(TeXfile,'w');
fprintf(fidTeX,'%% TeX-table generated by Dynare.\n');
fprintf(fidTeX,['%% RESULTS FROM METROPOLIS HASTINGS (' title ')\n']);
fprintf(fidTeX,['%% ' datestr(now,0)]);
fprintf(fidTeX,' \n');
fprintf(fidTeX,' \n');
fprintf(fidTeX,'\\begin{center}\n');
fprintf(fidTeX,'\\begin{longtable}{llcccccc} \n');
fprintf(fidTeX,['\\caption{Results from Metropolis-Hastings (' title ')}\n ']);
fprintf(fidTeX,['\\label{Table:MHPosterior:' int2str(fnum) '}\\\\\n']);
fprintf(fidTeX,'\\toprule \n');
fprintf(fidTeX,' & \\multicolumn{3}{c}{Prior} & \\multicolumn{4}{c}{Posterior} \\\\\n');
fprintf(fidTeX,' \\cmidrule(r{.75em}){2-4} \\cmidrule(r{.75em}){5-8}\n');
fprintf(fidTeX,' & Dist. & Mean & Stdev. & Mean & Stdev. & HPD inf & HPD sup\\\\\n');
fprintf(fidTeX,'\\midrule \\endfirsthead \n');
fprintf(fidTeX,['\\caption{(continued)}\\\\']);
fprintf(fidTeX,'\\toprule \n');
fprintf(fidTeX,' & \\multicolumn{3}{c}{Prior} & \\multicolumn{4}{c}{Posterior} \\\\\n');
fprintf(fidTeX,' \\cmidrule(r{.75em}){2-4} \\cmidrule(r{.75em}){5-8}\n');
fprintf(fidTeX,' & Dist. & Mean & Stdev. & Mean & Stdev. & HPD inf & HPD sup\\\\\n');
fprintf(fidTeX,'\\midrule \\endhead \n');
fprintf(fidTeX, '%% TeX-table generated by Dynare.\n');
fprintf(fidTeX, ['%% RESULTS FROM METROPOLIS HASTINGS (' title ')\n']);
fprintf(fidTeX, ['%% ' datestr(now, 0)]);
fprintf(fidTeX, ' \n');
fprintf(fidTeX, ' \n');
fprintf(fidTeX, '\\begin{center}\n');
fprintf(fidTeX, '\\begin{longtable}{llcccccc} \n');
fprintf(fidTeX, ['\\caption{Results from Metropolis-Hastings (' title ')}\n ']);
fprintf(fidTeX, ['\\label{Table:MHPosterior:' int2str(fnum) '}\\\\\n']);
fprintf(fidTeX, '\\toprule \n');
fprintf(fidTeX, ' & \\multicolumn{3}{c}{Prior} & \\multicolumn{4}{c}{Posterior} \\\\\n');
fprintf(fidTeX, ' \\cmidrule(r{.75em}){2-4} \\cmidrule(r{.75em}){5-8}\n');
fprintf(fidTeX, ' & Dist. & Mean & Stdev. & Mean & Stdev. & HPD inf & HPD sup\\\\\n');
fprintf(fidTeX, '\\midrule \\endfirsthead \n');
fprintf(fidTeX, ['\\caption{(continued)}\\\\']);
fprintf(fidTeX, '\\toprule \n');
fprintf(fidTeX, ' & \\multicolumn{3}{c}{Prior} & \\multicolumn{4}{c}{Posterior} \\\\\n');
fprintf(fidTeX, ' \\cmidrule(r{.75em}){2-4} \\cmidrule(r{.75em}){5-8}\n');
fprintf(fidTeX, ' & Dist. & Mean & Stdev. & Mean & Stdev. & HPD inf & HPD sup\\\\\n');
fprintf(fidTeX, '\\midrule \\endhead \n');
fprintf(fidTeX,'\\bottomrule \\multicolumn{8}{r}{(Continued on next page)} \\endfoot \n');
fprintf(fidTeX,'\\bottomrule \\endlastfoot \n');
fprintf(fidTeX, '\\bottomrule \\multicolumn{8}{r}{(Continued on next page)} \\endfoot \n');
fprintf(fidTeX, '\\bottomrule \\endlastfoot \n');
fid = fidTeX;
function TeXCore(fid,name,shape,priormean,priorstd,postmean,poststd,hpd)
function TeXCore(fid, name, shape, priormean, priorstd, postmean, poststd, hpd)
fprintf(fid,['$%s$ & %s & %7.3f & %6.4f & %7.3f& %6.4f & %7.4f & %7.4f \\\\ \n'],...
name,...
shape,...
priormean,...
priorstd,...
postmean,...
poststd,...
hpd(1),...
name, ...
shape, ...
priormean, ...
priorstd, ...
postmean, ...
poststd, ...
hpd(1), ...
hpd(2));
function TeXEnd(fid,fnum,title)
fprintf(fid,'\\end{longtable}\n ');
fprintf(fid,'\\end{center}\n');
fprintf(fid,'%% End of TeX file.\n');
function TeXEnd(fid, fnum, title)
fprintf(fid, '\\end{longtable}\n ');
fprintf(fid, '\\end{center}\n');
fprintf(fid, '%% End of TeX file.\n');
fclose(fid);
function oo = Filloo(oo,name,type,postmean,hpdinterval,postmedian,postvar,postdecile,density)
function oo = Filloo(oo, name, type, postmean, hpdinterval, postmedian, postvar, postdecile, density)
oo.posterior_mean.(type).(name) = postmean;
oo.posterior_hpdinf.(type).(name) = hpdinterval(1);
oo.posterior_hpdsup.(type).(name) = hpdinterval(2);
@ -387,7 +373,7 @@ oo.posterior_std.(type).(name) = sqrt(postvar);
oo.posterior_deciles.(type).(name) = postdecile;
oo.posterior_density.(type).(name) = density;
function [post_mean,hpd_interval,post_var] = Extractoo(oo,name,type)
function [post_mean,hpd_interval,post_var] = Extractoo(oo, name, type)
hpd_interval = zeros(2,1);
post_mean = oo.posterior_mean.(type).(name);
hpd_interval(1) = oo.posterior_hpdinf.(type).(name);

65
matlab/PlotPosteriorDistributions.m
View File

@ -16,7 +16,7 @@ function oo_ = PlotPosteriorDistributions(estim_params_, M_, options_, bayestopt
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2005-2017 Dynare Team
% Copyright (C) 2005-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -63,24 +63,24 @@ for i=1:npar
subplotnum = subplotnum+1;
if subplotnum == 1
figunumber = figunumber+1;
hfig=dyn_figure(options_.nodisplay,'Name',figurename);
hfig=dyn_figure(options_.nodisplay, 'Name', figurename);
end
[nam,texnam] = get_the_name(i,TeX,M_,estim_params_,options_);
[nam,texnam] = get_the_name(i, TeX, M_, estim_params_, options_);
if subplotnum == 1
NAMES = nam;
NAMES = {nam};
if TeX
TeXNAMES = texnam;
TeXNAMES = {texnam};
end
else
NAMES = char(NAMES,nam);
NAMES = [NAMES; {nam}];
if TeX
TeXNAMES = char(TeXNAMES,texnam);
TeXNAMES = [TeXNAMES; {texnam}];
end
end
[x2,f2,abscissa,dens,binf2,bsup2] = draw_prior_density(i,bayestopt_);
[x2, f2, abscissa, dens, binf2, bsup2] = draw_prior_density(i, bayestopt_);
top2 = max(f2);
if i <= nvx
name = deblank(M_.exo_names(estim_params_.var_exo(i,1),:));
name = M_.exo_names{estim_params_.var_exo(i,1)};
x1 = oo_.posterior_density.shocks_std.(name)(:,1);
f1 = oo_.posterior_density.shocks_std.(name)(:,2);
oo_.prior_density.shocks_std.(name)(:,1) = x2;
@ -101,7 +101,7 @@ for i=1:npar
j = i - (nvx+nvn);
k1 = estim_params_.corrx(j,1);
k2 = estim_params_.corrx(j,2);
name = [deblank(M_.exo_names(k1,:)) '_' deblank(M_.exo_names(k2,:))];
name = sprintf('%s_%s', M_.exo_names{k1}, M_.exo_names{k2});
x1 = oo_.posterior_density.shocks_corr.(name)(:,1);
f1 = oo_.posterior_density.shocks_corr.(name)(:,2);
oo_.prior_density.shocks_corr.(name)(:,1) = x2;
@ -113,7 +113,7 @@ for i=1:npar
j = i - (nvx+nvn+ncx);
k1 = estim_params_.corrn(j,1);
k2 = estim_params_.corrn(j,2);
name = [deblank(M_.endo_names(k1,:)) '_' deblank(M_.endo_names(k2,:))];
name = sprintf('%s_%s', M_.endo_names{k1}, M_.endo_names{k2});
x1 = oo_.posterior_density.measurement_errors_corr.(name)(:,1);
f1 = oo_.posterior_density.measurement_errors_corr.(name)(:,2);
oo_.prior_density.measurement_errors_corr.(name)(:,1) = x2;
@ -123,7 +123,7 @@ for i=1:npar
end
else
j = i - (nvx+nvn+ncx+ncn);
name = deblank(M_.param_names(estim_params_.param_vals(j,1),:));
name = M_.param_names{estim_params_.param_vals(j,1)};
x1 = oo_.posterior_density.parameters.(name)(:,1);
f1 = oo_.posterior_density.parameters.(name)(:,2);
oo_.prior_density.parameters.(name)(:,1) = x2;
@ -133,35 +133,36 @@ for i=1:npar
end
end
top1 = max(f1);
top0 = max([top1;top2]);
top0 = max([top1; top2]);
binf1 = x1(1);
bsup1 = x1(end);
borneinf = min(binf1,binf2);
bornesup = max(bsup1,bsup2);
subplot(nn,nn,subplotnum)
hh = plot(x2,f2,'-k','linewidth',2);
set(hh,'color',[0.7 0.7 0.7]);
borneinf = min(binf1, binf2);
bornesup = max(bsup1, bsup2);
subplot(nn, nn, subplotnum)
hh = plot(x2, f2, '-k', 'linewidth', 2);
set(hh, 'color', [0.7 0.7 0.7]);
hold on;
plot(x1,f1,'-k','linewidth',2);
plot(x1, f1, '-k', 'linewidth', 2);
if ~options_.mh_posterior_mode_estimation
plot( [pmod pmod], [0.0 1.1*top0], '--g', 'linewidth', 2);
plot([pmod pmod], [0.0 1.1*top0], '--g', 'linewidth', 2);
end
box on;
axis([borneinf bornesup 0 1.1*top0]);
title(nam,'Interpreter','none');
hold off;
box on
axis([borneinf bornesup 0 1.1*top0])
title(nam, 'Interpreter', 'none')
hold off
drawnow
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');
for j = 1:size(NAMES,1)
fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(j,:)),deblank(TeXNAMES(j,:)));
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');
for j = 1:size(NAMES, 1)
fprintf(fidTeX, '\\psfrag{%s}[1][][0.5][0]{%s}\n', NAMES{j}, TeXNAMES{j});
end
fprintf(fidTeX,'\\centering\n');
fprintf(fidTeX,'\\includegraphics[width=%2.2f\\textwidth]{%s/%s_PriorsAndPosteriors%s}\n',options_.figures.textwidth*min(subplotnum/nn,1),OutputDirectoryName,M_.fname,int2str(figunumber));
fprintf(fidTeX, '\\centering\n');
fprintf(fidTeX, '\\includegraphics[width=%2.2f\\textwidth]{%s/%s_PriorsAndPosteriors%s}\n', ...
options_.figures.textwidth*min(subplotnum/nn,1), OutputDirectoryName, M_.fname, int2str(figunumber));
fprintf(fidTeX,'\\caption{Priors and posteriors.}');
fprintf(fidTeX,'\\label{Fig:PriorsAndPosteriors:%s}\n',int2str(figunumber));
fprintf(fidTeX,'\\label{Fig:PriorsAndPosteriors:%s}\n', int2str(figunumber));
fprintf(fidTeX,'\\end{figure}\n');
fprintf(fidTeX,' \n');
if i == npar

44
matlab/PosteriorIRF.m
View File

@ -16,7 +16,7 @@ function PosteriorIRF(type)
% functions associated with it(the _core1 and _core2).
% See also the comments posterior_sampler.m funtion.
% Copyright (C) 2006-2017 Dynare Team
% Copyright (C) 2006-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -43,17 +43,17 @@ end
% Set varlist if necessary
varlist = options_.varlist;
if isempty(varlist)
varlist = char(options_.varobs);
varlist = options_.varobs;
end
options_.varlist = varlist;
nvar = size(varlist,1);
nvar = length(varlist);
IndxVariables = [];
for i=1:nvar
idx = strmatch(deblank(varlist(i,:)),M_.endo_names,'exact');
idx = strmatch(varlist{i}, M_.endo_names, 'exact');
if isempty(idx)
disp(['PosteriorIRF :: ' deblank(varlist(i,:)) 'is not a declared endogenous variable!'])
disp(['PosteriorIRF :: ' varlist{i} 'is not a declared endogenous variable!'])
else
IndxVariables = [IndxVariables,idx];
IndxVariables = [IndxVariables, idx];
end
end
@ -281,17 +281,14 @@ DistribIRF = zeros(options_.irf,9,nvar,M_.exo_nbr);
HPDIRF = zeros(options_.irf,2,nvar,M_.exo_nbr);
if options_.TeX
varlist_TeX = cell(nvar, 1);
for i=1:nvar
if i==1
varlist_TeX = M_.endo_names_tex(IndxVariables(i),:);
else
varlist_TeX = char(varlist_TeX,M_.endo_names_tex(IndxVariables(i),:));
end
varlist_TeX(i) = {M_.endo_names_tex{IndxVariables(i)}};
end
end
fprintf('Estimation::mcmc: Posterior (dsge) IRFs...\n');
tit(M_.exo_names_orig_ord,:) = M_.exo_names;
tit(M_.exo_names_orig_ord) = M_.exo_names;
kdx = 0;
for file = 1:NumberOfIRFfiles_dsge
@ -313,7 +310,7 @@ clear STOCK_IRF_DSGE;
for i = irf_shocks_indx
for j = 1:nvar
name = [deblank(M_.endo_names(IndxVariables(j),:)) '_' deblank(tit(i,:))];
name = sprintf('%s_%s', M_.endo_names{IndxVariables(j)}, tit{i});
oo_.PosteriorIRF.dsge.Mean.(name) = MeanIRF(:,j,i);
oo_.PosteriorIRF.dsge.Median.(name) = MedianIRF(:,j,i);
oo_.PosteriorIRF.dsge.Var.(name) = VarIRF(:,j,i);
@ -331,7 +328,7 @@ if MAX_nirfs_dsgevar
DistribIRFdsgevar = zeros(options_.irf,9,nvar,M_.exo_nbr);
HPDIRFdsgevar = zeros(options_.irf,2,nvar,M_.exo_nbr);
fprintf('Estimation::mcmc: Posterior (bvar-dsge) IRFs...\n');
tit(M_.exo_names_orig_ord,:) = M_.exo_names;
tit(M_.exo_names_orig_ord) = M_.exo_names;
kdx = 0;
for file = 1:NumberOfIRFfiles_dsgevar
load([MhDirectoryName filesep M_.fname '_IRF_BVARDSGEs' int2str(file) '.mat']);
@ -350,7 +347,7 @@ if MAX_nirfs_dsgevar
clear STOCK_IRF_BVARDSGE;
for i = irf_shocks_indx
for j = 1:nvar
name = [deblank(M_.endo_names(IndxVariables(j),:)) '_' deblank(tit(i,:))];
name = sprintf('%s_%s', M_.endo_names{IndxVariables(j)}, tit{i});
oo_.PosteriorIRF.bvardsge.Mean.(name) = MeanIRFdsgevar(:,j,i);
oo_.PosteriorIRF.bvardsge.Median.(name) = MedianIRFdsgevar(:,j,i);
oo_.PosteriorIRF.bvardsge.Var.(name) = VarIRFdsgevar(:,j,i);
@ -396,13 +393,13 @@ if ~options_.nograph && ~options_.no_graph.posterior
% The files .TeX are generated in sequential way always!
subplotnum = 0;
tit_TeX(M_.exo_names_orig_ord,:) = M_.exo_names_tex;
titTeX(M_.exo_names_orig_ord) = M_.exo_names_tex;
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fidTeX = fopen([DirectoryName filesep M_.fname '_BayesianIRF.tex'],'w');
fprintf(fidTeX,'%% TeX eps-loader file generated by PosteriorIRF.m (Dynare).\n');
fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
fprintf(fidTeX,' \n');
titTeX(M_.exo_names_orig_ord,:) = M_.exo_names_tex;
titTeX(M_.exo_names_orig_ord) = M_.exo_names_tex;
for ii=irf_shocks_indx
figunumber = 0;
@ -414,24 +411,23 @@ if ~options_.nograph && ~options_.no_graph.posterior
if subplotnum == 1
fprintf(fidTeX,'\\begin{figure}[H]\n');
end
name = deblank(varlist(jj,:));
texname = deblank(varlist_TeX(jj,:));
name = varlist{jj};
texname = varlist_TeX{jj};
fprintf(fidTeX,['\\psfrag{%s}[1][][0.5][0]{%s}\n'],name,['$' texname '$']);
end
if subplotnum == MaxNumberOfPlotPerFigure || (jj == nvar && subplotnum> 0)
figunumber = figunumber+1;
fprintf(fidTeX,'\\centering \n');
fprintf(fidTeX,'\\includegraphics[width=%2.2f\\textwidth]{%s/%s_Bayesian_IRF_%s_%d}\n',options_.figures.textwidth*min(subplotnum/nn,1),DirectoryName,M_.fname,deblank(tit(ii,:)),figunumber);
fprintf(fidTeX,'\\includegraphics[width=%2.2f\\textwidth]{%s/%s_Bayesian_IRF_%s_%d}\n',options_.figures.textwidth*min(subplotnum/nn,1),DirectoryName,M_.fname,tit{ii},figunumber);
if options_.relative_irf
fprintf(fidTeX,['\\caption{Bayesian relative IRF.}']);
else
fprintf(fidTeX,'\\caption{Bayesian IRF: Orthogonalized shock to $%s$.}\n',deblank(tit_TeX(ii,:)));
fprintf(fidTeX,'\\caption{Bayesian IRF: Orthogonalized shock to $%s$.}\n',titTeX{ii});
end
fprintf(fidTeX,'\\label{Fig:BayesianIRF:%s:%d}\n',deblank(tit(ii,:)),figunumber);
fprintf(fidTeX,'\\label{Fig:BayesianIRF:%s:%d}\n', tit{ii},figunumber);
fprintf(fidTeX,'\\end{figure}\n');
fprintf(fidTeX,' \n');
subplotnum = 0;
end
end
@ -445,7 +441,7 @@ if ~options_.nograph && ~options_.no_graph.posterior
% 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(length(varlist)/MaxNumberOfPlotPerFigure))<8
[fout] = PosteriorIRF_core2(localVars,1,M_.exo_nbr,0);
else
isRemoteOctave = 0;

4
matlab/PosteriorIRF_core1.m
View File

@ -23,7 +23,7 @@ function myoutput=PosteriorIRF_core1(myinputs,fpar,B,whoiam, ThisMatlab)
% SPECIAL REQUIREMENTS.
% None.
%
% Copyright (C) 2006-2017 Dynare Team
% Copyright (C) 2006-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -195,7 +195,7 @@ while fpar<B
if MAX_nirfs_dsgevar
IRUN = IRUN+1;
[fval,info,junk1,junk2,junk3,junk3,junk4,PHI,SIGMAu,iXX] = dsge_var_likelihood(deep',dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,bounds,oo_);
dsge_prior_weight = M_.params(strmatch('dsge_prior_weight',M_.param_names));
dsge_prior_weight = M_.params(strmatch('dsge_prior_weight', M_.param_names));
DSGE_PRIOR_WEIGHT = floor(dataset_.nobs*(1+dsge_prior_weight));
SIGMA_inv_upper_chol = chol(inv(SIGMAu*dataset_.nobs*(dsge_prior_weight+1)));
explosive_var = 1;

12
matlab/PosteriorIRF_core2.m
View File

@ -30,7 +30,7 @@ function myoutput=PosteriorIRF_core2(myinputs,fpar,npar,whoiam,ThisMatlab)
% SPECIAL REQUIREMENTS.
% None.
%
% Copyright (C) 2006-2017 Dynare Team
% Copyright (C) 2006-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -103,9 +103,9 @@ for i=fpar:npar
if max(abs(MeanIRF(:,j,i))) >= options_.impulse_responses.plot_threshold
subplotnum = subplotnum+1;
if subplotnum == 1 && options_.relative_irf
hh = dyn_figure(options_.nodisplay,'Name',['Relative response to orthogonalized shock to ' tit(i,:)]);
hh = dyn_figure(options_.nodisplay,'Name',['Relative response to orthogonalized shock to ' tit{i}]);
elseif subplotnum == 1 && ~options_.relative_irf
hh = dyn_figure(options_.nodisplay,'Name',['Orthogonalized shock to ' tit(i,:)]);
hh = dyn_figure(options_.nodisplay,'Name',['Orthogonalized shock to ' tit{i}]);
end
set(0,'CurrentFigure',hh)
@ -142,17 +142,17 @@ for i=fpar:npar
remove_fractional_xticks;
hold off
end
name = deblank(varlist(j,:));
name = varlist{j};
title(name,'Interpreter','none')
else
if options_.debug
fprintf('POSTERIOR_IRF: The IRF of %s to %s is smaller than the irf_plot_threshold of %4.3f and will not be displayed.\n',deblank(varlist(j,:)),tit(i,:),options_.impulse_responses.plot_threshold)
fprintf('POSTERIOR_IRF: The IRF of %s to %s is smaller than the irf_plot_threshold of %4.3f and will not be displayed.\n',varlist{j},tit{i},options_.impulse_responses.plot_threshold)
end
end
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);
dyn_saveas(hh,[DirectoryName '/' M_.fname '_Bayesian_IRF_' tit{i} '_' int2str(figunumber)],options_.nodisplay,options_.graph_format);
if RemoteFlag==1
OutputFileName = [OutputFileName; {[DirectoryName,filesep], [M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) '_' int2str(figunumber) '.*']}];
end

16
matlab/UnivariateSpectralDensity.m
View File

@ -19,7 +19,7 @@ function [oo_] = UnivariateSpectralDensity(M_,oo_,options_,var_list)
% Adapted from th_autocovariances.m.
% Copyright (C) 2006-2017 Dynare Team
% Copyright (C) 2006-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -50,15 +50,15 @@ else
warning off MATLAB:dividebyzero
end
if nargin<2
var_list = [];
var_list = {};
end
if size(var_list,1) == 0
var_list = M_.endo_names(1:M_.orig_endo_nbr, :);
if isempty(var_list)
var_list = M_.endo_names(1:M_.orig_endo_nbr);
end
nvar = size(var_list,1);
nvar = length(var_list);
ivar=zeros(nvar,1);
for i=1:nvar
i_tmp = strmatch(var_list(i,:),M_.endo_names,'exact');
i_tmp = strmatch(var_list{i}, M_.endo_names, 'exact');
if isempty(i_tmp)
error (['One of the variables specified does not exist']) ;
else
@ -159,12 +159,12 @@ if options_.nograph == 0
end
for i= 1:nvar
hh = dyn_figure(options_.nodisplay,'Name',['Spectral Density of ' deblank(M_.endo_names(ivar(i),:)) '.']);
hh = dyn_figure(options_.nodisplay,'Name',['Spectral Density of ' M_.endo_names{ivar(i)} '.']);
plot(freqs,f(i,:),'-k','linewidth',2)
xlabel('0 \leq \omega \leq \pi')
ylabel('f(\omega)')
box on
axis tight
dyn_saveas(hh,[M_.fname ,filesep,'graphs', filesep, 'SpectralDensity_' deblank(M_.endo_names(ivar(i),:))],options_.nodisplay,options_.graph_format)
dyn_saveas(hh,[M_.fname ,filesep,'graphs', filesep, 'SpectralDensity_' M_.endo_names{ivar(i)}],options_.nodisplay,options_.graph_format)
end
end

8
matlab/WriteShockDecomp2Excel.m
View File

@ -11,7 +11,7 @@ function WriteShockDecomp2Excel(z,shock_names,endo_names,i_var,initial_date,Dyna
% DynareModel [structure] Dynare model structure
% DynareOptions [structure] Dynare options structure
% Copyright (C) 2016-2017 Dynare Team
% Copyright (C) 2016-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -94,7 +94,7 @@ for j=1:nvar
z1 = squeeze(z(i_var(j),:,:));
if screen_shocks
[junk, isort] = sort(mean(abs(z1(1:end-2,:)')), 'descend');
labels = char(char(shock_names(isort(1:16),:)),'Others', 'Initial values');
labels = char(char(shock_names(isort(1:16))),'Others', 'Initial values');
zres = sum(z1(isort(17:end),:),1);
z1 = [z1(isort(1:16),:); zres; z1(comp_nbr0:end,:)];
comp_nbr=18;
@ -115,9 +115,9 @@ for j=1:nvar
warning off
if ~ismac
[STATUS,MESSAGE] = xlswrite([DynareModel.fname,'_shock_decomposition',fig_mode,fig_name1],d0,deblank(endo_names(i_var(j),:)));
[STATUS,MESSAGE] = xlswrite([DynareModel.fname,'_shock_decomposition',fig_mode,fig_name1],d0,endo_names{i_var(j)});
else
[STATUS] = xlwrite([DynareModel.fname,'_shock_decomposition',fig_mode,fig_name1],d0,deblank(endo_names(i_var(j),:)));
[STATUS] = xlwrite([DynareModel.fname,'_shock_decomposition',fig_mode,fig_name1],d0,endo_names{i_var(j)});
end
warning on

23
matlab/annualized_shock_decomposition.m
View File

@ -32,7 +32,7 @@ function [z, endo_names, endo_names_tex, steady_state, i_var, oo_] = annualized_
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2018 Dynare Team
%
% This file is part of Dynare.
%
@ -109,17 +109,15 @@ elseif mytype
gtex = 'g';
end
steady_state=steady_state(i_var);
% endo_names = M_.endo_names(i_var,:);
% endo_names_tex = M_.endo_names_tex(i_var,:);
nterms = size(z,2);
nfrcst = opts.forecast/4;
for j=1:nvar
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,:)]);
gendo_names_tex = char(gendo_names_tex,[gtex '(' deblank(endo_names_tex(j,:)) ')']);
endo_names = char(endo_names, sprintf('%s_A', M_.endo_names{i_var(j)}));
endo_names_tex = char(endo_names_tex, sprintf('{%s}^A', M_.endo_names_tex{i_var(j)}));
gendo_names = char(gendo_names,[gtxt endo_names{j}]);
gendo_names_tex = char(gendo_names_tex,[gtex '(' endo_names_tex{j} ')']);
else
if nvar==1 && ~mytype
endo_names = mytxt;
@ -127,10 +125,10 @@ for j=1:nvar
gendo_names = gtxt;
gendo_names_tex = gtex;
else
endo_names = [deblank(M_.endo_names(i_var(j),:)) '_A'];
endo_names_tex = ['{' deblank(M_.endo_names_tex(i_var(j),:)) '}^A'];
gendo_names = [gtxt endo_names(j,:)];
gendo_names_tex = [gtex '(' deblank(endo_names_tex(j,:)) ')'];
endo_names = sprintf('%s_A', M_.endo_names{i_var(j)});
endo_names_tex = sprintf('{%s}^A', M_.endo_names_tex{i_var(j)});
gendo_names = [gtxt endo_names{j}];
gendo_names_tex = [gtex '(' endo_names_tex{j} ')'];
end
end
for k =1:nterms
@ -331,3 +329,6 @@ else
steady_state = steady_state_a;
end
end
endo_names = cellstr(endo_names);
endo_names_tex = cellstr(endo_names_tex);

4
matlab/backward/backward_model_forecast.m
View File

@ -10,7 +10,7 @@ function forecasts = backward_model_forecast(initialcondition, listofvariables,
% OUTPUTS
% - forecast [dseries]
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2017-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -39,7 +39,7 @@ forecasts = struct();
% Set defaults.
if nargin<2
listofvariables = cellstr(M_.endo_names);
listofvariables = M_.endo_names;
periods = 8;
withuncertainty = false;
end

12
matlab/backward/backward_model_irf.m
View File

@ -19,7 +19,7 @@ function [deviations, baseline, irfs] = backward_model_irf(initialcondition, inn
% argument.
% - If second argument is not empty, periods must not be greater than innovationbaseline.nobs.
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2017-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -72,7 +72,7 @@ else
end
if deterministicshockflag
numberofexperiments = length(listofshocks);
exonames = cellstr(M_.exo_names);
exonames = M_.exo_names;
initialconditionperiod = initialcondition.dates(end);
for i=1:numberofexperiments
shock = listofshocks{i};
@ -108,7 +108,7 @@ if ~isempty(innovationbaseline)
error('The second input argument must at least have %s observations or lower the number of periods.', periods)
end
% Fill innovations with provided paths for the innovations.
exonames = cellstr(M_.exo_names);
exonames = M_.exo_names;
for i = 1:length(exonames)
if ~isempty(strmatch(exonames{i}, innovationbaseline.name))
Innovations(:,i) = innovationbaseline{exonames{i}}.data(1:periods);
@ -183,9 +183,9 @@ for i=1:length(listofshocks)
endo_simul__1 = feval(transform, ysim__1);
end
% Instantiate a dseries object (with all the endogenous variables)
alldeviations = dseries(transpose(endo_simul__1-endo_simul__0), initialcondition.init, endonames(1:M_.orig_endo_nbr), cellstr(DynareModel.endo_names_tex(1:M_.orig_endo_nbr,:)));
alldeviations = dseries(transpose(endo_simul__1-endo_simul__0), initialcondition.init, endonames(1:M_.orig_endo_nbr), DynareModel.endo_names_tex(1:M_.orig_endo_nbr));
if nargout>2
allirfs = dseries(transpose(endo_simul__1), initialcondition.init, endonames(1:M_.orig_endo_nbr), cellstr(DynareModel.endo_names_tex(1:M_.orig_endo_nbr,:)));
allirfs = dseries(transpose(endo_simul__1), initialcondition.init, endonames(1:M_.orig_endo_nbr), DynareModel.endo_names_tex(1:M_.orig_endo_nbr));
end
% Extract a sub-dseries object
if deterministicshockflag
@ -201,6 +201,6 @@ for i=1:length(listofshocks)
end
if nargout>1
baseline = dseries(transpose(endo_simul__0), initialcondition.init, endonames(1:M_.orig_endo_nbr), cellstr(DynareModel.endo_names_tex(1:M_.orig_endo_nbr,:)));
baseline = dseries(transpose(endo_simul__0), initialcondition.init, endonames(1:M_.orig_endo_nbr), DynareModel.endo_names_tex(1:M_.orig_endo_nbr));
baseline = [baseline, innovationbaseline];
end

4
matlab/backward/simul_backward_model.m
View File

@ -18,7 +18,7 @@ function simulation = simul_backward_model(initialconditions, samplesize, innova
% [3] If the first input argument is empty, the endogenous variables are initialized with 0, or if available with the informations
% provided thrtough the histval block.
% Copyright (C) 2012-2017 Dynare Team
% Copyright (C) 2012-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -47,7 +47,7 @@ else
end
% Set array holding innovations values.
Innovations = zeros(samplesize, M_.exo_nbr);
exonames = cellstr(M_.exo_names);
exonames = M_.exo_names;
for i=1:M_.exo_nbr
if ismember(exonames{i}, innovations.name)
Innovations(:,i) = innovations{exonames{i}}.data(1:samplesize);

18
matlab/backward/simul_backward_model_init.m
View File

@ -2,7 +2,7 @@ function [initialconditions, samplesize, innovations, DynareOptions, DynareModel
% Initialization of the routines simulating backward models.
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2017-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -41,7 +41,7 @@ if ~isdseries(initialconditions)
end
% Test if the first argument contains all the lagged endogenous variables
endonames = cellstr(DynareModel.endo_names);
endonames = DynareModel.endo_names;
missingendogenousvariables = setdiff(endonames, initialconditions.name);
endolags = get_lags_on_endogenous_variables(DynareModel);
endolags_ = endolags(find(endolags));
@ -84,7 +84,7 @@ if missinginitialcondition
end
% If the model has lags on the exogenous variables, test if we have corresponding initial conditions.
exonames = cellstr(DynareModel.exo_names);
exonames = DynareModel.exo_names;
missingexogenousvariables = setdiff(exonames, initialconditions.name);
exolags = get_lags_on_exogenous_variables(DynareModel);
exolags_ = exolags(find(exolags));
@ -131,16 +131,16 @@ k = 0;
for i = DynareModel.orig_endo_nbr+1:DynareModel.endo_nbr
k = k+1;
if DynareModel.aux_vars(k).type==1
if ismember(deblank(DynareModel.endo_names(DynareModel.aux_vars(k).orig_index,:)), initialconditions.name)
initialconditions{deblank(DynareModel.endo_names(DynareModel.aux_vars(k).endo_index, :))} = ...
initialconditions{deblank(DynareModel.endo_names(DynareModel.aux_vars(k).orig_index, :))}.lag(abs(DynareModel.aux_vars(k).orig_lead_lag));
if ismember(DynareModel.endo_names{DynareModel.aux_vars(k).orig_index}, initialconditions.name)
initialconditions{DynareModel.endo_names{DynareModel.aux_vars(k).endo_index}} = ...
initialconditions{DynareModel.endo_names{DynareModel.aux_vars(k).orig_index}}.lag(abs(DynareModel.aux_vars(k).orig_lead_lag));
else
error('This is a bug. Please contact Dynare Team!');
end
elseif DynareModel.aux_vars(k).type==3
if ismember(deblank(DynareModel.exo_names(DynareModel.aux_vars(k).orig_index, :)), initialconditions.name)
initialconditions{deblank(DynareModel.endo_names(DynareModel.aux_vars(k).endo_index,:))} = ...
initialconditions{deblank(DynareModel.exo_names(DynareModel.aux_vars(k).orig_index, :))}.lag(abs(DynareModel.aux_vars(k).orig_lead_lag));
if ismember(DynareModel.exo_names{DynareModel.aux_vars(k).orig_index}, initialconditions.name)
initialconditions{DynareModel.endo_names{DynareModel.aux_vars(k).endo_index}} = ...
initialconditions{DynareModel.exo_names{DynareModel.aux_vars(k).orig_index}}.lag(abs(DynareModel.aux_vars(k).orig_lead_lag));
else
error('This is a bug. Please contact Dynare Team!');
end

28
matlab/cellofchararraymaxlength.m Normal file
View File

@ -0,0 +1,28 @@
function n = cellofchararraymaxlength(c)
% Copyright (C) 2018 Dynare Team
%
% This file is part of Dynare.
%
% Dynare is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% Dynare is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
if ~all(cellfun(@ischar, c))
error('Input has to be a cell of char arrays!')
end
if ~all(cellfun(@isrow, c))
error('Input has to be a cell of one dimensional char arrays!')
end
n = max(cellfun(@length, c));

54
matlab/check_list_of_variables.m
View File

@ -5,16 +5,16 @@ function varlist = check_list_of_variables(options_, M_, varlist)
%
% INPUTS
%
% options_ [structure] Dynare structure.
% M_ [structure] Dynare structure (related to model definition).
% varlist [string] Array of strings with name of the endogenous variables.
% options_ [structure] Dynare structure.
% M_ [structure] Dynare structure (related to model definition).
% varlist [cell of char arrays] Array of strings with name of the endogenous variables.
%
% OUTPUTS
% varlist [string]
% varlist [cell of char arrays]
%
% SPECIAL REQUIREMENTS
% Copyright (C) 2003-2017 Dynare Team
% Copyright (C) 2003-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -33,21 +33,21 @@ function varlist = check_list_of_variables(options_, M_, varlist)
%get uniques
[junk1,junk2,index_uniques] = varlist_indices(varlist,M_.endo_names);
varlist=varlist(index_uniques,:);
[junk1, junk2, index_uniques] = varlist_indices(varlist, M_.endo_names);
varlist = varlist(index_uniques);
msg = 0;
msg = false;
if options_.dsge_var && options_.bayesian_irf
if ~isempty(varlist)
for i=1:size(varlist,1)
idx = strmatch(deblank(varlist(i,:)),options_.varobs,'exact');
idx = strmatch(varlist{i}, options_.varobs, 'exact');
if isempty(idx)
disp([varlist(i,:) ' is not an observed variable!']);
msg = 1;
disp(sprintf('%s is not an observed variable!', varlist{i}))
msg = true;
end
end
if size(varlist,1)~=length(options_.varobs)
msg = 1;
if ~isequal(size(varlist), length(options_.varobs))
msg = true;
end
if msg
skipline()
@ -55,7 +55,7 @@ if options_.dsge_var && options_.bayesian_irf
skipline()
end
end
varlist = char(options_.varobs);
varlist = options_.varobs;
return
end
@ -63,16 +63,16 @@ if ~isempty(varlist) && ~isempty(options_.endo_vars_for_moment_computations_in_e
error('You cannot use the consider_all_endogenous or consider_all_observed options when listing variables after the estimation command')
elseif isempty(varlist) && ~isempty(options_.endo_vars_for_moment_computations_in_estimation)
if strcmp(options_.endo_vars_for_moment_computations_in_estimation,'all_endogenous_variables')
varlist = M_.endo_names(1:M_.orig_endo_nbr, :);
varlist = M_.endo_names(1:M_.orig_endo_nbr);
elseif strcmp(options_.endo_vars_for_moment_computations_in_estimation,'only_observed_variables')
varlist = char(options_.varobs');
varlist = options_.varobs;
else
error('Unknown option')
end
elseif isempty(varlist) && isempty(options_.endo_vars_for_moment_computations_in_estimation)
skipline()
disp(['You did not declare endogenous variables after the estimation/calib_smoother command.'])
cas = [];
cas = '';
if options_.bayesian_irf
cas = 'Posterior IRFs';
end
@ -80,37 +80,37 @@ elseif isempty(varlist) && isempty(options_.endo_vars_for_moment_computations_in
if isempty(cas)
cas = 'Posterior moments';
else
cas = [ cas , ', posterior moments'];
cas = [cas, ', posterior moments'];
end
end
if options_.smoother
if isempty(cas)
cas = 'Smoothed variables';
else
cas = [ cas , ', smoothed variables'];
cas = [cas, ', smoothed variables'];
end
end
if ~isempty(options_.filter_step_ahead)
if isempty(cas)
cas = 'k-step ahead filtered variables';
else
cas = [ cas , ', k-step ahead filtered variables'];
cas = [cas, ', k-step ahead filtered variables'];
end
end
if options_.forecast
if isempty(cas)
cas = 'Forecasts';
else
cas = [ cas , ' and forecasts'];
cas = [cas, ' and forecasts'];
end
end
if ~isempty(cas)
string = [ cas , ' will be computed for the ' num2str(M_.endo_nbr) ' endogenous variables'];
string = [ string ' of your model, this can take a long time ....'];
format_text(string, 10)
str = sprintf('%s will be computed for the %s endogenous variables of your model', cas, num2str(M_.orig_endo_nbr));
str = sprintf('%s, this can take a long time ....', str);
format_text(str, 10)
if options_.nointeractive
% Default behaviour is to consider all the endogenous variables.
varlist = M_.endo_names(1:M_.orig_endo_nbr, :);
varlist = M_.endo_names(1:M_.orig_endo_nbr);
else
choice = [];
while isempty(choice)
@ -126,9 +126,9 @@ elseif isempty(varlist) && isempty(options_.endo_vars_for_moment_computations_in
choice=1;
end
if choice==1
varlist = M_.endo_names(1:M_.orig_endo_nbr, :);
varlist = M_.endo_names(1:M_.orig_endo_nbr);
elseif choice==2
varlist = char(options_.varobs);
varlist = options_.varobs;
elseif choice==3
varlist = NaN;
else

198
matlab/compute_moments_varendo.m
View File

@ -1,14 +1,15 @@
function oo_ = compute_moments_varendo(type,options_,M_,oo_,var_list_)
function oo_ = compute_moments_varendo(type, options_, M_, oo_, var_list_)
% Computes the second order moments (autocorrelation function, covariance
% matrix and variance decomposition) distributions for all the endogenous variables selected in
% var_list_. The results are saved in oo_
%
% INPUTS:
% type [string] 'posterior' or 'prior'
% options_ [structure] Dynare structure.
% M_ [structure] Dynare structure (related to model definition).
% oo_ [structure] Dynare structure (results).
% var_list_ [string] Array of string with endogenous variable names.
% type [string] 'posterior' or 'prior'
% options_ [structure] Dynare structure.
% M_ [structure] Dynare structure (related to model definition).
% oo_ [structure] Dynare structure (results).
% var_list_ [cell of char arrays] Endogenous variable names.
%
% OUTPUTS
% oo_ [structure] Dynare structure (results).
@ -16,7 +17,7 @@ function oo_ = compute_moments_varendo(type,options_,M_,oo_,var_list_)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2008-2017 Dynare Team
% Copyright (C) 2008-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -39,21 +40,21 @@ fprintf('Estimation::compute_moments_varendo: I''m computing endogenous moments
if strcmpi(type,'posterior')
posterior = 1;
if nargin==4
var_list_ = char(options_.varobs);
var_list_ = options_.varobs;
end
elseif strcmpi(type,'prior')
posterior = 0;
if nargin==4
var_list_ = options_.prior_analysis_endo_var_list;
if isempty(var_list_)
options_.prior_analysis_var_list = char(options_.varobs);
options_.prior_analysis_var_list = options_.varobs;
end
end
else
error('compute_moments_varendo:: Unknown type!')
end
NumberOfEndogenousVariables = rows(var_list_);
NumberOfEndogenousVariables = length(var_list_);
NumberOfExogenousVariables = M_.exo_nbr;
NumberOfLags = options_.ar;
NoDecomposition = options_.nodecomposition;
@ -64,9 +65,9 @@ else
end
if options_.TeX
var_list_tex='';
for var_iter=1:size(var_list_,1)
var_list_tex=strvcat(var_list_tex,M_.endo_names_tex(strmatch(var_list_(var_iter,:),M_.endo_names,'exact'),:));
var_list_tex={};
for var_iter = 1:length(var_list_)
var_list_tex = vertcat(var_list_tex, M_.endo_names_tex{strmatch(var_list_{var_iter}, M_.endo_names, 'exact')});
end
end
@ -74,22 +75,23 @@ end
if posterior
for i=1:NumberOfEndogenousVariables
for j=i:NumberOfEndogenousVariables
oo_ = posterior_analysis('variance',var_list_(i,:),var_list_(j,:),[],options_,M_,oo_);
oo_ = posterior_analysis('variance', var_list_{i}, var_list_{j}, [], options_, M_, oo_);
end
end
else
for i=1:NumberOfEndogenousVariables
for j=i:NumberOfEndogenousVariables
oo_ = prior_analysis('variance',var_list_(i,:),var_list_(j,:),[],options_,M_,oo_);
oo_ = prior_analysis('variance', var_list_{i}, var_list_{j}, [], options_, M_, oo_);
end
end
end
% CORRELATION FUNCTION.
if posterior
for h=NumberOfLags:-1:1
for i=1:NumberOfEndogenousVariables
for j=1:NumberOfEndogenousVariables
oo_ = posterior_analysis('correlation',var_list_(i,:),var_list_(j,:),h,options_,M_,oo_);
oo_ = posterior_analysis('correlation', var_list_{i}, var_list_{j}, h, options_, M_, oo_);
end
end
end
@ -97,11 +99,12 @@ else
for h=NumberOfLags:-1:1
for i=1:NumberOfEndogenousVariables
for j=1:NumberOfEndogenousVariables
oo_ = prior_analysis('correlation',var_list_(i,:),var_list_(j,:),h,options_,M_,oo_);
oo_ = prior_analysis('correlation', var_list_{i}, var_list_{j}, h, options_, M_, oo_);
end
end
end
end
% VARIANCE DECOMPOSITION.
if M_.exo_nbr > 1
if ~NoDecomposition
@ -109,8 +112,8 @@ if M_.exo_nbr > 1
if posterior
for i=1:NumberOfEndogenousVariables
for j=1:NumberOfExogenousVariables
oo_ = posterior_analysis('decomposition',var_list_(i,:),M_.exo_names(j,:),[],options_,M_,oo_);
temp(i,j)=oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.Mean.(deblank(var_list_(i,:))).(deblank(M_.exo_names(j,:)));
oo_ = posterior_analysis('decomposition', var_list_{i}, M_.exo_names{j}, [], options_, M_, oo_);
temp(i,j) = oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.Mean.(var_list_{i}).(M_.exo_names{j});
end
end
title='Posterior mean variance decomposition (in percent)';
@ -118,160 +121,157 @@ if M_.exo_nbr > 1
else
for i=1:NumberOfEndogenousVariables
for j=1:NumberOfExogenousVariables
oo_ = prior_analysis('decomposition',var_list_(i,:),M_.exo_names(j,:),[],options_,M_,oo_);
temp(i,j)=oo_.PriorTheoreticalMoments.dsge.VarianceDecomposition.Mean.(deblank(var_list_(i,:))).(deblank(M_.exo_names(j,:)));
oo_ = prior_analysis('decomposition', var_list_{i}, M_.exo_names{j}, [], options_, M_, oo_);
temp(i,j)=oo_.PriorTheoreticalMoments.dsge.VarianceDecomposition.Mean.(var_list_{i}).(M_.exo_names{j});
end
end
title='Prior mean variance decomposition (in percent)';
save_name_string='dsge_prior_mean_var_decomp_uncond';
end
title=add_filter_subtitle(title,options_);
title=add_filter_subtitle(title, options_);
headers = M_.exo_names;
headers(M_.exo_names_orig_ord,:) = headers;
headers = char(' ',headers);
lh = size(deblank(var_list_),2)+2;
dyntable(options_,title,headers,deblank(var_list_),100* ...
temp,lh,8,2);
headers(M_.exo_names_orig_ord) = headers;
headers = vertcat(' ', headers);
lh = cellofchararraymaxlength(var_list_)+2;
dyntable(options_, title, headers, var_list_, 100*temp, lh, 8, 2);
if options_.TeX
headers=M_.exo_names_tex;
headers = char(' ',headers);
labels = deblank(var_list_tex);
headers = M_.exo_names_tex;
headers = vertcat(' ', headers);
labels = var_list_tex;
lh = size(labels,2)+2;
dyn_latex_table(M_,options_,title,save_name_string,headers,labels,100*temp,lh,8,2);
dyn_latex_table(M_, options_, title, save_name_string, headers, labels, 100*temp, lh, 8, 2);
end
skipline();
end
skipline();
if ~all(M_.H==0)
[observable_name_requested_vars,varlist_pos]=intersect(var_list_,options_.varobs,'stable');
[observable_name_requested_vars, varlist_pos] = intersect(var_list_, options_.varobs, 'stable');
if ~isempty(observable_name_requested_vars)
NumberOfObservedEndogenousVariables=length(observable_name_requested_vars);
temp=NaN(NumberOfObservedEndogenousVariables,NumberOfExogenousVariables+1);
NumberOfObservedEndogenousVariables = length(observable_name_requested_vars);
temp = NaN(NumberOfObservedEndogenousVariables, NumberOfExogenousVariables+1);
if posterior
for i=1:NumberOfObservedEndogenousVariables
for j=1:NumberOfExogenousVariables
temp(i,j,:)=oo_.PosteriorTheoreticalMoments.dsge.VarianceDecompositionME.Mean.(deblank(observable_name_requested_vars{i,1})).(deblank(M_.exo_names(j,:)));
temp(i,j,:) = oo_.PosteriorTheoreticalMoments.dsge.VarianceDecompositionME.Mean.(observable_name_requested_vars{i}).(M_.exo_names{j});
end
endo_index_varlist=strmatch(deblank(observable_name_requested_vars{i,1}),var_list_,'exact');
oo_ = posterior_analysis('decomposition',var_list_(endo_index_varlist,:),'ME',[],options_,M_,oo_);
temp(i,j+1,:)=oo_.PosteriorTheoreticalMoments.dsge.VarianceDecompositionME.Mean.(deblank(observable_name_requested_vars{i,1})).('ME');
endo_index_varlist = strmatch(observable_name_requested_vars{i}, var_list_, 'exact');
oo_ = posterior_analysis('decomposition', var_list_{endo_index_varlist}, 'ME', [], options_, M_, oo_);
temp(i,j+1,:) = oo_.PosteriorTheoreticalMoments.dsge.VarianceDecompositionME.Mean.(observable_name_requested_vars{i}).('ME');
end
title='Posterior mean variance decomposition (in percent) with measurement error';
save_name_string='dsge_post_mean_var_decomp_uncond_ME';
else
for i=1:NumberOfObservedEndogenousVariables
for j=1:NumberOfExogenousVariables
temp(i,j,:)=oo_.PriorTheoreticalMoments.dsge.VarianceDecompositionME.Mean.(deblank(observable_name_requested_vars(i,:))).(deblank(M_.exo_names(j,:)));
temp(i,j,:) = oo_.PriorTheoreticalMoments.dsge.VarianceDecompositionME.Mean.(observable_name_requested_vars{i}).(M_.exo_names{j});
end
endo_index_varlist=strmatch(deblank(observable_name_requested_vars{i,1}),var_list_,'exact');
oo_ = prior_analysis('decomposition',var_list_(endo_index_varlist,:),'ME',[],options_,M_,oo_);
temp(i,j+1,:)=oo_.PriorTheoreticalMoments.dsge.VarianceDecompositionME.Mean.(deblank(observable_name_requested_vars{i,1})).('ME');
endo_index_varlist = strmatch(observable_name_requested_vars{i}, var_list_, 'exact');
oo_ = prior_analysis('decomposition', var_list_{endo_index_varlist}, 'ME', [], options_, M_, oo_);
temp(i,j+1,:) = oo_.PriorTheoreticalMoments.dsge.VarianceDecompositionME.Mean.(observable_name_requested_vars{i}).('ME');
end
title='Prior mean variance decomposition (in percent) with measurement error';
save_name_string='dsge_prior_mean_var_decomp_uncond_ME';
end
title=add_filter_subtitle(title,options_);
title=add_filter_subtitle(title, options_);
headers = M_.exo_names;
headers(M_.exo_names_orig_ord,:) = headers;
headers = char(' ',headers,'ME');
lh = size(deblank(var_list_),2)+2;
dyntable(options_,title,headers,deblank(char(observable_name_requested_vars)),100* ...
temp,lh,8,2);
headers(M_.exo_names_orig_ord) = headers;
headers = vertcat(' ', headers, 'ME');
lh = cellofchararraymaxlength(var_list_)+2;
dyntable(options_, title, headers, observable_name_requested_vars,100*temp,lh,8,2);
if options_.TeX
headers=M_.exo_names_tex;
headers = char(' ',headers,'ME');
labels = deblank(var_list_tex(varlist_pos,:));
lh = size(labels,2)+2;
dyn_latex_table(M_,options_,title,save_name_string,headers,labels,100*temp,lh,8,2);
headers = M_.exo_names_tex;
headers = vertcat(' ', headers, 'ME');
labels = var_list_tex(varlist_pos);
lh = cellofchararraymaxlength(labels)+2;
dyn_latex_table(M_, options_, title, save_name_string, headers, labels, 100*temp, lh, 8, 2);
end
skipline();
end
end
% CONDITIONAL VARIANCE DECOMPOSITION.
% CONDITIONAL VARIANCE DECOMPOSITION.
if Steps
temp=NaN(NumberOfEndogenousVariables,NumberOfExogenousVariables,length(Steps));
temp = NaN(NumberOfEndogenousVariables, NumberOfExogenousVariables, length(Steps));
if posterior
for i=1:NumberOfEndogenousVariables
for j=1:NumberOfExogenousVariables
oo_ = posterior_analysis('conditional decomposition',i,M_.exo_names(j,:),Steps,options_,M_,oo_);
temp(i,j,:)=oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.Mean.(deblank(var_list_(i,:))).(deblank(M_.exo_names(j,:)));
oo_ = posterior_analysis('conditional decomposition', var_list_{i}, M_.exo_names{j}, Steps, options_, M_, oo_);
temp(i,j,:) = oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.Mean.(var_list_{i}).(M_.exo_names{j});
end
end
title='Posterior mean conditional variance decomposition (in percent)';
save_name_string='dsge_post_mean_var_decomp_cond_h';
title = 'Posterior mean conditional variance decomposition (in percent)';
save_name_string = 'dsge_post_mean_var_decomp_cond_h';
else
for i=1:NumberOfEndogenousVariables
for j=1:NumberOfExogenousVariables
oo_ = prior_analysis('conditional decomposition',var_list_(i,:),M_.exo_names(j,:),Steps,options_,M_,oo_);
temp(i,j,:)=oo_.PriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.Mean.(deblank(var_list_(i,:))).(deblank(M_.exo_names(j,:)));
oo_ = prior_analysis('conditional decomposition', var_list_{i}, M_.exo_names{j}, Steps, options_, M_, oo_);
temp(i,j,:) = oo_.PriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.Mean.(var_list_{i}).(M_.exo_names{j});
end
end
title='Prior mean conditional variance decomposition (in percent)';
save_name_string='dsge_prior_mean_var_decomp_cond_h';
title = 'Prior mean conditional variance decomposition (in percent)';
save_name_string = 'dsge_prior_mean_var_decomp_cond_h';
end
for step_iter=1:length(Steps)
title_print=[title, ' Period ' int2str(Steps(step_iter))];
headers = M_.exo_names;
headers(M_.exo_names_orig_ord,:) = headers;
headers = char(' ',headers);
lh = size(deblank(var_list_),2)+2;
dyntable(options_,title_print,headers,deblank(var_list_),100* ...
headers(M_.exo_names_orig_ord) = headers;
headers = vertcat(' ', headers);
lh = cellofchararraymaxlength(var_list_)+2;
dyntable(options_,title_print,headers, var_list_,100* ...
temp(:,:,step_iter),lh,8,2);
if options_.TeX
headers=M_.exo_names_tex;
headers = char(' ',headers);
labels = deblank(var_list_tex);
lh = size(labels,2)+2;
dyn_latex_table(M_,options_,title_print,[save_name_string,int2str(Steps(step_iter))],headers,labels,100*temp(:,:,step_iter),lh,8,2);
headers = M_.exo_names_tex;
headers = vertcat(' ', headers);
labels = var_list_tex;
lh = cellofchararraymaxlength(labels)+2;
dyn_latex_table(M_, options_, title_print, [save_name_string, int2str(Steps(step_iter))], headers, labels, 100*temp(:,:,step_iter), lh, 8, 2);
end
end
skipline();
if ~all(M_.H==0)
if ~isempty(observable_name_requested_vars)
NumberOfObservedEndogenousVariables=length(observable_name_requested_vars);
NumberOfObservedEndogenousVariables = length(observable_name_requested_vars);
temp=NaN(NumberOfObservedEndogenousVariables,NumberOfExogenousVariables+1,length(Steps));
if posterior
for i=1:NumberOfObservedEndogenousVariables
for j=1:NumberOfExogenousVariables
temp(i,j,:)=oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecompositionME.Mean.(deblank(observable_name_requested_vars{i,1})).(deblank(M_.exo_names(j,:)));
temp(i,j,:) = oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecompositionME.Mean.(observable_name_requested_vars{i}).(M_.exo_names{j});
end
endo_index_varlist=strmatch(deblank(observable_name_requested_vars{i,1}),var_list_,'exact');
oo_ = posterior_analysis('conditional decomposition',endo_index_varlist,'ME',Steps,options_,M_,oo_);
temp(i,j+1,:)=oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecompositionME.Mean.(deblank(observable_name_requested_vars{i,1})).('ME');
end
title='Posterior mean conditional variance decomposition (in percent) with measurement error';
save_name_string='dsge_post_mean_var_decomp_ME_cond_h';
endo_index_varlist = strmatch(observable_name_requested_vars{i}, var_list_, 'exact');
oo_ = posterior_analysis('conditional decomposition', var_list_{endo_index_varlist}, 'ME', Steps, options_, M_, oo_);
temp(i,j+1,:) = oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecompositionME.Mean.(observable_name_requested_vars{i}).('ME');
end
title = 'Posterior mean conditional variance decomposition (in percent) with measurement error';
save_name_string = 'dsge_post_mean_var_decomp_ME_cond_h';
else
for i=1:NumberOfObservedEndogenousVariables
for j=1:NumberOfExogenousVariables
temp(i,j,:)=oo_.PriorTheoreticalMoments.dsge.ConditionalVarianceDecompositionME.Mean.(deblank(observable_name_requested_vars(i,:))).(deblank(M_.exo_names(j,:)));
temp(i,j,:) = oo_.PriorTheoreticalMoments.dsge.ConditionalVarianceDecompositionME.Mean.(observable_name_requested_vars{i}).(M_.exo_names{j});
end
endo_index_varlist=strmatch(deblank(observable_name_requested_vars{i,1}),var_list_,'exact');
oo_ = prior_analysis('conditional decomposition',endo_index_varlist,'ME',Steps,options_,M_,oo_);
temp(i,j+1,:)=oo_.PriorTheoreticalMoments.dsge.ConditionalVarianceDecompositionME.Mean.(deblank(observable_name_requested_vars{i,1})).('ME');
end
title='Prior mean conditional variance decomposition (in percent) with measurement error';
save_name_string='dsge_prior_mean_var_decomp_ME_cond_h';
endo_index_varlist = strmatch(observable_name_requested_vars{i}, var_list_, 'exact');
oo_ = prior_analysis('conditional decomposition', var_list_{endo_index_varlist}, 'ME', Steps, options_, M_, oo_);
temp(i,j+1,:) = oo_.PriorTheoreticalMoments.dsge.ConditionalVarianceDecompositionME.Mean.(observable_name_requested_vars{i}).('ME');
end
title = 'Prior mean conditional variance decomposition (in percent) with measurement error';
save_name_string = 'dsge_prior_mean_var_decomp_ME_cond_h';
end
for step_iter=1:length(Steps)
title_print=[title, ' Period ' int2str(Steps(step_iter))];
title_print = [title, ' Period ' int2str(Steps(step_iter))];
headers = M_.exo_names;
headers(M_.exo_names_orig_ord,:) = headers;
headers = char(' ',headers,'ME');
lh = size(deblank(var_list_),2)+2;
dyntable(options_,title_print,headers,deblank(char(observable_name_requested_vars)),100* ...
temp(:,:,step_iter),lh,8,2);
headers(M_.exo_names_orig_ord) = headers;
headers = vertcat(' ', headers, 'ME');
lh = cellofchararraymaxlength(var_list_)+2;
dyntable(options_, title_print, headers, observable_name_requested_vars, 100*temp(:,:,step_iter), lh, 8, 2);
if options_.TeX
headers=M_.exo_names_tex;
headers = char(' ',headers,'ME');
labels = deblank(var_list_tex(varlist_pos,:));
lh = size(labels,2)+2;
dyn_latex_table(M_,options_,title_print,[save_name_string,int2str(Steps(step_iter))],headers,labels,100*temp(:,:,step_iter),lh,8,2);
headers = M_.exo_names_tex;
headers = vertcat(' ', headers, 'ME');
labels = var_list_tex(varlist_pos);
lh = cellofchararraymaxlength(labels)+2;
dyn_latex_table(M_, options_, title_print, [save_name_string, int2str(Steps(step_iter))], headers, labels, 100*temp(:,:,step_iter), lh, 8, 2);
end
end
skipline();
end
end
end
end
end

27
matlab/conditional_variance_decomposition_ME_mc_analysis.m
View File

@ -1,5 +1,5 @@
function oo_ = ...
conditional_variance_decomposition_ME_mc_analysis(NumberOfSimulations, type, dname, fname, Steps, exonames, exo, var_list, endogenous_variable_index, mh_conf_sig, oo_,options_)
conditional_variance_decomposition_ME_mc_analysis(NumberOfSimulations, type, dname, fname, Steps, exonames, exo, var_list, endo, mh_conf_sig, oo_,options_)
% This function analyses the (posterior or prior) distribution of the
% endogenous variables' conditional variance decomposition with measurement error.
%
@ -14,8 +14,7 @@ function oo_ = ...
% variable
% var_list [string] (n_endo*char_length) character array with name
% of endogenous variables
% endogenous_variable_index [integer] index of the current
% endogenous variable
% endo [integer] Current endogenous variable
% mh_conf_sig [double] 2 by 1 vector with upper
% and lower bound of HPD intervals
% oo_ [structure] Dynare structure where the results are saved.
@ -23,7 +22,7 @@ function oo_ = ...
% OUTPUTS
% oo_ [structure] Dynare structure where the results are saved.
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2017-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -48,16 +47,16 @@ else
PATH = [dname '/prior/moments/'];
end
% $$$ indx = check_name(vartan,var);
% $$$ if isempty(indx)
% $$$ disp([ type '_analysis:: ' var ' is not a stationary endogenous variable!'])
% $$$ return
% $$$ end
% $$$ endogenous_variable_index = sum(1:indx);
endogenous_variable_index = check_name(var_list, endo);
if isempty(endogenous_variable_index)
disp([ type '_analysis:: Can''t find ' endo '!'])
return
end
exogenous_variable_index = check_name(exonames,exo);
if isempty(exogenous_variable_index)
if isequal(exo,'ME')
exogenous_variable_index=size(exonames,1)+1;
exogenous_variable_index=length(exonames)+1;
else
disp([ type '_analysis:: ' exo ' is not a declared exogenous variable!'])
return
@ -65,9 +64,9 @@ if isempty(exogenous_variable_index)
end
[observable_pos_requested_vars,index_subset,index_observables]=intersect(var_list,options_.varobs,'stable');
matrix_pos=strmatch(var_list(endogenous_variable_index,:),var_list(index_subset,:),'exact');
name_1 = deblank(var_list(endogenous_variable_index,:));
name_2 = deblank(exo);
matrix_pos=strmatch(endo, var_list(index_subset),'exact');
name_1 = endo;
name_2 = exo;
name = [ name_1 '.' name_2 ];
if isfield(oo_, [ TYPE 'TheoreticalMoments' ])

20
matlab/conditional_variance_decomposition_mc_analysis.m
View File

@ -1,5 +1,5 @@
function oo_ = ...
conditional_variance_decomposition_mc_analysis(NumberOfSimulations, type, dname, fname, Steps, exonames, exo, var_list, endogenous_variable_index, mh_conf_sig, oo_,options_)
conditional_variance_decomposition_mc_analysis(NumberOfSimulations, type, dname, fname, Steps, exonames, exo, var_list, endo, mh_conf_sig, oo_,options_)
% This function analyses the (posterior or prior) distribution of the
% endogenous variables' conditional variance decomposition.
%
@ -23,7 +23,7 @@ function oo_ = ...
% OUTPUTS
% oo_ [structure] Dynare structure where the results are saved.
% Copyright (C) 2009-2017 Dynare Team
% Copyright (C) 2009-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -48,12 +48,6 @@ else
PATH = [dname '/prior/moments/'];
end
% $$$ indx = check_name(vartan,var);
% $$$ if isempty(indx)
% $$$ disp([ type '_analysis:: ' var ' is not a stationary endogenous variable!'])
% $$$ return
% $$$ end
% $$$ endogenous_variable_index = sum(1:indx);
exogenous_variable_index = check_name(exonames,exo);
if isempty(exogenous_variable_index)
if ~isequal(exo,'ME')
@ -62,8 +56,14 @@ if isempty(exogenous_variable_index)
return
end
name_1 = deblank(var_list(endogenous_variable_index,:));
name_2 = deblank(exo);
endogenous_variable_index = check_name(var_list, endo);
if isempty(endogenous_variable_index)
disp([ type '_analysis:: Can''t find ' endo '!'])
return
end
name_1 = endo;
name_2 = exo;
name = [ name_1 '.' name_2 ];
if isfield(oo_, [ TYPE 'TheoreticalMoments' ])

92
matlab/convergence_diagnostics/McMCDiagnostics.m
View File

@ -16,7 +16,7 @@ function oo_ = McMCDiagnostics(options_, estim_params_, M_, oo_)
% PARALLEL CONTEXT
% See the comment in posterior_sampler.m funtion.
% Copyright (C) 2005-2017 Dynare Team
% Copyright (C) 2005-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -77,41 +77,42 @@ TotalNumberOfMhDraws = sum(record.MhDraws(:,1));
FirstMhFile = record.KeepedDraws.FirstMhFile;
NumberOfDraws = TotalNumberOfMhDraws-floor(options_.mh_drop*TotalNumberOfMhDraws);
param_name=[];
param_name_tex=[];
for jj=1:npar
param_name = {};
param_name_tex = {};
for jj = 1:npar
if options_.TeX
[par_name_temp,par_name_tex_temp]=get_the_name(jj,options_.TeX,M_,estim_params_,options_);
param_name = strvcat(param_name,par_name_temp);
[par_name_temp, par_name_tex_temp] = get_the_name(jj, options_.TeX, M_,estim_params_, options_);
param_name = vertcat(param_name, par_name_temp);
par_name_tex_temp = strrep(par_name_tex_temp,'$','');
param_name_tex = strvcat(param_name_tex,par_name_tex_temp);
param_name_tex = vertcat(param_name_tex, par_name_tex_temp);
else
[par_name_temp]=get_the_name(jj,options_.TeX,M_,estim_params_,options_);
param_name = strvcat(param_name,par_name_temp);
par_name_temp = get_the_name(jj, options_.TeX, M_, estim_params_, options_);
param_name = vertcat(param_name, par_name_temp);
end
Draws = GetAllPosteriorDraws(jj,FirstMhFile,FirstLine,TotalNumberOfMhFiles,NumberOfDraws);
Draws = reshape(Draws,[NumberOfDraws nblck]);
Draws = GetAllPosteriorDraws(jj, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
Draws = reshape(Draws, [NumberOfDraws nblck]);
Nc = min(1000, NumberOfDraws/2);
for ll=1:nblck
for ll = 1:nblck
Ifac(ll,jj) = mcmc_ifac(Draws(:,ll), Nc);
end
tmp = num2cell(Ifac(:,jj));
end
my_title='MCMC Inefficiency factors per block';
IFAC_header='Parameter';
IFAC_header_tex='Parameter';
for j=1:nblck
IFAC_header = char(IFAC_header,['Block ' int2str(j)]);
IFAC_header_tex = char(IFAC_header_tex,['Block~' int2str(j)]);
IFAC_header = {'Parameter'};
IFAC_header_tex = {'Parameter'};
for j = 1:nblck
IFAC_header = vertcat(IFAC_header, ['Block ' int2str(j)]);
IFAC_header_tex = vertcat(IFAC_header_tex, ['Block~' int2str(j)]);
end
lh = size(param_name,2)+2;
dyntable(options_,my_title,IFAC_header,param_name,Ifac',lh,12,3);
lh = cellofchararraymaxlength(param_name)+2;
dyntable(options_, my_title, IFAC_header, param_name, Ifac', lh, 12, 3);
skipline()
if options_.TeX
dyn_latex_table(M_,options_,my_title,'MCMC_inefficiency_factors',IFAC_header_tex,param_name_tex,Ifac',lh,12,3);
dyn_latex_table(M_, options_, my_title, 'MCMC_inefficiency_factors', IFAC_header_tex, param_name_tex, Ifac', lh, 12, 3);
end
record.InefficiencyFactorsPerBlock = Ifac;
update_last_mh_history_file(MetropolisFolder, ModelName, record);
@ -137,25 +138,25 @@ if nblck == 1 % Brooks and Gelman tests need more than one block
first_obs_begin_sample = max(1,ceil(options_.mh_drop*NumberOfDraws));
last_obs_begin_sample = first_obs_begin_sample+round(options_.convergence.geweke.geweke_interval(1)*NumberOfDraws*(1-options_.mh_drop));
first_obs_end_sample = first_obs_begin_sample+round(options_.convergence.geweke.geweke_interval(2)*NumberOfDraws*(1-options_.mh_drop));
param_name=[];
param_name = {};
if options_.TeX
param_name_tex=[];
param_name_tex = {};
end
for jj=1:npar
if options_.TeX
[param_name_temp, param_name_tex_temp]= get_the_name(jj,options_.TeX,M_,estim_params_,options_);
param_name_tex = strvcat(param_name_tex,strrep(param_name_tex_temp,'$',''));
param_name = strvcat(param_name,param_name_temp);
[param_name_temp, param_name_tex_temp] = get_the_name(jj, options_.TeX, M_, estim_params_, options_);
param_name_tex = vertcat(param_name_tex, strrep(param_name_tex_temp, '$',''));
param_name = vertcat(param_name, param_name_temp);
else
param_name_temp = get_the_name(jj,options_.TeX,M_,estim_params_,options_);
param_name = strvcat(param_name,param_name_temp);
param_name_temp = get_the_name(jj, options_.TeX, M_,estim_params_, options_);
param_name = vertcat(param_name, param_name_temp);
end
end
fprintf('\nGeweke (1992) Convergence Tests, based on means of draws %d to %d vs %d to %d.\n',first_obs_begin_sample,last_obs_begin_sample,first_obs_end_sample,NumberOfDraws);
fprintf('p-values are for Chi2-test for equality of means.\n');
Geweke_header=char('Parameter', 'Post. Mean', 'Post. Std', 'p-val No Taper');
for ii=1:length(options_.convergence.geweke.taper_steps)
Geweke_header=char(Geweke_header,['p-val ' num2str(options_.convergence.geweke.taper_steps(ii)),'% Taper']);
Geweke_header = {'Parameter'; 'Post. Mean'; 'Post. Std'; 'p-val No Taper'};
for ii = 1:length(options_.convergence.geweke.taper_steps)
Geweke_header = vertcat(Geweke_header, ['p-val ' num2str(options_.convergence.geweke.taper_steps(ii)),'% Taper']);
end
datamat=NaN(npar,3+length(options_.convergence.geweke.taper_steps));
for jj=1:npar
@ -175,22 +176,22 @@ if nblck == 1 % Brooks and Gelman tests need more than one block
[results_vec2] = geweke_moments(param_draws2,options_);
results_struct = geweke_chi2_test(results_vec1,results_vec2,results_struct,options_);
eval(['oo_.convergence.geweke.',param_name(jj,:),'=results_struct;'])
oo_.convergence.geweke.(param_name{jj}) = results_struct;
datamat(jj,:)=[results_struct.posteriormean,results_struct.posteriorstd,results_struct.prob_chi2_test];
end
lh = size(param_name,2)+2;
dyntable(options_,'',Geweke_header,param_name,datamat,lh,12,3);
dyntable(options_, '', Geweke_header, param_name, datamat, lh, 12, 3);
if options_.TeX
Geweke_tex_header=char('Parameter', 'Mean', 'Std', 'No\ Taper');
additional_header={[' & \multicolumn{2}{c}{Posterior} & \multicolumn{',num2str(1+length(options_.convergence.geweke.taper_steps)),'}{c}{p-values} \\'],
Geweke_tex_header = {'Parameter'; 'Mean'; 'Std'; 'No\ Taper'};
additional_header = {[' & \multicolumn{2}{c}{Posterior} & \multicolumn{',num2str(1+length(options_.convergence.geweke.taper_steps)),'}{c}{p-values} \\'],
['\cmidrule(r{.75em}){2-3} \cmidrule(r{.75em}){4-',num2str(4+length(options_.convergence.geweke.taper_steps)),'}']};
for ii=1:length(options_.convergence.geweke.taper_steps)
Geweke_tex_header=char(Geweke_tex_header,[num2str(options_.convergence.geweke.taper_steps(ii)),'\%%\ Taper']);
Geweke_tex_header = vertcat(Geweke_tex_header, [num2str(options_.convergence.geweke.taper_steps(ii)),'\%%\ Taper']);
end
headers = char(Geweke_tex_header);
lh = size(param_name_tex,2)+2;
headers = Geweke_tex_header;
lh = cellofchararraymaxlength(param_name_tex)+2;
my_title=sprintf('Geweke (1992) Convergence Tests, based on means of draws %d to %d vs %d to %d. p-values are for $\\\\chi^2$-test for equality of means.',first_obs_begin_sample,last_obs_begin_sample,first_obs_end_sample,NumberOfDraws);
dyn_latex_table(M_,options_,my_title,'geweke',headers,param_name_tex,datamat,lh,12,4,additional_header);
dyn_latex_table(M_, options_, my_title, 'geweke', headers, param_name_tex, datamat, lh, 12, 4, additional_header);
end
skipline(2);
@ -206,17 +207,16 @@ if nblck == 1 % Brooks and Gelman tests need more than one block
oo_.Raftery_Lewis = raftery_lewis(x2,Raftery_Lewis_q,Raftery_Lewis_r,Raftery_Lewis_s);
oo_.Raftery_Lewis.parameter_names=param_name;
my_title=sprintf('Raftery/Lewis (1992) Convergence Diagnostics, based on quantile q=%4.3f with precision r=%4.3f with probability s=%4.3f.',Raftery_Lewis_q,Raftery_Lewis_r,Raftery_Lewis_s);
headers = char('Variables','M (burn-in)','N (req. draws)','N+M (total draws)','k (thinning)');
headers = {'Variables'; 'M (burn-in)'; 'N (req. draws)'; 'N+M (total draws)'; 'k (thinning)'};
raftery_data_mat=[oo_.Raftery_Lewis.M_burn,oo_.Raftery_Lewis.N_prec,oo_.Raftery_Lewis.N_total,oo_.Raftery_Lewis.k_thin];
raftery_data_mat=[raftery_data_mat;max(raftery_data_mat)];
labels_Raftery_Lewis=char(param_name,'Maximum');
lh = size(labels_Raftery_Lewis,2)+2;
dyntable(options_,my_title,headers,labels_Raftery_Lewis,raftery_data_mat,lh,10,0);
labels_Raftery_Lewis = vertcat(param_name, 'Maximum');
lh = cellofchararraymaxlength(labels_Raftery_Lewis)+2;
dyntable(options_, my_title, headers, labels_Raftery_Lewis, raftery_data_mat, lh, 10, 0);
if options_.TeX
labels_Raftery_Lewis_tex=char(param_name_tex,'Maximum');
lh = size(labels_Raftery_Lewis_tex,2)+2;
dyn_latex_table(M_,options_,my_title,'raftery_lewis',headers,labels_Raftery_Lewis_tex,raftery_data_mat,lh,10,0);
labels_Raftery_Lewis_tex = vertcat(param_name_tex, 'Maximum');
lh = cellofchararraymaxlength(labels_Raftery_Lewis_tex)+2;
dyn_latex_table(M_, options_, my_title, 'raftery_lewis', headers, labels_Raftery_Lewis_tex, raftery_data_mat, lh, 10, 0);
end
end

20
matlab/datatomfile.m
View File

@ -17,7 +17,7 @@ function datatomfile (s, var_list, names)
% provided, all the variables as defined in M_.endo_names will be saved in
% the generated m file.
% Copyright (C) 2001-2017 Dynare Team
% Copyright (C) 2001-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -40,24 +40,28 @@ global M_ oo_
sm=[s,'.m'];
fid=fopen(sm,'w') ;
if nargin < 2 || size(var_list,1) == 0
var_list = M_.endo_names(1:M_.orig_endo_nbr,:);
if nargin < 2 || isempty(var_list)
var_list = M_.endo_names(1:M_.orig_endo_nbr);
end
n = size(var_list,1);
ivar=zeros(n,1);
n = length(var_list);
if nargin==3
if ~isequal(size(var_list,1),n)
names = cellstr(names);
n = length(names);
if ~isequal(length(var_list), n)
error('datatomfile:: Second and third arguments must have the same number of rows (variables)!')
end
else
names = var_list;
n = length(names);
end
ivar=zeros(n, 1);
% Get indices for the endogenous variables.
for i=1:n
i_tmp = strmatch(var_list(i,:),M_.endo_names,'exact');
i_tmp = strmatch(var_list{i}, M_.endo_names, 'exact');
if isempty(i_tmp)
error (['One of the specified variables does not exist']) ;
else
@ -69,7 +73,7 @@ fprintf(fid,'%% Dataset generated by %s.\n',stack(2).file);
fprintf(fid,['%% ' datestr(now,0) '\n']);
% Save the selected data.
for i = 1:n
fprintf(fid,[strtrim(names(i,:)), ' = ['],'\n') ;
fprintf(fid,[names{i}, ' = ['],'\n') ;
fprintf(fid,'\n') ;
fprintf(fid,'%15.8g\n',oo_.endo_simul(ivar(i),:)') ;
fprintf(fid,'];\n') ;

7
matlab/discretionary_policy.m
View File

@ -1,6 +1,6 @@
function info = discretionary_policy(var_list)
% Copyright (C) 2007-2015 Dynare Team
% Copyright (C) 2007-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -27,9 +27,8 @@ info = stoch_simul(var_list);
if options_.noprint == 0
disp_steady_state(M_,oo_)
for i=M_.orig_endo_nbr:M_.endo_nbr
if strmatch('mult_',M_.endo_names(i,:))
disp(sprintf('%s \t\t %g',M_.endo_names(i,:), ...
oo_.dr.ys(i)));
if strmatch('mult_', M_.endo_names{i})
disp(sprintf('%s \t\t %g', M_.endo_names{i}, oo_.dr.ys(i)));
end
end
end

8
matlab/discretionary_policy_1.m
View File

@ -1,6 +1,6 @@
function [dr,ys,info]=discretionary_policy_1(oo_,Instruments)
% Copyright (C) 2007-2017 Dynare Team
% Copyright (C) 2007-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -42,7 +42,7 @@ else
M_.orig_model = M_;
end
beta = get_optimal_policy_discount_factor(M_.params,M_.param_names);
beta = get_optimal_policy_discount_factor(M_.params, M_.param_names);
exo_nbr = M_.exo_nbr;
if isfield(M_,'orig_model')
@ -70,7 +70,7 @@ end
if any(any(Uy~=0))
non_zero_derivs=find(any(Uy~=0));
for ii=1:length(non_zero_derivs)
non_zero_deriv_names{ii,1}=deblank(M_.endo_names(non_zero_derivs(ii),:));
non_zero_deriv_names{ii,1} = M_.endo_names{non_zero_derivs(ii)};
end
disp_string=[non_zero_deriv_names{1,:}];
for ii=2:size(non_zero_deriv_names,1)
@ -116,7 +116,7 @@ end
instr_id=nan(instr_nbr,1);
for j=1:instr_nbr
vj=deblank(Instruments(j,:));
vj_id=strmatch(vj,endo_names,'exact');
vj_id=strmatch(vj, endo_names, 'exact');
if ~isempty(vj_id)
instr_id(j)=vj_id;
else

52
matlab/disp_dr.m
View File

@ -8,7 +8,7 @@ function disp_dr(dr,order,var_list)
% var_list [char array]: list of endogenous variables for which the
% decision rules should be printed
%
% Copyright (C) 2001-2017 Dynare Team
% Copyright (C) 2001-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -43,17 +43,17 @@ else
k1 = dr.order_var;
end
if size(var_list,1) == 0
var_list = M_.endo_names(1:M_.orig_endo_nbr, :);
if isempty(var_list)
var_list = M_.endo_names(1:M_.orig_endo_nbr);
end
nvar = size(var_list,1);
nvar = length(var_list);
ivar=zeros(nvar,1);
for i=1:nvar
i_tmp = strmatch(var_list(i,:),M_.endo_names(k1,:),'exact');
i_tmp = strmatch(var_list{i}, M_.endo_names(k1), 'exact');
if isempty(i_tmp)
disp(var_list(i,:));
disp(var_list{i});
error (['One of the variable specified does not exist']) ;
else
ivar(i) = i_tmp;
@ -63,7 +63,7 @@ end
% get length of display strings
header_label_length=16; %default
for ii=1:length(ivar)
header_label_length=max(header_label_length,length(deblank(M_.endo_names(k1(ivar(ii)),:)))+2);
header_label_length = max(header_label_length,length(M_.endo_names{k1(ivar(ii))})+2);
end
header_label_format = sprintf('%%%ds',header_label_length);
value_format_float = sprintf('%%%d.6f',header_label_length);
@ -81,7 +81,7 @@ else
aux_var_additional_characters=0;
end
var_name_width=max([max(size(deblank(M_.endo_names(k1(ivar),:)),2)),max(size(deblank(M_.exo_names),2))]);
var_name_width = max([cellofchararraymaxlength(M_.endo_names(k1(ivar))), cellofchararraymaxlength(M_.exo_names)]);
%deal with covariances
if order > 1
@ -97,7 +97,7 @@ disp('POLICY AND TRANSITION FUNCTIONS')
% variable names
str = char(32*ones(1,var_name_width));
for i=1:nvar
str = [str sprintf(header_label_format,deblank(M_.endo_names(k1(ivar(i)),:)))];
str = [str sprintf(header_label_format, M_.endo_names{k1(ivar(i))})];
end
disp(str);
%
@ -150,10 +150,10 @@ end
%
for k=1:nu
flag = 0;
str = sprintf(label_format,M_.exo_names(k,:));
str = sprintf(label_format, M_.exo_names{k});
for i=1:nvar
x = dr.ghu(ivar(i),k);
[str,flag]=get_print_string(str,x,value_format_zero,value_format_float,flag,options_);
[str,flag] = get_print_string(str, x, value_format_zero, value_format_float, flag, options_);
end
if flag
disp(str)
@ -167,7 +167,7 @@ if order > 1
flag = 0;
str1 = sprintf('%s,%s',subst_auxvar(k1(klag(k,1)),klag(k,2)-M_.maximum_lag-2), ...
subst_auxvar(k1(klag(j,1)),klag(j,2)-M_.maximum_lag-2));
str = sprintf(label_format,str1);
str = sprintf(label_format, str1);
for i=1:nvar
if k == j
x = dr.ghxx(ivar(i),(k-1)*nx+j)/2;
@ -187,14 +187,14 @@ if order > 1
for k = 1:nu
for j = 1:k
flag = 0;
str = sprintf(label_format,[deblank(M_.exo_names(k,:)) ',' deblank(M_.exo_names(j,:))] );
str = sprintf(label_format, [M_.exo_names{k} ',' M_.exo_names{j}]);
for i=1:nvar
if k == j
x = dr.ghuu(ivar(i),(k-1)*nu+j)/2;
else
x = dr.ghuu(ivar(i),(k-1)*nu+j);
end
[str,flag]=get_print_string(str,x,value_format_zero,value_format_float,flag,options_);
[str,flag]=get_print_string(str, x, value_format_zero, value_format_float, flag, options_);
end
if flag
disp(str)
@ -207,8 +207,7 @@ if order > 1
for k = 1:nx
for j = 1:nu
flag = 0;
str1 = sprintf('%s,%s',subst_auxvar(k1(klag(k,1)),klag(k,2)-M_.maximum_lag-2), ...
deblank(M_.exo_names(j,:)));
str1 = sprintf('%s,%s',subst_auxvar(k1(klag(k,1)),klag(k,2)-M_.maximum_lag-2), M_.exo_names{j});
str = sprintf(label_format,str1);
for i=1:nvar
x = dr.ghxu(ivar(i),(k-1)*nu+j);
@ -230,41 +229,40 @@ function str = subst_auxvar(aux_index, aux_lead_lag)
global M_
if aux_index <= M_.orig_endo_nbr
str = sprintf('%s(%d)', deblank(M_.endo_names(aux_index,:)), aux_lead_lag);
str = sprintf('%s(%d)', M_.endo_names{aux_index}, aux_lead_lag);
return
end
for i = 1:length(M_.aux_vars)
if M_.aux_vars(i).endo_index == aux_index
switch M_.aux_vars(i).type
case 0
str = sprintf('%s(%d)',deblank(M_.endo_names(aux_index,:)),aux_lead_lag);
str = sprintf('%s(%d)', M_.endo_names{aux_index}, aux_lead_lag);
return
case 1
orig_name = deblank(M_.endo_names(M_.aux_vars(i).orig_index, :));
orig_name = M_.endo_names{M_.aux_vars(i).orig_index};
case 3
orig_name = deblank(M_.exo_names(M_.aux_vars(i).orig_index, :));
orig_name = M_.exo_names{M_.aux_vars(i).orig_index};
case 4
str = sprintf('EXPECTATION(%d)(...)', aux_lead_lag);
return
case 6
str = sprintf('%s(%d)', ...
deblank(M_.endo_names(M_.aux_vars(i).endo_index, :)),aux_lead_lag);
str = sprintf('%s(%d)', M_.endo_names{M_.aux_vars(i).endo_index}, aux_lead_lag);
return
otherwise
error(sprintf('Invalid auxiliary type: %s', M_.endo_names(aux_index, :)))
error(sprintf('Invalid auxiliary type: %s', M_.endo_names{aux_index}))
end
str = sprintf('%s(%d)', orig_name, M_.aux_vars(i).orig_lead_lag+aux_lead_lag);
return
end
end
error(sprintf('Could not find aux var: %s', M_.endo_names(aux_index, :)))
error(sprintf('Could not find aux var: %s', M_.endo_names{aux_index}))
end
function [str,flag]=get_print_string(str,x,value_format_zero,value_format_float,flag,options_)
function [str,flag]=get_print_string(str, x, value_format_zero, value_format_float, flag, options_)
if abs(x) >= options_.dr_display_tol
flag = 1;
str = [str sprintf(value_format_float,x)];
str = [str sprintf(value_format_float, x)];
else
str = [str sprintf(value_format_zero,0)];
str = [str sprintf(value_format_zero, 0)];
end
end

10
matlab/disp_model_summary.m
View File

@ -8,7 +8,7 @@ function disp_model_summary(M,dr,options)
% dr [matlab structure] Decision rules
% options [matlab structure] Options
%
% Copyright (C) 2001-2017 Dynare Team
% Copyright (C) 2001-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -36,7 +36,7 @@ disp([' Number of jumpers: ' ...
int2str(length(find(dr.kstate(:,2) == M.maximum_lag+2)))])
disp([' Number of static variables: ' int2str(M.nstatic)])
my_title='MATRIX OF COVARIANCE OF EXOGENOUS SHOCKS';
labels = deblank(M.exo_names);
headers = char('Variables',labels);
lh = size(labels,2)+2;
dyntable(options,my_title,headers,labels,M.Sigma_e,lh,10,6);
labels = M.exo_names;
headers = vertcat('Variables', labels);
lh = cellofchararraymaxlength(labels)+2;
dyntable(options, my_title, headers, labels, M.Sigma_e, lh, 10, 6);

88
matlab/disp_moments.m
View File

@ -11,7 +11,7 @@ function oo_=disp_moments(y,var_list,M_,options_,oo_)
% OUTPUTS
% oo_ [structure] Dynare's results structure,
% Copyright (C) 2001-2017 Dynare Team
% Copyright (C) 2001-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -31,16 +31,16 @@ function oo_=disp_moments(y,var_list,M_,options_,oo_)
warning_old_state = warning;
warning off
if size(var_list,1) == 0
var_list = M_.endo_names(1:M_.orig_endo_nbr, :);
if isempty(var_list)
var_list = M_.endo_names(1:M_.orig_endo_nbr);
end
nvar = size(var_list,1);
nvar = length(var_list);
ivar=zeros(nvar,1);
for i=1:nvar
i_tmp = strmatch(var_list(i,:),M_.endo_names,'exact');
i_tmp = strmatch(var_list{i}, M_.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
@ -50,7 +50,7 @@ y = y(ivar,options_.drop+1:end)';
ME_present=0;
if ~all(M_.H==0)
[observable_pos_requested_vars,index_subset,index_observables]=intersect(ivar,options_.varobs_id,'stable');
[observable_pos_requested_vars, index_subset, index_observables] = intersect(ivar, options_.varobs_id, 'stable');
if ~isempty(observable_pos_requested_vars)
ME_present=1;
i_ME = setdiff([1:size(M_.H,1)],find(diag(M_.H) == 0)); % find ME with 0 variance
@ -79,20 +79,17 @@ oo_.var = y'*y/size(y,1);
oo_.skewness = (mean(y.^3)./s2.^1.5)';
oo_.kurtosis = (mean(y.^4)./(s2.*s2)-3)';
labels = deblank(M_.endo_names(ivar,:));
labels_TeX = deblank(M_.endo_names_tex(ivar,:));
labels = M_.endo_names(ivar);
labels_TeX = M_.endo_names_tex(ivar);
if options_.nomoments == 0
z = [ m' s' s2' (mean(y.^3)./s2.^1.5)' (mean(y.^4)./(s2.*s2)-3)' ];
title='MOMENTS OF SIMULATED VARIABLES';
title=add_filter_subtitle(title,options_);
headers=char('VARIABLE','MEAN','STD. DEV.','VARIANCE','SKEWNESS', ...
'KURTOSIS');
dyntable(options_,title,headers,labels,z,size(labels,2)+2,16,6);
title=add_filter_subtitle(title, options_);
headers = {'VARIABLE'; 'MEAN'; 'STD. DEV.'; 'VARIANCE'; 'SKEWNESS'; 'KURTOSIS'};
dyntable(options_, title, headers, labels, z, cellofchararraymaxlength(labels)+2, 16, 6);
if options_.TeX
dyn_latex_table(M_,options_,title,'sim_moments',headers,labels_TeX,z,size(labels,2)+2,16,6);
dyn_latex_table(M_, options_, title, 'sim_moments', headers, labels_TeX, z, cellofchararraymaxlength(labels)+2, 16, 6);
end
end
@ -103,15 +100,13 @@ if options_.nocorr == 0
end
if options_.noprint == 0
title = 'CORRELATION OF SIMULATED VARIABLES';
title=add_filter_subtitle(title,options_);
headers = char('VARIABLE',M_.endo_names(ivar,:));
dyntable(options_,title,headers,labels,corr,size(labels,2)+2,8,4);
headers = vertcat('VARIABLE', M_.endo_names(ivar));
dyntable(options_, title, headers, labels, corr, cellofchararraymaxlength(labels)+2, 8, 4);
if options_.TeX
headers = char('VARIABLE',M_.endo_names_tex(ivar,:));
lh = size(labels,2)+2;
dyn_latex_table(M_,options_,title,'sim_corr_matrix',headers,labels_TeX,corr,size(labels,2)+2,8,4);
headers = vertcat('VARIABLE', M_.endo_names_tex(ivar));
lh = cellofchararraymaxlength(labels)+2;
dyn_latex_table(M_, options_, title, 'sim_corr_matrix', headers, labels_TeX, corr, lh, 8,4);
end
end
end
@ -130,12 +125,12 @@ if ar > 0
if options_.noprint == 0
title = 'AUTOCORRELATION OF SIMULATED VARIABLES';
title=add_filter_subtitle(title,options_);
headers = char('VARIABLE',int2str([1:ar]'));
dyntable(options_,title,headers,labels,autocorr,size(labels,2)+2,8,4);
headers = vertcat('VARIABLE', cellstr(int2str([1:ar]')));
dyntable(options_, title, headers, labels, autocorr, cellofchararraymaxlength(labels)+2, 8, 4);
if options_.TeX
headers = char('VARIABLE',int2str([1:ar]'));
lh = size(labels,2)+2;
dyn_latex_table(M_,options_,title,'sim_autocorr_matrix',headers,labels_TeX,autocorr,size(labels_TeX,2)+2,8,4);
headers = vertcat('VARIABLE', cellstr(int2str([1:ar]')));
lh = cellofchararraymaxlength(labels)+2;
dyn_latex_table(M_, options_, title, 'sim_autocorr_matrix', headers, labels_TeX, autocorr, cellofchararraymaxlength(labels_TeX)+2, 8, 4);
end
end
@ -180,28 +175,31 @@ if ~options_.nodecomposition
if ~options_.noprint %options_.nomoments == 0
skipline()
title='VARIANCE DECOMPOSITION SIMULATING ONE SHOCK AT A TIME (in percent)';
title=add_filter_subtitle(title,options_);
headers = M_.exo_names;
headers(M_.exo_names_orig_ord,:) = headers;
headers = char(' ',headers);
lh = size(deblank(M_.endo_names(ivar,:)),2)+2;
dyntable(options_,title,char(headers,'Tot. lin. contr.'),deblank(M_.endo_names(ivar,:)),[oo_.variance_decomposition sum(oo_.variance_decomposition,2)],lh,8,2);
headers(M_.exo_names_orig_ord) = headers;
headers = vertcat(' ', headers);
lh = cellofchararraymaxlength(M_.endo_names(ivar))+2;
dyntable(options_, title, vertcat(headers, 'Tot. lin. contr.'), ...
M_.endo_names(ivar), [oo_.variance_decomposition sum(oo_.variance_decomposition,2)], lh, 8, 2);
if ME_present
headers_ME=char(headers,'ME');
dyntable(options_,[title,' WITH MEASUREMENT ERROR'],char(headers_ME,'Tot. lin. contr.'),deblank(M_.endo_names(ivar(index_subset), ...
:)),[oo_.variance_decomposition_ME sum(oo_.variance_decomposition_ME,2)],lh,8,2);
headers_ME = vertcat(headers, 'ME');
dyntable(options_, [title,' WITH MEASUREMENT ERROR'], vertcat(headers_ME, 'Tot. lin. contr.'), M_.endo_names(ivar(index_subset)), ...
[oo_.variance_decomposition_ME sum(oo_.variance_decomposition_ME, 2)], lh, 8, 2);
end
if options_.TeX
headers=M_.exo_names_tex;
headers = char(' ',headers);
labels = deblank(M_.endo_names_tex(ivar,:));
lh = size(labels,2)+2;
dyn_latex_table(M_,options_,title,'sim_var_decomp',char(headers,'Tot. lin. contr.'),labels_TeX,[oo_.variance_decomposition sum(oo_.variance_decomposition,2)],lh,8,2);
headers = M_.exo_names_tex;
headers = vertcat(' ', headers);
labels = M_.endo_names_tex(ivar);
lh = cellofchararraymaxlength(labels)+2;
dyn_latex_table(M_, options_, title, 'sim_var_decomp', vertcat(headers, 'Tot. lin. contr.'), ...
labels_TeX, [oo_.variance_decomposition sum(oo_.variance_decomposition, 2)], lh, 8, 2);
if ME_present
headers_ME=char(headers,'ME');
dyn_latex_table(M_,options_,[title,' WITH MEASUREMENT ERROR'],'sim_var_decomp_ME',char(headers_ME,'Tot. lin. contr.'),labels_TeX(ivar(index_subset),:),[oo_.variance_decomposition_ME sum(oo_.variance_decomposition_ME,2)],lh,8,2);
headers_ME = vertcat(headers, 'ME');
dyn_latex_table(M_, options_, [title, ' WITH MEASUREMENT ERROR'], 'sim_var_decomp_ME', ...
vertcat(headers_ME, 'Tot. lin. contr.'), ...
labels_TeX(ivar(index_subset)), ...
[oo_.variance_decomposition_ME sum(oo_.variance_decomposition_ME, 2)], lh, 8, 2);
end
end
@ -218,7 +216,7 @@ end
warning(warning_old_state);
end
function y=get_filtered_time_series(y,m,options_)
function y = get_filtered_time_series(y, m, options_)
if options_.hp_filter && ~options_.one_sided_hp_filter && ~options_.bandpass.indicator
[hptrend,y] = sample_hp_filter(y,options_.hp_filter);

7
matlab/disp_steady_state.m
View File

@ -12,7 +12,7 @@ function disp_steady_state(M,oo)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2001-2017 Dynare Team
% Copyright (C) 2001-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -34,6 +34,7 @@ disp('STEADY-STATE RESULTS:')
skipline()
endo_names = M.endo_names;
steady_state = oo.steady_state;
for i=1:M.orig_endo_nbr
disp(sprintf('%s \t\t %g',endo_names(i,:),steady_state(i)));
for i = 1:M.orig_endo_nbr
disp(sprintf('%s \t\t %g', endo_names{i}, steady_state(i)));
end

148
matlab/disp_th_moments.m
View File

@ -1,7 +1,8 @@
function oo_=disp_th_moments(dr,var_list,M_,options_,oo_)
function oo_ = disp_th_moments(dr, var_list, M_, options_, oo_)
% Display theoretical moments of variables
% Copyright (C) 2001-2017 Dynare Team
% Copyright (C) 2001-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -22,21 +23,21 @@ nodecomposition = options_.nodecomposition;
if options_.one_sided_hp_filter
error(['disp_th_moments:: theoretical moments incompatible with one-sided HP filter. Use simulated moments instead'])
end
if size(var_list,1) == 0
var_list = M_.endo_names(1:M_.orig_endo_nbr, :);
if isempty(var_list)
var_list = M_.endo_names(1:M_.orig_endo_nbr);
end
nvar = size(var_list,1);
nvar = length(var_list);
ivar=zeros(nvar,1);
for i=1:nvar
i_tmp = strmatch(var_list(i,:),M_.endo_names,'exact');
i_tmp = strmatch(var_list{i}, M_.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
[oo_.gamma_y,stationary_vars] = th_autocovariances(dr,ivar,M_,options_, nodecomposition);
[oo_.gamma_y,stationary_vars] = th_autocovariances(dr, ivar, M_, options_, nodecomposition);
m = dr.ys(ivar);
non_stationary_vars = setdiff(1:length(ivar),stationary_vars);
m(non_stationary_vars) = NaN;
@ -71,75 +72,73 @@ if size(stationary_vars, 1) > 0
end
if ~options_.noprint %options_.nomoments == 0
if options_.order == 2
title='APPROXIMATED THEORETICAL MOMENTS';
title = 'APPROXIMATED THEORETICAL MOMENTS';
else
title='THEORETICAL MOMENTS';
title = 'THEORETICAL MOMENTS';
end
title=add_filter_subtitle(title,options_);
headers=char('VARIABLE','MEAN','STD. DEV.','VARIANCE');
labels = deblank(M_.endo_names(ivar,:));
lh = size(labels,2)+2;
dyntable(options_,title,headers,labels,z,lh,11,4);
title = add_filter_subtitle(title, options_);
headers = {'VARIABLE';'MEAN';'STD. DEV.';'VARIANCE'};
labels = M_.endo_names(ivar);
lh = cellofchararraymaxlength(labels)+2;
dyntable(options_, title, headers, labels, z, lh, 11, 4);
if options_.TeX
labels = deblank(M_.endo_names_tex(ivar,:));
lh = size(labels,2)+2;
dyn_latex_table(M_,options_,title,'th_moments',headers,labels,z,lh,11,4);
labels = M_.endo_names_tex(ivar);
lh = cellofchararraymaxlength(labels)+2;
dyn_latex_table(M_, options_, title, 'th_moments', headers, labels, z, lh, 11, 4);
end
if M_.exo_nbr > 1 && ~nodecomposition
skipline()
if options_.order == 2
title='APPROXIMATED VARIANCE DECOMPOSITION (in percent)';
title = 'APPROXIMATED VARIANCE DECOMPOSITION (in percent)';
else
title='VARIANCE DECOMPOSITION (in percent)';
title = 'VARIANCE DECOMPOSITION (in percent)';
end
title=add_filter_subtitle(title,options_);
title = add_filter_subtitle(title, options_);
headers = M_.exo_names;
headers(M_.exo_names_orig_ord,:) = headers;
headers = char(' ',headers);
lh = size(deblank(M_.endo_names(ivar(stationary_vars),:)),2)+2;
dyntable(options_,title,headers,deblank(M_.endo_names(ivar(stationary_vars), ...
:)),100* ...
oo_.gamma_y{options_.ar+2}(stationary_vars,:),lh,8,2);
headers(M_.exo_names_orig_ord) = headers;
headers = vertcat(' ', headers);
lh = cellofchararraymaxlength(M_.endo_names(ivar(stationary_vars)))+2;
dyntable(options_, title, headers, M_.endo_names(ivar(stationary_vars)), 100*oo_.gamma_y{options_.ar+2}(stationary_vars,:), lh, 8, 2);
if ME_present
[stationary_observables,pos_index_subset]=intersect(index_subset,stationary_vars,'stable');
headers_ME=char(headers,'ME');
dyntable(options_,[title,' WITH MEASUREMENT ERROR'],headers_ME,deblank(M_.endo_names(ivar(stationary_observables), ...
:)),oo_.variance_decomposition_ME(pos_index_subset,:),lh,8,2);
[stationary_observables, pos_index_subset] = intersect(index_subset, stationary_vars, 'stable');
headers_ME = vertcat(headers, 'ME');
dyntable(options_, [title,' WITH MEASUREMENT ERROR'], headers_ME, M_.endo_names(ivar(stationary_observables)), ...
oo_.variance_decomposition_ME(pos_index_subset,:), lh, 8, 2);
end
if options_.TeX
headers=M_.exo_names_tex;
headers = char(' ',headers);
labels = deblank(M_.endo_names_tex(ivar(stationary_vars),:));
lh = size(labels,2)+2;
dyn_latex_table(M_,options_,title,'th_var_decomp_uncond',headers,labels,100*oo_.gamma_y{options_.ar+2}(stationary_vars,:),lh,8,2);
headers = M_.exo_names_tex;
headers = vertcat(' ', headers);
labels = M_.endo_names_tex(ivar(stationary_vars));
lh = cellofchararraymaxlength(labels)+2;
dyn_latex_table(M_, options_, title, 'th_var_decomp_uncond', headers, labels, 100*oo_.gamma_y{options_.ar+2}(stationary_vars,:), lh, 8, 2);
if ME_present
headers_ME=char(headers,'ME');
dyn_latex_table(M_,options_,[title,' WITH MEASUREMENT ERROR'],'th_var_decomp_uncond_ME',headers_ME,labels,oo_.variance_decomposition_ME(pos_index_subset,:),lh,8,2);
headers_ME = vertcat(headers, 'ME');
dyn_latex_table(M_, options_, [title,' WITH MEASUREMENT ERROR'], ...
'th_var_decomp_uncond_ME', headers_ME, labels, oo_.variance_decomposition_ME(pos_index_subset,:), lh, 8, 2);
end
end
end
end
conditional_variance_steps = options_.conditional_variance_decomposition;
if length(conditional_variance_steps)
StateSpaceModel.number_of_state_equations = M_.endo_nbr;
StateSpaceModel.number_of_state_innovations = M_.exo_nbr;
StateSpaceModel.sigma_e_is_diagonal = M_.sigma_e_is_diagonal;
[StateSpaceModel.transition_matrix,StateSpaceModel.impulse_matrix] = kalman_transition_matrix(dr,(1:M_.endo_nbr)',M_.nstatic+(1:M_.nspred)',M_.exo_nbr);
[StateSpaceModel.transition_matrix, StateSpaceModel.impulse_matrix] = ...
kalman_transition_matrix(dr,(1:M_.endo_nbr)',M_.nstatic+(1:M_.nspred)',M_.exo_nbr);
StateSpaceModel.state_innovations_covariance_matrix = M_.Sigma_e;
StateSpaceModel.order_var = dr.order_var;
StateSpaceModel.measurement_error=M_.H;
StateSpaceModel.observable_pos=options_.varobs_id;
[oo_.conditional_variance_decomposition, oo_.conditional_variance_decomposition_ME]= conditional_variance_decomposition(StateSpaceModel,conditional_variance_steps,ivar);
StateSpaceModel.measurement_error = M_.H;
StateSpaceModel.observable_pos = options_.varobs_id;
[oo_.conditional_variance_decomposition, oo_.conditional_variance_decomposition_ME] = ...
conditional_variance_decomposition(StateSpaceModel, conditional_variance_steps, ivar);
if options_.noprint == 0
display_conditional_variance_decomposition(oo_.conditional_variance_decomposition,conditional_variance_steps,...
ivar,M_,options_);
display_conditional_variance_decomposition(oo_.conditional_variance_decomposition, conditional_variance_steps, ivar, M_, options_);
if ME_present
display_conditional_variance_decomposition(oo_.conditional_variance_decomposition_ME,conditional_variance_steps,...
observable_pos_requested_vars,M_,options_);
end
display_conditional_variance_decomposition(oo_.conditional_variance_decomposition_ME, conditional_variance_steps, ...
observable_pos_requested_vars, M_, options_);
end
end
end
end
@ -151,32 +150,33 @@ if length(i1) == 0
return
end
if options_.nocorr == 0 && size(stationary_vars, 1) > 0
corr=NaN(size(oo_.gamma_y{1}));
if options_.nocorr == 0 && size(stationary_vars, 1)>0
corr = NaN(size(oo_.gamma_y{1}));
corr(i1,i1) = oo_.gamma_y{1}(i1,i1)./(sd(i1)*sd(i1)');
if options_.contemporaneous_correlation
oo_.contemporaneous_correlation = corr;
end
if ~options_.noprint
skipline()
if options_.order == 2
title='APPROXIMATED MATRIX OF CORRELATIONS';
if options_.order==2
title = 'APPROXIMATED MATRIX OF CORRELATIONS';
else
title='MATRIX OF CORRELATIONS';
title = 'MATRIX OF CORRELATIONS';
end
title=add_filter_subtitle(title,options_);
labels = deblank(M_.endo_names(ivar(i1),:));
headers = char('Variables',labels);
lh = size(labels,2)+2;
dyntable(options_,title,headers,labels,corr(i1,i1),lh,8,4);
title = add_filter_subtitle(title, options_);
labels = M_.endo_names(ivar(i1));
headers = vertcat('Variables', labels);
lh = cellofchararraymaxlength(labels)+2;
dyntable(options_, title, headers, labels, corr(i1,i1), lh, 8, 4);
if options_.TeX
labels = deblank(M_.endo_names_tex(ivar(i1),:));
headers=char('Variables',labels);
lh = size(labels,2)+2;
dyn_latex_table(M_,options_,title,'th_corr_matrix',headers,labels,corr(i1,i1),lh,8,4);
labels = M_.endo_names_tex(ivar(i1));
headers = vertcat('Variables', labels);
lh = cellofchararraymaxlength(labels)+2;
dyn_latex_table(M_, options_, title, 'th_corr_matrix', headers, labels, corr(i1,i1), lh, 8, 4);
end
end
end
if options_.ar > 0 && size(stationary_vars, 1) > 0
z=[];
for i=1:options_.ar
@ -186,20 +186,20 @@ if options_.ar > 0 && size(stationary_vars, 1) > 0
if ~options_.noprint
skipline()
if options_.order == 2
title='APPROXIMATED COEFFICIENTS OF AUTOCORRELATION';
title = 'APPROXIMATED COEFFICIENTS OF AUTOCORRELATION';
else
title='COEFFICIENTS OF AUTOCORRELATION';
title = 'COEFFICIENTS OF AUTOCORRELATION';
end
title=add_filter_subtitle(title,options_);
labels = deblank(M_.endo_names(ivar(i1),:));
headers = char('Order ',int2str([1:options_.ar]'));
lh = size(labels,2)+2;
dyntable(options_,title,headers,labels,z,lh,8,4);
title = add_filter_subtitle(title, options_);
labels = M_.endo_names(ivar(i1));
headers = vertcat('Order ', cellstr(int2str([1:options_.ar]')));
lh = cellofchararraymaxlength(labels)+2;
dyntable(options_, title, headers, labels, z, lh, 8, 4);
if options_.TeX
labels = deblank(M_.endo_names_tex(ivar(i1),:));
headers=char('Order ',int2str([1:options_.ar]'));
lh = size(labels,2)+2;
dyn_latex_table(M_,options_,title,'th_autocorr_matrix',headers,labels,z,lh,8,4);
labels = M_.endo_names_tex(ivar(i1));
headers = vertcat('Order ', cellstr(int2str([1:options_.ar]')));
lh = cellofchararraymaxlength(labels)+2;
dyn_latex_table(M_, options_, title, 'th_autocorr_matrix', headers, labels, z, lh, 8, 4);
end
end
end

32
matlab/display_conditional_variance_decomposition.m
View File

@ -13,7 +13,7 @@ function display_conditional_variance_decomposition(conditional_decomposition_ar
% OUTPUTS
% none
%
% Copyright (C) 2010-2017 Dynare Team
% Copyright (C) 2010-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -33,18 +33,19 @@ function display_conditional_variance_decomposition(conditional_decomposition_ar
if size(conditional_decomposition_array,3)==M_.exo_nbr %no ME input
shock_number=M_.exo_nbr;
headers = M_.exo_names;
headers(M_.exo_names_orig_ord,:) = headers;
headers(M_.exo_names_orig_ord) = headers;
if options_.TeX
headers_TeX=char('',deblank(M_.exo_names_tex));
headers_TeX = vertcat(' ', M_.exo_names_tex);
end
title_addon='';
elseif size(conditional_decomposition_array,3)==M_.exo_nbr+1 %ME input
shock_number=M_.exo_nbr+1;
headers = M_.exo_names;
headers(M_.exo_names_orig_ord,:) = headers;
headers=char(headers,'ME');
headers(M_.exo_names_orig_ord) = headers;
headers = vertcat(headers, 'ME');
if options_.TeX
headers_TeX=char('',deblank(strvcat(M_.exo_names_tex,'ME')));
headers_TeX = vertcat(M_.exo_names_tex, 'ME');
headers_TeX = vertcat(' ', headers_TeX);
end
title_addon=' - WITH MEASUREMENT ERROR';
else
@ -61,25 +62,22 @@ else
disp(title)
end
headers = char(' ',headers);
lh = size(deblank(M_.endo_names(SubsetOfVariables,:)),2)+2;
headers = vertcat(' ', headers);
lh = cellofchararraymaxlength(M_.endo_names(SubsetOfVariables))+2;
if options_.TeX
labels_TeX = deblank(M_.endo_names_tex(SubsetOfVariables,:));
lh = size(labels_TeX,2)+2;
labels_TeX = M_.endo_names_tex(SubsetOfVariables);
lh = cellofchararraymaxlength(labels_TeX)+2;
end
vardec_i = zeros(length(SubsetOfVariables),shock_number);
vardec_i = zeros(length(SubsetOfVariables), shock_number);
for i=1:length(Steps)
disp(['Period ' int2str(Steps(i)) ':'])
for j=1:shock_number
vardec_i(:,j) = 100*conditional_decomposition_array(:, ...
i,j);
vardec_i(:,j) = 100*conditional_decomposition_array(:,i,j);
end
dyntable(options_,'',headers,...
deblank(M_.endo_names(SubsetOfVariables,:)),...
vardec_i,lh,8,2);
dyntable(options_, '', headers, M_.endo_names(SubsetOfVariables), vardec_i, lh, 8, 2);
if options_.TeX
dyn_latex_table(M_,options_,[title,'; Period ' int2str(Steps(i))],['th_var_decomp_cond_h',int2str(Steps(i))],headers_TeX,labels_TeX,vardec_i,lh,8,2);
dyn_latex_table(M_, options_, [title, '; Period ' int2str(Steps(i))], ['th_var_decomp_cond_h', int2str(Steps(i))], headers_TeX, labels_TeX, vardec_i, lh, 8, 2);
end
end

144
matlab/display_estimation_results_table.m
View File

@ -10,7 +10,7 @@ function oo_=display_estimation_results_table(xparam1,stdh,M_,options_,estim_par
% o options_ Matlab's structure describing the options (initialized by dynare, see @ref{options_}).
% o bayestopt_ Matlab's structure describing the priors (initialized by dynare, see @ref{bayesopt_}).
% o oo_ Matlab's structure gathering the results (initialized by dynare, see @ref{oo_}).
% o pnames [string] Character Array storing the names for prior distributions
% o pnames [string] Cell of strings storing the names for prior distributions
% o table_title [string] Title of the Table
% o field_name [string] String storing the name of the fields for oo_ where the parameters are stored
%
@ -20,7 +20,7 @@ function oo_=display_estimation_results_table(xparam1,stdh,M_,options_,estim_par
% SPECIAL REQUIREMENTS
% None.
% Copyright (C) 2014-2017 Dynare Team
% Copyright (C) 2014-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -49,12 +49,12 @@ disp(['RESULTS FROM ' upper(table_title) ' ESTIMATION'])
LaTeXtitle=strrep(table_title,' ','_');
tstath = abs(xparam1)./stdh;
header_width = row_header_width(M_,estim_params_,bayestopt_);
header_width = row_header_width(M_, estim_params_, bayestopt_);
if strcmp(field_name,'posterior')
tit1 = sprintf('%-*s %7s %8s %7s %4s %6s\n',header_width-2,' ','prior mean', ...
'mode','s.d.','prior','pstdev');
tit1 = sprintf('%-*s %7s %8s %7s %4s %6s\n', header_width-2, ' ', 'prior mean', ...
'mode', 's.d.', 'prior', 'pstdev');
else
tit1 = sprintf('%-*s %10s %7s %6s\n',header_width-2,' ','Estimate','s.d.','t-stat');
tit1 = sprintf('%-*s %10s %7s %6s\n', header_width-2, ' ', 'Estimate', 's.d.', 't-stat');
end
if np
ip = nvx+nvn+ncx+ncn+1;
@ -66,11 +66,11 @@ if np
fprintf('%-*s %7.3f %8.4f %7.4f %4s %6.4f \n', ...
header_width,name, ...
bayestopt_.p1(ip),xparam1(ip),stdh(ip), ...
pnames(bayestopt_.pshape(ip)+1,:), ...
pnames{bayestopt_.pshape(ip)+1}, ...
bayestopt_.p2(ip));
else
fprintf('%-*s %8.4f %7.4f %7.4f \n', ...
header_width,name,xparam1(ip),stdh(ip),tstath(ip));
header_width, name, xparam1(ip), stdh(ip), tstath(ip));
end
eval(['oo_.' field_name '_mode.parameters.' name ' = xparam1(ip);']);
eval(['oo_.' field_name '_std_at_mode.parameters.' name ' = stdh(ip);']);
@ -84,14 +84,14 @@ if nvx
disp(tit1)
for i=1:nvx
k = estim_params_.var_exo(i,1);
name = deblank(M_.exo_names(k,:));
name = M_.exo_names{k};
if strcmp(field_name,'posterior')
fprintf('%-*s %7.3f %8.4f %7.4f %4s %6.4f \n', ...
header_width,name,bayestopt_.p1(ip),xparam1(ip), ...
stdh(ip),pnames(bayestopt_.pshape(ip)+1,:), ...
header_width, name, bayestopt_.p1(ip), xparam1(ip), ...
stdh(ip), pnames{bayestopt_.pshape(ip)+1}, ...
bayestopt_.p2(ip));
else
fprintf('%-*s %8.4f %7.4f %7.4f \n',header_width,name,xparam1(ip),stdh(ip),tstath(ip));
fprintf('%-*s %8.4f %7.4f %7.4f \n', header_width, name, xparam1(ip), stdh(ip), tstath(ip));
end
M_.Sigma_e(k,k) = xparam1(ip)*xparam1(ip);
eval(['oo_.' field_name '_mode.shocks_std.' name ' = xparam1(ip);']);
@ -108,12 +108,13 @@ if nvn
name = options_.varobs{estim_params_.nvn_observable_correspondence(i,1)};
if strcmp(field_name,'posterior')
fprintf('%-*s %7.3f %8.4f %7.4f %4s %6.4f \n', ...
header_width,name,bayestopt_.p1(ip), ...
xparam1(ip),stdh(ip), ...
pnames(bayestopt_.pshape(ip)+1,:), ...
header_width, name, bayestopt_.p1(ip), ...
xparam1(ip), stdh(ip), ...
pnames{bayestopt_.pshape(ip)+1}, ...
bayestopt_.p2(ip));
else
fprintf('%-*s %8.4f %7.4f %7.4f \n',header_width,name,xparam1(ip),stdh(ip),tstath(ip))
fprintf('%-*s %8.4f %7.4f %7.4f \n', header_width, name, xparam1(ip), ...
stdh(ip), tstath(ip))
end
eval(['oo_.' field_name '_mode.measurement_errors_std.' name ' = xparam1(ip);']);
eval(['oo_.' field_name '_std_at_mode.measurement_errors_std.' name ' = stdh(ip);']);
@ -129,14 +130,15 @@ if ncx
for i=1:ncx
k1 = estim_params_.corrx(i,1);
k2 = estim_params_.corrx(i,2);
name = [deblank(M_.exo_names(k1,:)) ',' deblank(M_.exo_names(k2,:))];
NAME = [deblank(M_.exo_names(k1,:)) '_' deblank(M_.exo_names(k2,:))];
if strcmp(field_name,'posterior')
name = sprintf('%s,%s', M_.exo_names{k1}, M_.exo_names{k2});
NAME = sprintf('%s_%s', M_.exo_names{k1}, M_.exo_names{k2});
if strcmp(field_name, 'posterior')
fprintf('%-*s %7.3f %8.4f %7.4f %4s %6.4f \n', ...
header_width,name,bayestopt_.p1(ip),xparam1(ip),stdh(ip), ...
pnames(bayestopt_.pshape(ip)+1,:), bayestopt_.p2(ip));
header_width, name, bayestopt_.p1(ip), xparam1(ip), stdh(ip), ...
pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p2(ip));
else
fprintf('%-*s %8.4f %7.4f %7.4f \n', header_width,name,xparam1(ip),stdh(ip),tstath(ip));
fprintf('%-*s %8.4f %7.4f %7.4f \n', header_width,name, xparam1(ip), ...
stdh(ip), tstath(ip));
end
M_.Sigma_e(k1,k2) = xparam1(ip)*sqrt(M_.Sigma_e(k1,k1)*M_.Sigma_e(k2,k2));
M_.Sigma_e(k2,k1) = M_.Sigma_e(k1,k2);
@ -154,14 +156,15 @@ if ncn
for i=1:ncn
k1 = estim_params_.corrn(i,1);
k2 = estim_params_.corrn(i,2);
name = [deblank(M_.endo_names(k1,:)) ',' deblank(M_.endo_names(k2,:))];
NAME = [deblank(M_.endo_names(k1,:)) '_' deblank(M_.endo_names(k2,:))];
name = sprintf('%s,%s', M_.endo_names{k1}, M_.endo_names{k2});
NAME = sprintf('%s_%s', M_.endo_names{k1}, M_.endo_names{k2});
if strcmp(field_name,'posterior')
fprintf('%-*s %7.3f %8.4f %7.4f %4s %6.4f \n', ...
header_width,name,bayestopt_.p1(ip),xparam1(ip),stdh(ip), ...
pnames(bayestopt_.pshape(ip)+1,:), bayestopt_.p2(ip));
header_width, name, bayestopt_.p1(ip), xparam1(ip), stdh(ip), ...
pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p2(ip));
else
fprintf('%-*s %8.4f %7.4f %7.4f \n',header_width,name,xparam1(ip),stdh(ip),tstath(ip));
fprintf('%-*s %8.4f %7.4f %7.4f \n',header_width, name, xparam1(ip), ...
stdh(ip), tstath(ip));
end
eval(['oo_.' field_name '_mode.measurement_errors_corr.' NAME ' = xparam1(ip);']);
eval(['oo_.' field_name '_std_at_mode.measurement_errors_corr.' NAME ' = stdh(ip);']);
@ -169,6 +172,7 @@ if ncn
end
skipline()
end
if any(xparam1(1:nvx+nvn)<0)
warning('Some estimated standard deviations are negative. Dynare internally works with variances so that the sign does not matter. Nevertheless, it is recommended to impose either prior restrictions (Bayesian Estimation) or a lower bound (ML) to assure positive values.')
end
@ -183,11 +187,11 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
ip = nvx+nvn+ncx+ncn+1;
for i=1:np
fprintf(fidTeX,'$%s$ & %s & %7.3f & %6.4f & %8.4f & %7.4f \\\\ \n',...
M_.param_names_tex(estim_params_.param_vals(i,1),:),...
deblank(pnames(bayestopt_.pshape(ip)+1,:)),...
bayestopt_.p1(ip),...
bayestopt_.p2(ip),...
xparam1(ip),...
M_.param_names_tex{estim_params_.param_vals(i,1)}, ...
pnames{bayestopt_.pshape(ip)+1}, ...
bayestopt_.p1(ip), ...
bayestopt_.p2(ip), ...
xparam1(ip), ...
stdh(ip));
ip = ip + 1;
end
@ -201,8 +205,8 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
for i=1:nvx
k = estim_params_.var_exo(i,1);
fprintf(fidTeX,[ '$%s$ & %4s & %7.3f & %6.4f & %8.4f & %7.4f \\\\ \n'],...
deblank(M_.exo_names_tex(k,:)),...
deblank(pnames(bayestopt_.pshape(ip)+1,:)),...
M_.exo_names_tex{k},...
pnames{bayestopt_.pshape(ip)+1},...
bayestopt_.p1(ip),...
bayestopt_.p2(ip),...
xparam1(ip), ...
@ -217,10 +221,10 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
TeXBegin_Bayesian(fidTeX,3,'standard deviation of measurement errors')
ip = nvx+1;
for i=1:nvn
idx = strmatch(options_.varobs{estim_params_.nvn_observable_correspondence(i,1)},M_.endo_names);
idx = strmatch(options_.varobs{estim_params_.nvn_observable_correspondence(i,1)}, M_.endo_names);
fprintf(fidTeX,'$%s$ & %4s & %7.3f & %6.4f & %8.4f & %7.4f \\\\ \n',...
deblank(M_.endo_names_tex(idx,:)), ...
deblank(pnames(bayestopt_.pshape(ip)+1,:)), ...
M_.endo_names_tex{idx}, ...
pnames{bayestopt_.pshape(ip)+1}, ...
bayestopt_.p1(ip), ...
bayestopt_.p2(ip),...
xparam1(ip),...
@ -238,8 +242,8 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
k1 = estim_params_.corrx(i,1);
k2 = estim_params_.corrx(i,2);
fprintf(fidTeX,[ '$%s$ & %s & %7.3f & %6.4f & %8.4f & %7.4f \\\\ \n'],...
[deblank(M_.exo_names_tex(k1,:)) ',' deblank(M_.exo_names_tex(k2,:))], ...
deblank(pnames(bayestopt_.pshape(ip)+1,:)), ...
[M_.exo_names_tex{k1} ',' M_.exo_names_tex{k2}], ...
pnames{bayestopt_.pshape(ip)+1}, ...
bayestopt_.p1(ip), ...
bayestopt_.p2(ip), ...
xparam1(ip), ...
@ -257,8 +261,8 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
k1 = estim_params_.corrn(i,1);
k2 = estim_params_.corrn(i,2);
fprintf(fidTeX,'$%s$ & %s & %7.3f & %6.4f & %8.4f & %7.4f \\\\ \n',...
[deblank(M_.endo_names_tex(k1,:)) ',' deblank(M_.endo_names_tex(k2,:))], ...
pnames(bayestopt_.pshape(ip)+1,:), ...
[ M_.endo_names_tex{k1} ',' M_.endo_names_tex{k2}], ...
pnames{bayestopt_.pshape(ip)+1}, ...
bayestopt_.p1(ip), ...
bayestopt_.p2(ip), ...
xparam1(ip), ...
@ -270,14 +274,14 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
elseif all(bayestopt_.pshape == 0) && options_.TeX %% MLE and GMM Latex output
if np
filename = [OutputDirectoryName '/' M_.fname '_' LaTeXtitle '_Mode_1.tex'];
fidTeX = fopen(filename,'w');
TeXBegin_ML(fidTeX,1,'parameters',table_title,LaTeXtitle)
fidTeX = fopen(filename, 'w');
TeXBegin_ML(fidTeX, 1, 'parameters', table_title, LaTeXtitle)
ip = nvx+nvn+ncx+ncn+1;
for i=1:np
fprintf(fidTeX,'$%s$ & %8.4f & %7.4f & %7.4f\\\\ \n',...
M_.param_names_tex(estim_params_.param_vals(i,1),:),...
xparam1(ip),...
stdh(ip),...
M_.param_names_tex{estim_params_.param_vals(i,1)}, ...
xparam1(ip), ...
stdh(ip), ...
tstath(ip));
ip = ip + 1;
end
@ -285,15 +289,15 @@ elseif all(bayestopt_.pshape == 0) && options_.TeX %% MLE and GMM Latex output
end
if nvx
filename = [OutputDirectoryName '/' M_.fname '_' LaTeXtitle '_Mode_2.tex'];
fidTeX = fopen(filename,'w');
TeXBegin_ML(fidTeX,2,'standard deviation of structural shocks',table_title,LaTeXtitle)
fidTeX = fopen(filename, 'w');
TeXBegin_ML(fidTeX, 2, 'standard deviation of structural shocks', table_title, LaTeXtitle)
ip = 1;
for i=1:nvx
k = estim_params_.var_exo(i,1);
fprintf(fidTeX,[ '$%s$ & %8.4f & %7.4f & %7.4f\\\\ \n'],...
deblank(M_.exo_names_tex(k,:)),...
fprintf(fidTeX,[ '$%s$ & %8.4f & %7.4f & %7.4f\\\\ \n'], ...
M_.exo_names_tex{k}, ...
xparam1(ip), ...
stdh(ip),...
stdh(ip), ...
tstath(ip));
ip = ip+1;
end
@ -301,15 +305,15 @@ elseif all(bayestopt_.pshape == 0) && options_.TeX %% MLE and GMM Latex output
end
if nvn
filename = [OutputDirectoryName '/' M_.fname '_' LaTeXtitle '_Mode_3.tex'];
fidTeX = fopen(filename,'w');
TeXBegin_ML(fidTeX,3,'standard deviation of measurement errors',table_title,LaTeXtitle)
fidTeX = fopen(filename, 'w');
TeXBegin_ML(fidTeX, 3, 'standard deviation of measurement errors', table_title, LaTeXtitle)
ip = nvx+1;
for i=1:nvn
idx = strmatch(options_.varobs{estim_params_.nvn_observable_correspondence(i,1)},M_.endo_names);
fprintf(fidTeX,'$%s$ & %8.4f & %7.4f & %7.4f \\\\ \n',...
deblank(M_.endo_names_tex(idx,:)), ...
xparam1(ip),...
stdh(ip),...
idx = strmatch(options_.varobs{estim_params_.nvn_observable_correspondence(i,1)}, M_.endo_names);
fprintf(fidTeX, '$%s$ & %8.4f & %7.4f & %7.4f \\\\ \n', ...
M_.endo_names_tex{idx}, ...
xparam1(ip), ...
stdh(ip), ...
tstath(ip));
ip = ip+1;
end
@ -317,16 +321,16 @@ elseif all(bayestopt_.pshape == 0) && options_.TeX %% MLE and GMM Latex output
end
if ncx
filename = [OutputDirectoryName '/' M_.fname '_' LaTeXtitle '_Mode_4.tex'];
fidTeX = fopen(filename,'w');
TeXBegin_ML(fidTeX,4,'correlation of structural shocks',table_title,LaTeXtitle)
fidTeX = fopen(filename, 'w');
TeXBegin_ML(fidTeX, 4, 'correlation of structural shocks', table_title,LaTeXtitle)
ip = nvx+nvn+1;
for i=1:ncx
k1 = estim_params_.corrx(i,1);
k2 = estim_params_.corrx(i,2);
fprintf(fidTeX,[ '$%s$ & %8.4f & %7.4f & %7.4f \\\\ \n'],...
[deblank(M_.exo_names_tex(k1,:)) ',' deblank(M_.exo_names_tex(k2,:))], ...
fprintf(fidTeX,[ '$%s$ & %8.4f & %7.4f & %7.4f \\\\ \n'], ...
[M_.exo_names_tex{k1} ',' M_.exo_names_tex{k2}], ...
xparam1(ip), ...
stdh(ip),...
stdh(ip), ...
tstath(ip));
ip = ip+1;
end
@ -334,16 +338,16 @@ elseif all(bayestopt_.pshape == 0) && options_.TeX %% MLE and GMM Latex output
end
if ncn
filename = [OutputDirectoryName '/' M_.fname '_' LaTeXtitle '_Mode_5.tex'];
fidTeX = fopen(filename,'w');
TeXBegin_ML(fidTeX,5,'correlation of measurement errors',table_title,LaTeXtitle)
fidTeX = fopen(filename, 'w');
TeXBegin_ML(fidTeX, 5, 'correlation of measurement errors', table_title, LaTeXtitle)
ip = nvx+nvn+ncx+1;
for i=1:ncn
k1 = estim_params_.corrn(i,1);
k2 = estim_params_.corrn(i,2);
fprintf(fidTeX,'$%s$ & %8.4f & %7.4f & %7.4f \\\\ \n',...
[deblank(M_.endo_names_tex(k1,:)) ',' deblank(M_.endo_names_tex(k2,:))], ...
fprintf(fidTeX, '$%s$ & %8.4f & %7.4f & %7.4f \\\\ \n', ...
[ M_.endo_names_tex{k1} ',' M_.endo_names_tex{k2}], ...
xparam1(ip), ...
stdh(ip),...
stdh(ip), ...
tstath(ip));
ip = ip+1;
end
@ -355,7 +359,7 @@ end
%% subfunctions:
%
function TeXBegin_Bayesian(fid,fnum,title)
function TeXBegin_Bayesian(fid, fnum, title)
fprintf(fid,'%% TeX-table generated by dynare_estimation (Dynare).\n');
fprintf(fid,['%% RESULTS FROM POSTERIOR MAXIMIZATION (' title ')\n']);
fprintf(fid,['%% ' datestr(now,0)]);
@ -379,7 +383,7 @@ fprintf(fid,'\\midrule \\endhead \n');
fprintf(fid,'\\bottomrule \\multicolumn{6}{r}{(Continued on next page)}\\endfoot \n');
fprintf(fid,'\\bottomrule\\endlastfoot \n');
function TeXBegin_ML(fid,fnum,title,table_title,LaTeXtitle)
function TeXBegin_ML(fid, fnum, title, table_title, LaTeXtitle)
fprintf(fid,'%% TeX-table generated by dynare_estimation (Dynare).\n');
fprintf(fid,['%% RESULTS FROM ' table_title ' MAXIMIZATION (' title ')\n']);
fprintf(fid,['%% ' datestr(now,0)]);

114
matlab/display_problematic_vars_Jacobian.m
View File

@ -16,7 +16,7 @@ function []=display_problematic_vars_Jacobian(problemrow,problemcol,M_,x,type,ca
% none.
%
% Copyright (C) 2014-2017 Dynare Team
% Copyright (C) 2014-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -55,84 +55,98 @@ if strcmp(type,'dynamic')
end
if problemcol(ii)<=max(max(M_.lead_lag_incidence)) && var_index<=M_.orig_endo_nbr
if problemrow(ii)<=aux_eq_nbr
eq_nbr=problemrow(ii);
fprintf('Derivative of Auxiliary Equation %d with respect to %s Variable %s (initial value of %s: %g) \n',eq_nbr,type_string,deblank(M_.endo_names(var_index,:)),deblank(M_.endo_names(var_index,:)),x(var_index))
eq_nbr = problemrow(ii);
fprintf('Derivative of Auxiliary Equation %d with respect to %s Variable %s (initial value of %s: %g) \n', ...
eq_nbr, type_string, M_.endo_names{var_index}, M_.endo_names{var_index}, x(var_index));
else
eq_nbr=problemrow(ii)-aux_eq_nbr;
fprintf('Derivative of Equation %d with respect to %s Variable %s (initial value of %s: %g) \n',eq_nbr,type_string,deblank(M_.endo_names(var_index,:)),deblank(M_.endo_names(var_index,:)),x(var_index))
eq_nbr = problemrow(ii)-aux_eq_nbr;
fprintf('Derivative of Equation %d with respect to %s Variable %s (initial value of %s: %g) \n', ...
eq_nbr, type_string, M_.endo_names{var_index}, M_.endo_names{var_index}, x(var_index));
end
elseif problemcol(ii)<=max(max(M_.lead_lag_incidence)) && var_index>M_.orig_endo_nbr %auxiliary vars
if M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).type ==6 %Ramsey Lagrange Multiplier
if problemrow(ii)<=aux_eq_nbr
eq_nbr=problemrow(ii);
fprintf('Derivative of Auxiliary Equation %d with respect to %s of Langrange multiplier of equation %s (initial value: %g) \n',eq_nbr,type_string,M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).eq_nbr,x(problemcol(ii)))
elseif problemcol(ii)<=max(max(M_.lead_lag_incidence)) && var_index>M_.orig_endo_nbr % auxiliary vars
if M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).type==6 %Ramsey Lagrange Multiplier
if problemrow(ii)<=aux_eq_nbr
eq_nbr = problemrow(ii);
fprintf('Derivative of Auxiliary Equation %d with respect to %s of Langrange multiplier of equation %s (initial value: %g) \n', ...
eq_nbr, type_string, M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).eq_nbr, x(problemcol(ii)));
else
eq_nbr = problemrow(ii)-aux_eq_nbr;
fprintf('Derivative of Equation %d with respect to %s of Langrange multiplier of equation %s (initial value: %g) \n', ...
eq_nbr, type_string, M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).eq_nbr, x(problemcol(ii)));
end
else
eq_nbr=problemrow(ii)-aux_eq_nbr;
fprintf('Derivative of Equation %d with respect to %s of Langrange multiplier of equation %s (initial value: %g) \n',eq_nbr,type_string,M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).eq_nbr,x(problemcol(ii)))
if problemrow(ii)<=aux_eq_nbr
eq_nbr = problemrow(ii);
orig_var_index = M_.aux_vars(1,var_index-M_.orig_endo_nbr).orig_index;
fprintf('Derivative of Auxiliary Equation %d with respect to %s Variable %s (initial value of %s: %g) \n', ...
eq_nbr, type_string, M_.endo_names{orig_var_index}, M_.endo_names{orig_var_index}, x(orig_var_index));
else
eq_nbr = problemrow(ii)-aux_eq_nbr;
orig_var_index = M_.aux_vars(1,var_index-M_.orig_endo_nbr).orig_index;
fprintf('Derivative of Equation %d with respect to %s Variable %s (initial value of %s: %g) \n', ...
eq_nbr, type_string, M_.endo_names{orig_var_index}, M_.endo_names{orig_var_index}, x(orig_var_index));
end
end
else
if problemrow(ii)<=aux_eq_nbr
eq_nbr=problemrow(ii);
orig_var_index=M_.aux_vars(1,var_index-M_.orig_endo_nbr).orig_index;
fprintf('Derivative of Auxiliary Equation %d with respect to %s Variable %s (initial value of %s: %g) \n',eq_nbr,type_string,deblank(M_.endo_names(orig_var_index,:)),deblank(M_.endo_names(orig_var_index,:)),x(orig_var_index))
else
eq_nbr=problemrow(ii)-aux_eq_nbr;
orig_var_index=M_.aux_vars(1,var_index-M_.orig_endo_nbr).orig_index;
fprintf('Derivative of Equation %d with respect to %s Variable %s (initial value of %s: %g) \n',eq_nbr,type_string,deblank(M_.endo_names(orig_var_index,:)),deblank(M_.endo_names(orig_var_index,:)),x(orig_var_index))
end
end
elseif problemcol(ii)>max(max(M_.lead_lag_incidence)) && var_index<=M_.exo_nbr
if problemrow(ii)<=aux_eq_nbr
eq_nbr=problemrow(ii);
fprintf('Derivative of Auxiliary Equation %d with respect to %s shock %s \n',eq_nbr,type_string,deblank(M_.exo_names(var_index,:)));
eq_nbr = problemrow(ii);
fprintf('Derivative of Auxiliary Equation %d with respect to %s shock %s \n', ...
eq_nbr, type_string, M_.exo_names{var_index});
else
eq_nbr=problemrow(ii)-aux_eq_nbr;
fprintf('Derivative of Equation %d with respect to %s shock %s \n',eq_nbr,type_string,deblank(M_.exo_names(var_index,:)));
eq_nbr = problemrow(ii)-aux_eq_nbr;
fprintf('Derivative of Equation %d with respect to %s shock %s \n', ...
eq_nbr, type_string, M_.exo_names{var_index});
end
else
error('display_problematic_vars_Jacobian:: The error should not happen. Please contact the developers')
end
end
fprintf('\n%s The problem most often occurs, because a variable with\n',caller_string)
fprintf('%s exponent smaller than 1 has been initialized to 0. Taking the derivative\n',caller_string)
fprintf('%s and evaluating it at the steady state then results in a division by 0.\n',caller_string)
fprintf('%s If you are using model-local variables (# operator), check their values as well.\n',caller_string)
elseif strcmp(type,'static')
fprintf('\n%s The problem most often occurs, because a variable with\n', caller_string)
fprintf('%s exponent smaller than 1 has been initialized to 0. Taking the derivative\n', caller_string)
fprintf('%s and evaluating it at the steady state then results in a division by 0.\n', caller_string)
fprintf('%s If you are using model-local variables (# operator), check their values as well.\n', caller_string)
elseif strcmp(type, 'static')
for ii=1:length(problemrow)
if problemcol(ii)<=M_.orig_endo_nbr
if problemrow(ii)<=aux_eq_nbr
eq_nbr=problemrow(ii);
fprintf('Derivative of Auxiliary Equation %d with respect to Variable %s (initial value of %s: %g) \n',eq_nbr,deblank(M_.endo_names(problemcol(ii),:)),deblank(M_.endo_names(problemcol(ii),:)),x(problemcol(ii)))
eq_nbr = problemrow(ii);
fprintf('Derivative of Auxiliary Equation %d with respect to Variable %s (initial value of %s: %g) \n', ...
eq_nbr, M_.endo_names{problemcol(ii)}, M_.endo_names{problemcol(ii)}, x(problemcol(ii)));
else
eq_nbr=problemrow(ii)-aux_eq_nbr;
fprintf('Derivative of Equation %d with respect to Variable %s (initial value of %s: %g) \n',eq_nbr,deblank(M_.endo_names(problemcol(ii),:)),deblank(M_.endo_names(problemcol(ii),:)),x(problemcol(ii)))
eq_nbr = problemrow(ii)-aux_eq_nbr;
fprintf('Derivative of Equation %d with respect to Variable %s (initial value of %s: %g) \n', ...
eq_nbr, M_.endo_names{problemcol(ii)}, M_.endo_names{problemcol(ii)}, x(problemcol(ii)));
end
else %auxiliary vars
if M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).type ==6 %Ramsey Lagrange Multiplier
if problemrow(ii)<=aux_eq_nbr
eq_nbr=problemrow(ii);
fprintf('Derivative of Auxiliary Equation %d with respect to Lagrange multiplier of equation %d (initial value: %g) \n',eq_nbr,M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).eq_nbr,x(problemcol(ii)))
eq_nbr = problemrow(ii);
fprintf('Derivative of Auxiliary Equation %d with respect to Lagrange multiplier of equation %d (initial value: %g) \n', ...
eq_nbr, M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).eq_nbr, x(problemcol(ii)));
else
eq_nbr=problemrow(ii)-aux_eq_nbr;
fprintf('Derivative of Equation %d with respect to Lagrange multiplier of equation %d (initial value: %g) \n',eq_nbr,M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).eq_nbr,x(problemcol(ii)))
eq_nbr = problemrow(ii)-aux_eq_nbr;
fprintf('Derivative of Equation %d with respect to Lagrange multiplier of equation %d (initial value: %g) \n', ...
eq_nbr, M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).eq_nbr, x(problemcol(ii)));
end
else
if problemrow(ii)<=aux_eq_nbr
eq_nbr=problemrow(ii);
orig_var_index=M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).orig_index;
fprintf('Derivative of Auxiliary Equation %d with respect to Variable %s (initial value of %s: %g) \n',eq_nbr,deblank(M_.endo_names(orig_var_index,:)),deblank(M_.endo_names(orig_var_index,:)),x(problemcol(ii)))
eq_nbr = problemrow(ii);
orig_var_index = M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).orig_index;
fprintf('Derivative of Auxiliary Equation %d with respect to Variable %s (initial value of %s: %g) \n', ...
eq_nbr, M_.endo_names{orig_var_index}, M_.endo_names{orig_var_index}, x(problemcol(ii)));
else
eq_nbr=problemrow(ii)-aux_eq_nbr;
orig_var_index=M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).orig_index;
fprintf('Derivative of Equation %d with respect to Variable %s (initial value of %s: %g) \n',eq_nbr,deblank(M_.endo_names(orig_var_index,:)),deblank(M_.endo_names(orig_var_index,:)),x(problemcol(ii)))
eq_nbr = problemrow(ii)-aux_eq_nbr;
orig_var_index = M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).orig_index;
fprintf('Derivative of Equation %d with respect to Variable %s (initial value of %s: %g) \n', ...
eq_nbr, M_.endo_names{orig_var_index}, M_.endo_names{orig_var_index}, x(problemcol(ii)));
end
end
end
end
fprintf('\n%s The problem most often occurs, because a variable with\n',caller_string)
fprintf('%s exponent smaller than 1 has been initialized to 0. Taking the derivative\n',caller_string)
fprintf('%s and evaluating it at the steady state then results in a division by 0.\n',caller_string)
fprintf('%s If you are using model-local variables (# operator), check their values as well.\n',caller_string)
fprintf('\n%s The problem most often occurs, because a variable with\n', caller_string)
fprintf('%s exponent smaller than 1 has been initialized to 0. Taking the derivative\n', caller_string)
fprintf('%s and evaluating it at the steady state then results in a division by 0.\n', caller_string)
fprintf('%s If you are using model-local variables (# operator), check their values as well.\n', caller_string)
else
error('Unknown Type')
end

4
matlab/dsge_var_likelihood.m
View File

@ -37,7 +37,7 @@ function [fval,info,exit_flag,grad,hess,SteadyState,trend_coeff,PHI_tilde,SIGMA_
% SPECIAL REQUIREMENTS
% None.
% Copyright (C) 2006-2017 Dynare Team
% Copyright (C) 2006-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -73,7 +73,7 @@ xparam1 = xparam1(:);
% Initialization of of the index for parameter dsge_prior_weight in Model.params.
if isempty(dsge_prior_weight_idx)
dsge_prior_weight_idx = strmatch('dsge_prior_weight',Model.param_names);
dsge_prior_weight_idx = strmatch('dsge_prior_weight', Model.param_names);
end
% Get the number of estimated (dsge) parameters.

8
matlab/dyn2vec.m
View File

@ -14,7 +14,7 @@ function [z,zss]=dyn2vec(s1,s2)
% none
%
% Copyright (C) 2001-2017 Dynare Team
% Copyright (C) 2001-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -46,15 +46,15 @@ if nargin == 0
error(t);
end
for i=1:size(oo_.endo_simul,1)
assignin('base',deblank(M_.endo_names(i,:)),oo_.endo_simul(i,k)');
assignin('base', M_.endo_names{i}, oo_.endo_simul(i,k)');
end
return
else
j = strmatch(s1,M_.endo_names,'exact');
j = strmatch(s1, M_.endo_names, 'exact');
if ~ isempty(j)
z = oo_.endo_simul(j,k)';
else
j = strmatch(s1,M_.exo_names,'exact');
j = strmatch(s1, M_.exo_names, 'exact');
if ~ isempty(j)
if options_.smpl == 0
z = oo_.exo_simul(:,j);

26
matlab/dyn_forecast.m
View File

@ -21,7 +21,7 @@ function [forecast,info] = dyn_forecast(var_list,M,options,oo,task,dataset_info)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2017 Dynare Team
% Copyright (C) 2003-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -52,13 +52,13 @@ maximum_lag = M.maximum_lag;
endo_names = M.endo_names;
if isempty(var_list)
var_list = endo_names(1:M.orig_endo_nbr, :);
var_list = endo_names(1:M.orig_endo_nbr);
end
i_var = [];
for i = 1:size(var_list)
tmp = strmatch(var_list(i,:),endo_names,'exact');
for i = 1:length(var_list)
tmp = strmatch(var_list{i}, endo_names, 'exact');
if isempty(tmp)
error([var_list(i,:) ' isn''t an endogenous variable'])
error([var_list{i} ' isn''t an endogenous variable'])
end
i_var = [i_var; tmp];
end
@ -90,7 +90,7 @@ switch task
y_smoothed = oo.SmoothedVariables;
y0 = zeros(M.endo_nbr,maximum_lag);
for i = 1:M.endo_nbr
v_name = deblank(M.endo_names(i,:));
v_name = M.endo_names{i};
y0(i,:) = y_smoothed.(v_name)(end-maximum_lag+1:end); %includes steady state or mean, but simult_ will subtract only steady state
% 2. Subtract mean/steady state and add steady state; takes care of prefiltering
if isfield(oo.Smoother,'Constant') && isfield(oo.Smoother.Constant,v_name)
@ -98,7 +98,7 @@ switch task
if options.loglinear
y0(i,:)=y0(i,:)+log_variable(i,oo.dr.ys,M);
else
y0(i,:)=y0(i,:)+oo.dr.ys(strmatch(v_name,deblank(M.endo_names),'exact'));
y0(i,:)=y0(i,:)+oo.dr.ys(strmatch(v_name, M.endo_names, 'exact'));
end
end
% 2. Subtract trend
@ -114,8 +114,8 @@ switch task
i_var_obs = [];
trend_coeffs = [];
for i=1:length(var_obs)
tmp = strmatch(var_obs{i},endo_names(i_var,:),'exact');
trend_var_index=strmatch(var_obs{i},M.endo_names,'exact');
tmp = strmatch(var_obs{i}, endo_names(i_var), 'exact');
trend_var_index = strmatch(var_obs{i}, M.endo_names, 'exact');
if ~isempty(tmp)
i_var_obs = [ i_var_obs; tmp];
trend_coeffs = [trend_coeffs; oo.Smoother.TrendCoeffs(trend_var_index)];
@ -175,21 +175,21 @@ else
end
for i=1:n_var
vname = deblank(var_list(i,:));
vname = var_list{i};
forecast.Mean.(vname) = yf(i,maximum_lag+(1:horizon))';
forecast.HPDinf.(vname)= yf(i,maximum_lag+(1:horizon))' - int_width(1:horizon,i);
forecast.HPDsup.(vname) = yf(i,maximum_lag+(1:horizon))' + int_width(1:horizon,i);
if ~isequal(M.H,0) && ismember(var_list(i,:),options.varobs)
if ~isequal(M.H,0) && ismember(var_list{i},options.varobs)
forecast.HPDinf_ME.(vname)= yf(i,maximum_lag+(1:horizon))' - int_width_ME(1:horizon,i);
forecast.HPDsup_ME.(vname) = yf(i,maximum_lag+(1:horizon))' + int_width_ME(1:horizon,i);
end
end
for i=1:M.exo_det_nbr
forecast.Exogenous.(deblank(M.exo_det_names(i,:))) = oo.exo_det_simul(maximum_lag+(1:horizon),i);
forecast.Exogenous.(M.exo_det_names{i}) = oo.exo_det_simul(maximum_lag+(1:horizon),i);
end
if options.nograph == 0
oo.forecast = forecast;
forecast_graphs(var_list,M, oo,options)
forecast_graphs(var_list, M, oo, options)
end

102
matlab/dyn_latex_table.m
View File

@ -1,7 +1,8 @@
function dyn_latex_table(M_,options_,title,LaTeXtitle,headers,labels,values,label_width,val_width,val_precis,optional_header)
function dyn_latex_table(M_, options_, title, LaTeXtitle, headers, labels, values, label_width, val_width, val_precis, optional_header)
%function dyn_latex_table(M_,options_,title,LaTeXtitle,headers,labels,values,label_width,val_width,val_precis,optional_header)
% Copyright (C) 2015-2017 Dynare Team
% Copyright (C) 2015-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -24,16 +25,15 @@ end
OutputDirectoryName = CheckPath('Output',M_.dname);
%% get width of label column
if ~isempty(label_width)
label_width = max(size(deblank(char(headers(1,:),labels)),2)+2, ...
label_width);
else %use default length
label_width = max(size(deblank(char(headers(1,:),labels)),2))+2;
% Set width of label column
if isempty(label_width)
label_width = cellofchararraymaxlength(vertcat(headers{1}, labels))+2;
else
label_width = max(cellofchararraymaxlength(vertcat(headers{1}, labels))+2, label_width);
end
label_format_leftbound = sprintf('$%%-%ds$',label_width);
label_format_leftbound = sprintf('$%%-%ds$', label_width);
%% get width of label column
% Set width of other columns
if all(~isfinite(values))
values_length = 4;
else
@ -42,66 +42,64 @@ end
if any(values) < 0 %add one character for minus sign
values_length = values_length+1;
end
%% get width of header strings
headers_length = max(size(deblank(headers(2:end,:)),2));
if ~isempty(val_width)
val_width = max(max(headers_length,values_length)+4,val_width);
headers_length = cellofchararraymaxlength(headers(2:end));
if isempty(val_width)
val_width = max(headers_length, values_length)+4;
else
val_width = max(headers_length,values_length)+4;
val_width = max(max(headers_length, values_length)+4, val_width);
end
value_format = sprintf('%%%d.%df',val_width,val_precis);
header_string_format = sprintf('$%%%ds$',val_width);
value_format = sprintf('%%%d.%df', val_width, val_precis);
header_string_format = sprintf('$%%%ds$', val_width);
%Create and print header string
if length(headers) > 0
header_string = sprintf(label_format_leftbound ,strrep(deblank(headers(1,:)),'\','\\'));
header_code_string='l';
for i=2:size(headers,1)
header_string = [header_string '\t & \t ' sprintf(header_string_format,strrep(deblank(headers(i,:)),'\','\\'))];
header_code_string= [header_code_string 'c'];
% Create and print header string
if length(headers)>0
header_string = sprintf(label_format_leftbound, strrep(headers{1}, '\', '\\'));
header_code_string = 'l';
for i=2:length(headers)
header_string = [header_string '\t & \t ' sprintf(header_string_format, strrep(headers{i},'\','\\'))];
header_code_string = [header_code_string 'c'];
end
end
header_string=[header_string '\\\\\n'];
header_string = [header_string '\\\\\n'];
filename = [OutputDirectoryName '/' M_.fname '_' LaTeXtitle '.tex'];
fidTeX = fopen(filename,'w');
stack = dbstack;
fprintf(fidTeX,['%% ' datestr(now,0) ', created by ' stack(2).file]);
fprintf(fidTeX,' \n');
fprintf(fidTeX,' \n');
fprintf(fidTeX,'\\begin{center}\n');
fprintf(fidTeX,['\\begin{longtable}{%s} \n'],header_code_string);
fprintf(fidTeX,['\\caption{',title,'}\\\\\n ']);
fprintf(fidTeX, ['%% ' datestr(now,0) ', created by ' stack(2).file]);
fprintf(fidTeX, ' \n');
fprintf(fidTeX, ' \n');
fprintf(fidTeX, '\\begin{center}\n');
fprintf(fidTeX, ['\\begin{longtable}{%s} \n'], header_code_string);
fprintf(fidTeX, ['\\caption{',title,'}\\\\\n ']);
fprintf(fidTeX,['\\label{Table:',LaTeXtitle,'}\\\\\n']);
fprintf(fidTeX,'\\toprule \n');
fprintf(fidTeX, ['\\label{Table:',LaTeXtitle,'}\\\\\n']);
fprintf(fidTeX, '\\toprule \n');
if nargin==11
for ii=1:size(optional_header,1)
for ii = 1:length(optional_header)
fprintf(fidTeX,'%s\n',optional_header{ii});
end
end
fprintf(fidTeX,header_string);
fprintf(fidTeX,'\\midrule \\endfirsthead \n');
fprintf(fidTeX,'\\caption{(continued)}\\\\\n ');
fprintf(fidTeX,'\\toprule \\\\ \n');
fprintf(fidTeX, header_string);
fprintf(fidTeX, '\\midrule \\endfirsthead \n');
fprintf(fidTeX, '\\caption{(continued)}\\\\\n ');
fprintf(fidTeX, '\\toprule \\\\ \n');
if nargin==11
for ii=1:size(optional_header,1)
fprintf(fidTeX,'%s\n',optional_header{ii});
for ii = 1:length(optional_header)
fprintf(fidTeX, '%s\n', optional_header{ii});
end
end
fprintf(fidTeX,header_string);
fprintf(fidTeX,'\\midrule \\endhead \n');
fprintf(fidTeX,['\\midrule \\multicolumn{',num2str(size(headers,1)),'}{r}{(Continued on next page)} \\\\ \\bottomrule \\endfoot \n']);
fprintf(fidTeX,'\\bottomrule \\endlastfoot \n');
for i=1:size(values,1)
fprintf(fidTeX,label_format_leftbound,deblank(labels(i,:)));
fprintf(fidTeX,['\t & \t' value_format],values(i,:));
fprintf(fidTeX,' \\\\ \n');
fprintf(fidTeX, header_string);
fprintf(fidTeX, '\\midrule \\endhead \n');
fprintf(fidTeX, ['\\midrule \\multicolumn{',num2str(size(headers,1)),'}{r}{(Continued on next page)} \\\\ \\bottomrule \\endfoot \n']);
fprintf(fidTeX, '\\bottomrule \\endlastfoot \n');
for i = 1:size(values,1)
fprintf(fidTeX, label_format_leftbound, labels{i});
fprintf(fidTeX, ['\t & \t' value_format], values(i,:));
fprintf(fidTeX, ' \\\\ \n');
end
fprintf(fidTeX,'\\end{longtable}\n ');
fprintf(fidTeX,'\\end{center}\n');
fprintf(fidTeX,'%% End of TeX file.\n');
fprintf(fidTeX, '\\end{longtable}\n ');
fprintf(fidTeX, '\\end{center}\n');
fprintf(fidTeX, '%% End of TeX file.\n');
fclose(fidTeX);

8
matlab/dyn_ramsey_static.m
View File

@ -18,7 +18,7 @@ function [steady_state,params,check] = dyn_ramsey_static(ys_init,M,options_,oo)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2017 Dynare Team
% Copyright (C) 2003-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -50,8 +50,7 @@ elseif options_.steadystate_flag
k_inst = [];
inst_nbr = size(options_.instruments,1);
for i = 1:inst_nbr
k_inst = [k_inst; strmatch(options_.instruments(i,:), ...
M.endo_names,'exact')];
k_inst = [k_inst; strmatch(options_.instruments(i,:), M.endo_names, 'exact')];
end
if inst_nbr == 1
%solve for instrument, using univariate solver, starting at initial value for instrument
@ -113,8 +112,7 @@ if options_.steadystate_flag
k_inst = [];
instruments = options_.instruments;
for i = 1:size(instruments,1)
k_inst = [k_inst; strmatch(instruments(i,:), ...
endo_names,'exact')];
k_inst = [k_inst; strmatch(instruments(i,:), endo_names, 'exact')];
end
ys_init=zeros(size(oo.steady_state)); %create starting vector for steady state computation as only instrument value is handed over
ys_init(k_inst) = x; %set instrument, the only value required for steady state computation, to current value

12
matlab/dyn_risky_steadystate_solver.m
View File

@ -62,7 +62,7 @@ function [dr,info] = dyn_risky_steadystate_solver(ys0,M, ...
%! @end deftypefn
%@eod:
% Copyright (C) 2001-2017 Dynare Team
% Copyright (C) 2001-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -86,7 +86,7 @@ order_var = dr.order_var;
endo_nbr = M.endo_nbr;
exo_nbr = M.exo_nbr;
M.var_order_endo_names = M.endo_names(dr.order_var,:);
M.var_order_endo_names = M.endo_names(dr.order_var);
[junk,dr.i_fwrd_g,i_fwrd_f] = find(lead_lag_incidence(3,order_var));
dr.i_fwrd_f = i_fwrd_f;
@ -138,10 +138,10 @@ dr.ghs2 = zeros(M.endo_nbr,1);
for i=1:M.endo_nbr
if isfield(options,'portfolio') && options.portfolio == 1
disp(sprintf('%16s %12.6f %12.6f',M.endo_names(i,:),ys1(i), ...
disp(sprintf('%16s %12.6f %12.6f', M.endo_names{i}, ys1(i), ...
ys(i)))
else
disp(sprintf('%16s %12.6f %12.6f',M.endo_names(i,:),ys(i)))
disp(sprintf('%16s %12.6f %12.6f', M.endo_names{i}, ys(i)))
end
end
@ -500,11 +500,11 @@ M_np = M;
M_np.lead_lag_incidence = lead_lag_incidence_np;
M_np.lead_lag_incidence = lead_lag_incidence_np;
M_np.endo_nbr = length(v_np);
M_np.endo_names = M.endo_names(v_np,:);
M_np.endo_names = M.endo_names(v_np);
dr_np = struct();
dr_np = set_state_space(dr_np,M_np,options);
pm.dr_np = dr_np;
M_np.var_order_endo_names = M_np.endo_names(dr_np.order_var,:);
M_np.var_order_endo_names = M_np.endo_names(dr_np.order_var);
pm.M_np = M_np;
pm.i_fwrd_g = find(lead_lag_incidence_np(lead_index,dr_np.order_var)');

6
matlab/dynare_config.m
View File

@ -1,5 +1,5 @@
function dynareroot = dynare_config(path_to_dynare,verbose)
%function dynareroot = dynare_config(path_to_dynare)
function dynareroot = dynare_config(path_to_dynare, verbose)
% This function tests the existence of valid mex files (for qz
% decomposition, solution to sylvester equation and kronecker
% products...) and, if needed, add paths to the matlab versions
@ -15,7 +15,7 @@ function dynareroot = dynare_config(path_to_dynare,verbose)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2001-2017 Dynare Team
% Copyright (C) 2001-2018 Dynare Team
%
% This file is part of Dynare.
%

18
matlab/dynare_estimation.m
View File

@ -12,7 +12,7 @@ function oo_recursive_=dynare_estimation(var_list,dname)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2017 Dynare Team
% Copyright (C) 2003-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -117,16 +117,16 @@ if nnobs > 1 && horizon > 0
if isempty(var_list)
var_list = endo_names;
nvar = size(endo_names,1);
nvar = length(endo_names);
SelecVariables = transpose(1:nvar);
else
nvar = size(var_list,1);
nvar = length(var_list);
SelecVariables = [];
for i=1:nvar
if ~isempty(strmatch(var_list(i,:),endo_names,'exact'))
SelecVariables = [SelecVariables;strmatch(var_list(i,:),endo_names, 'exact')];
if ~isempty(strmatch(var_list{i}, endo_names, 'exact'))
SelecVariables = [SelecVariables; strmatch(var_list{i}, endo_names, 'exact')];
else
error(['Estimation:: ' var_list(i,:) ' isn''t an endogenous variable'])
error(['Estimation:: ' var_list{i} ' isn''t an endogenous variable'])
end
end
end
@ -148,7 +148,7 @@ if nnobs > 1 && horizon > 0
m = 1;
plot_index=0;
OutputDirectoryName = CheckPath('graphs',M_.fname);
for i = 1:size(var_list,1)
for i = 1:length(var_list)
if mod(i,nstar) == 1
plot_index=plot_index+1;
hfig = dyn_figure(options_.nodisplay,'Name',['Out of sample forecasts (',num2str(plot_index),')']);
@ -163,7 +163,7 @@ if nnobs > 1 && horizon > 0
else
offsetx = 0;
end
vname = deblank(var_list(i,:));
vname = var_list{i};
for j=1:nnobs
if mh_replic > 0
oo_.RecursiveForecast.Mean.(vname)(j,:) = ...
@ -207,7 +207,7 @@ if nnobs > 1 && horizon > 0
hold off
xlim([nobs(1)-offsetx nobs(end)+horizon])
m = m + 1;
if mod(i+1,nstar) == 1 || i ==size(var_list,1)
if mod(i+1,nstar) == 1 || i==length(var_list)
dyn_saveas(hfig,[M_.fname,filesep,'graphs',filesep M_.fname '_RecursiveForecasts_' int2str(plot_index)],options_.nodisplay,options_.graph_format);
end
end

33
matlab/dynare_estimation_1.m
View File

@ -12,7 +12,7 @@ function dynare_estimation_1(var_list_,dname)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2017 Dynare Team
% Copyright (C) 2003-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -141,8 +141,10 @@ missing_value = dataset_info.missing.state;
% Set number of observations
gend = dataset_.nobs;
% Set the number of observed variables.
n_varobs = length(options_.varobs);
% Get the number of parameters to be estimated.
nvx = estim_params_.nvx; % Variance of the structural innovations (number of parameters).
nvn = estim_params_.nvn; % Variance of the measurement innovations (number of parameters).
@ -150,8 +152,9 @@ ncx = estim_params_.ncx; % Covariance of the structural innovations (number of
ncn = estim_params_.ncn; % Covariance of the measurement innovations (number of parameters).
np = estim_params_.np ; % Number of deep parameters.
nx = nvx+nvn+ncx+ncn+np; % Total number of parameters to be estimated.
%% Set the names of the priors.
pnames = [' '; 'beta '; 'gamm '; 'norm '; 'invg '; 'unif '; 'invg2'; ' '; 'weibl'];
% Set the names of the priors.
pnames = {''; 'beta'; 'gamm'; 'norm'; 'invg'; 'unif'; 'invg2'; ''; 'weibl'};
dr = oo_.dr;
@ -358,7 +361,7 @@ end
if any(bayestopt_.pshape > 0) && ~options_.mh_posterior_mode_estimation
% display results table and store parameter estimates and standard errors in results
oo_=display_estimation_results_table(xparam1,stdh,M_,options_,estim_params_,bayestopt_,oo_,pnames,'Posterior','posterior');
oo_ = display_estimation_results_table(xparam1, stdh, M_, options_, estim_params_, bayestopt_, oo_, pnames, 'Posterior', 'posterior');
% Laplace approximation to the marginal log density:
if options_.cova_compute
estim_params_nbr = size(xparam1,1);
@ -376,7 +379,7 @@ if any(bayestopt_.pshape > 0) && ~options_.mh_posterior_mode_estimation
end
elseif ~any(bayestopt_.pshape > 0) && ~options_.mh_posterior_mode_estimation
oo_=display_estimation_results_table(xparam1,stdh,M_,options_,estim_params_,bayestopt_,oo_,pnames,'Maximum Likelihood','mle');
oo_=display_estimation_results_table(xparam1, stdh, M_, options_, estim_params_, bayestopt_, oo_, pnames, 'Maximum Likelihood', 'mle');
end
if np > 0
@ -563,7 +566,7 @@ if (~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.psha
hold on
plot(1:gend,innov(k,:),marker_string{2,1},'linewidth',1)
hold off
name = deblank(M_.exo_names(k,:));
name = M_.exo_names{k};
if isempty(NAMES)
NAMES = name;
else
@ -577,7 +580,7 @@ if (~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.psha
xlim([1 gend])
end
if options_.TeX
texname = M_.exo_names_tex(k,:);
texname = M_.exo_names_tex{k};
if isempty(TeXNAMES)
TeXNAMES = ['$ ' deblank(texname) ' $'];
else
@ -656,12 +659,12 @@ if (~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.psha
set(gca,'XTickLabel',options_.XTickLabel)
end
if options_.TeX
idx = strmatch(options_.varobs{index(k)},M_.endo_names,'exact');
texname = M_.endo_names_tex(idx,:);
idx = strmatch(options_.varobs{index(k)}, M_.endo_names, 'exact');
texname = M_.endo_names_tex{idx};
if isempty(TeXNAMES)
TeXNAMES = ['$ ' deblank(texname) ' $'];
TeXNAMES = ['$ ' texname ' $'];
else
TeXNAMES = char(TeXNAMES,['$ ' deblank(texname) ' $']);
TeXNAMES = char(TeXNAMES,['$ ' texname ' $']);
end
end
title(name,'Interpreter','none')
@ -731,12 +734,12 @@ if (~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.psha
xlim([1 gend])
end
if options_.TeX
idx = strmatch(options_.varobs{k},M_.endo_names,'exact');
texname = M_.endo_names_tex(idx,:);
idx = strmatch(options_.varobs{k}, M_.endo_names,'exact');
texname = M_.endo_names_tex{idx};
if isempty(TeXNAMES)
TeXNAMES = ['$ ' deblank(texname) ' $'];
TeXNAMES = ['$ ' texname ' $'];
else
TeXNAMES = char(TeXNAMES,['$ ' deblank(texname) ' $']);
TeXNAMES = char(TeXNAMES,['$ ' texname ' $']);
end
end
title(name,'Interpreter','none')

18
matlab/dynare_estimation_init.m
View File

@ -32,7 +32,7 @@ function [dataset_, dataset_info, xparam1, hh, M_, options_, oo_, estim_params_,
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2017 Dynare Team
% Copyright (C) 2003-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -56,7 +56,7 @@ if isempty(gsa_flag)
gsa_flag = false;
else
% Decide if a DSGE or DSGE-VAR has to be estimated.
if ~isempty(strmatch('dsge_prior_weight',M_.param_names))
if ~isempty(strmatch('dsge_prior_weight', M_.param_names))
options_.dsge_var = 1;
end
if isempty(var_list_)
@ -425,8 +425,8 @@ nspred = M_.nspred; % Number of predetermined variables in the state
var_obs_index_dr = [];
k1 = [];
for i=1:options_.number_of_observed_variables
var_obs_index_dr = [var_obs_index_dr; strmatch(options_.varobs{i},M_.endo_names(dr.order_var,:),'exact')];
k1 = [k1; strmatch(options_.varobs{i},M_.endo_names, 'exact')];
var_obs_index_dr = [var_obs_index_dr; strmatch(options_.varobs{i}, M_.endo_names(dr.order_var), 'exact')];
k1 = [k1; strmatch(options_.varobs{i}, M_.endo_names, 'exact')];
end
k3 = [];
@ -437,9 +437,9 @@ if options_.selected_variables_only
k3 = (1:M_.endo_nbr)';
k3p = (1:M_.endo_nbr)';
else
for i=1:size(var_list_,1)
k3 = [k3; strmatch(var_list_(i,:),M_.endo_names(dr.order_var,:), 'exact')];
k3p = [k3; strmatch(var_list_(i,:),M_.endo_names, 'exact')];
for i=1:length(var_list_)
k3 = [k3; strmatch(var_list_{i}, M_.endo_names(dr.order_var), 'exact')];
k3p = [k3; strmatch(var_list_{i}, M_.endo_names, 'exact')];
end
end
else
@ -513,11 +513,11 @@ if options_.analytic_derivation
skipline()
if any(isnan(params))
disp('After computing the steadystate, the following parameters are still NaN: '),
disp(M.param_names(isnan(params),:))
disp(char(M.param_names(isnan(params))))
end
if any(find(params(~isnan(params))-M.params(~isnan(params))))
disp('The steadystate file changed the values for the following parameters: '),
disp(M.param_names(find(params(~isnan(params))-M.params(~isnan(params))),:))
disp(char(M.param_names(find(params(~isnan(params))-M.params(~isnan(params))))))
end
disp('The derivatives of jacobian and steady-state will be computed numerically'),
disp('(re-set options_.analytic_derivation_mode= -2)'),

17
matlab/dynare_identification.m
View File

@ -17,9 +17,7 @@ function [pdraws, TAU, GAM, LRE, gp, H, JJ] = dynare_identification(options_iden
% SPECIAL REQUIREMENTS
% None
% main
%
% Copyright (C) 2010-2017 Dynare Team
% Copyright (C) 2010-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -147,8 +145,9 @@ options_ = set_default_option(options_,'datafile','');
options_.mode_compute = 0;
options_.plot_priors = 0;
options_.smoother=1;
[dataset_,dataset_info,xparam1,hh, M_, options_, oo_, estim_params_,bayestopt_,bounds]=dynare_estimation_init(M_.endo_names,fname_,1, M_, options_, oo_, estim_params_, bayestopt_);
options_ident = set_default_option(options_ident,'analytic_derivation_mode',options_.analytic_derivation_mode); % if not set by user, inherit default global one
[dataset_, dataset_info, xparam1, hh, M_, options_, oo_, estim_params_, bayestopt_, bounds] = ...
dynare_estimation_init(M_.endo_names, fname_,1, M_, options_, oo_, estim_params_, bayestopt_);
options_ident = set_default_option(options_ident,'analytic_derivation_mode', options_.analytic_derivation_mode); % if not set by user, inherit default global one
if prior_exist
if any(bayestopt_.pshape > 0)
@ -206,7 +205,7 @@ if prior_exist
end
end
if options_.TeX
name_tex=char(name_tex);
name_tex=name_tex;
end
else
indx = [1:M_.param_nbr];
@ -214,8 +213,10 @@ else
offset = M_.exo_nbr;
np = M_.param_nbr;
nparam = np+offset;
name = [cellstr([repmat('SE_',size(M_.exo_names_tex)),M_.exo_names_tex]); cellstr(M_.param_names)];
name_tex = [cellstr([repmat('$ SE_',size(M_.exo_names_tex)),M_.exo_names_tex,repmat('}$',size(M_.exo_names_tex))]); cellstr(M_.param_names_tex)];
name = cellfun(@(x) horzcat('SE_', x), M_.exo_names, 'UniformOutput', false);
name = vertcat(name, M_.param_names);
name_tex = cellfun(@(x) horzcat('$ SE_{', x, '} $'), M_.exo_names, 'UniformOutput', false);
name_tex = vertcat(name_tex, M_.param_names_tex);
if ~isequal(M_.H,0)
fprintf('\ndynare_identification:: Identification does not support measurement errors and will ignore them in the following. To test their identifiability, instead define them explicitly in measurement equations in the model definition.\n')
end

42
matlab/dynare_sensitivity.m
View File

@ -4,7 +4,7 @@ function x0=dynare_sensitivity(options_gsa)
% Reference:
% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
% Copyright (C) 2008-2017 Dynare Team
% Copyright (C) 2008-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -124,7 +124,8 @@ if ~isempty(options_gsa.datafile) || isempty(bayestopt_) || options_gsa.rmse
options_.mode_compute = 0;
options_.filtered_vars = 1;
options_.plot_priors = 0;
[dataset_,dataset_info,xparam1,hh, M_, options_, oo_, estim_params_,bayestopt_]=dynare_estimation_init(M_.endo_names,fname_,1, M_, options_, oo_, estim_params_, bayestopt_);
[dataset_,dataset_info,xparam1,hh, M_, options_, oo_, estim_params_, bayestopt_] = ...
dynare_estimation_init(M_.endo_names, fname_, 1, M_, options_, oo_, estim_params_, bayestopt_);
% computes a first linear solution to set up various variables
else
if isempty(options_.qz_criterium)
@ -186,23 +187,23 @@ options_gsa = set_default_option(options_gsa,'logtrans_redform',0);
options_gsa = set_default_option(options_gsa,'threshold_redform',[]);
options_gsa = set_default_option(options_gsa,'ksstat_redform',0.001);
options_gsa = set_default_option(options_gsa,'alpha2_redform',1.e-5);
options_gsa = set_default_option(options_gsa,'namendo',[]);
options_gsa = set_default_option(options_gsa,'namendo',{});
options_gsa = set_default_option(options_gsa,'namlagendo',[]);
options_gsa = set_default_option(options_gsa,'namexo',[]);
options_gsa = set_default_option(options_gsa,'namexo',{});
% RMSE mapping
options_gsa = set_default_option(options_gsa,'load_rmse',0);
options_gsa = set_default_option(options_gsa,'lik_only',0);
options_gsa = set_default_option(options_gsa,'var_rmse',char(options_.varobs));
options_gsa = set_default_option(options_gsa,'var_rmse', options_.varobs);
%get corresponding TeX-names;
options_gsa.var_rmse_tex='';
for ii=1:size(options_gsa.var_rmse,1)
temp_name=M_.endo_names_tex(strmatch(deblank(options_gsa.var_rmse(ii,:)),M_.endo_names,'exact'),:);
options_gsa.var_rmse_tex=strvcat(options_gsa.var_rmse_tex,temp_name);
options_gsa.var_rmse_tex={};
for ii=1:length(options_gsa.var_rmse)
temp_name = M_.endo_names_tex{strmatch(options_gsa.var_rmse{ii}, M_.endo_names, 'exact')};
options_gsa.var_rmse_tex = vertcat(options_gsa.var_rmse_tex, temp_name);
end
options_gsa = set_default_option(options_gsa,'pfilt_rmse',0.1);
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);
options_gsa = set_default_option(options_gsa,'pfilt_rmse', 0.1);
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
options_gsa.pprior=0;
@ -324,13 +325,13 @@ if options_gsa.redform && ~isempty(options_gsa.namendo)
x0 = stab_map_(OutputDirectoryName,options_gsa);
end
if strmatch(':',options_gsa.namendo,'exact')
options_gsa.namendo=M_.endo_names(1:M_.orig_endo_nbr,:);
options_gsa.namendo = M_.endo_names(1:M_.orig_endo_nbr);
end
if strmatch(':',options_gsa.namexo,'exact')
options_gsa.namexo=M_.exo_names;
options_gsa.namexo = M_.exo_names;
end
if strmatch(':',options_gsa.namlagendo,'exact')
options_gsa.namlagendo=M_.endo_names(1:M_.orig_endo_nbr,:);
options_gsa.namlagendo = M_.endo_names(1:M_.orig_endo_nbr);
end
% options_.opt_gsa = options_gsa;
if options_gsa.morris==1
@ -345,7 +346,6 @@ if options_gsa.redform && ~isempty(options_gsa.namendo)
fprintf('After obtaining the files, you need to unpack them and set a Matlab Path to those files.\n')
error('SS-ANOVA-R Toolbox missing!')
end
redform_map(OutputDirectoryName,options_gsa);
end
end
@ -462,7 +462,7 @@ if options_gsa.glue
Obs.name{j} = options_.varobs{j};
vj = options_.varobs{j};
jxj = strmatch(vj,lgy_(dr_.order_var,:),'exact');
jxj = strmatch(vj,lgy_(dr_.order_var),'exact');
js = strmatch(vj,lgy_,'exact');
if ~options_gsa.ppost
% y0=zeros(gend+1,nruns);
@ -502,7 +502,7 @@ if options_gsa.glue
for j=1:M_.endo_nbr
if ~ismember(j,ismoo)
jsmoo=jsmoo+1;
vj=deblank(M_.endo_names(dr_.order_var(j),:));
vj = M_.endo_names{dr_.order_var(j)};
if ~options_gsa.ppost
% y0 = squeeze(stock_smooth(:,j,:)) + ...
% kron(stock_ys(j,:),ones(size(stock_smooth,1),1));
@ -518,9 +518,9 @@ if options_gsa.glue
Out1(jsmoo).ini = 'yes';
end
end
tit(M_.exo_names_orig_ord,:) = M_.exo_names;
tit(M_.exo_names_orig_ord) = M_.exo_names;
for j=1:M_.exo_nbr
Exo(j).name = deblank(tit(j,:));
Exo(j).name = tit{j};
end
if ~options_gsa.ppost
Lik(length(options_.varobs)+1).name = 'logpo';

26
matlab/dynasave.m
View File

@ -1,4 +1,4 @@
function dynasave(s,var_list)
function dynasave(s, var_list)
% function dynasave(s,var_list)
% This optional command saves the simulation results in a .MAT file.
%
@ -12,7 +12,7 @@ function dynasave(s,var_list)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2001-2015 Dynare Team
% Copyright (C) 2001-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -31,28 +31,28 @@ function dynasave(s,var_list)
global M_ oo_
if size(var_list,1) == 0
var_list = M_.endo_names(1:M_.orig_endo_nbr, :);
if isempty(var_list)
var_list = M_.endo_names(1:M_.orig_endo_nbr);
end
if ~isfield(oo_,'endo_simul') || isempty(oo_.endo_simul)
if ~isfield(oo_, 'endo_simul') || isempty(oo_.endo_simul)
error('dynasave:: The results structure does not contain simulated series. Maybe the periods option has not been set.')
end
n = size(var_list,1);
ivar=zeros(n,1);
n = length(var_list);
ivar = zeros(n, 1);
for i=1:n
i_tmp = strmatch(var_list(i,:),M_.endo_names,'exact');
i_tmp = strmatch(var_list{i}, M_.endo_names, 'exact');
if isempty(i_tmp)
error (['One of the specified variables does not exist']) ;
error ('One of the specified variables does not exist') ;
else
ivar(i) = i_tmp;
end
end
eval([var_list(1,:) '=oo_.endo_simul(ivar(1),:)'';'])
eval(['save ' s ' ' var_list(1,:) ' -mat'])
eval([var_list{1} ' = oo_.endo_simul(ivar(1),:)'';'])
eval(['save ' s ' ' var_list{1} ' -mat'])
for dynare__i_ = 2:n
eval([var_list(dynare__i_,:) '=oo_.endo_simul(ivar(dynare__i_),:)'';'])
eval(['save ' s ' ' var_list(dynare__i_,:) ' -append -mat'])
eval([var_list{dynare__i_} ' = oo_.endo_simul(ivar(dynare__i_),:)'';'])
eval(['save ' s ' ' var_list{dynare__i_} ' -append -mat'])
end

17
matlab/dynatype.m
View File

@ -13,7 +13,7 @@ function dynatype (s,var_list)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2001-2017 Dynare Team
% Copyright (C) 2001-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -34,23 +34,24 @@ global M_ oo_
fid=fopen(s,'w') ;
if size(var_list,1) == 0
var_list = M_.endo_names(1:M_.orig_endo_nbr,:);
if isempty(var_list)
var_list = M_.endo_names(1:M_.orig_endo_nbr);
end
n = size(var_list,1);
ivar=zeros(n,1);
n = length(var_list);
ivar = zeros(n,1);
for i=1:n
i_tmp = strmatch(var_list(i,:),M_.endo_names,'exact');
i_tmp = strmatch(var_list{i}, M_.endo_names, 'exact');
if isempty(i_tmp)
error (['One of the specified variables does not exist']) ;
error ('One of the specified variables does not exist') ;
else
ivar(i) = i_tmp;
end
end
for i = 1:n
fprintf(fid,M_.endo_names(ivar(i),:),'\n') ;
fprintf(fid,M_.endo_names{ivar(i)},'\n') ;
fprintf(fid,'\n') ;
fprintf(fid,'%15.8g\n',oo_.endo_simul(ivar(i),:)') ;
end

72
matlab/dyntable.m
View File

@ -1,17 +1,21 @@
function dyntable(options_,title,headers,labels,values,label_width,val_width,val_precis,optional_header)
% function dyntable(title,headers,labels,values,label_width,val_width,val_precis)
% Inputs:
% options_ [structure] Dynare options structure
% title [string] Table title
% headers [n by nchar] character array of labels for header row
% labels [n by nchar] character array of labels for label column
% values [matrix] matrix of values to display
% label_width [scalar] Width of the label
% val_width [scalar] Width of value column
% val_precis [integer] precision of displayed values
function dyntable(options_, title, headers, labels, values, label_width, val_width, val_precis, optional_header)
% Prints a table of results in main command window.
%
% INPUTS
% - options_ [structure] Dynare options structure
% - title [string] Table title
% - headers [cell] labels for header row (each element is a row characater array)
% - labels [cell] labels for label column (each element is a row characater array)
% - values [double] matrix of values to display
% - label_width [integer] scalar, width of the label
% - val_width [integer] scalar, width of value column
% - val_precis [integer] scalar, precision of displayed values
%
% Copyright (C) 2002-2017 Dynare Team
% OUTPUTS
% none
% Copyright (C) 2002-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -32,16 +36,16 @@ if options_.noprint
return
end
%% get width of label column
if ~isempty(label_width)
label_width = max(size(deblank(char(headers(1,:),labels)),2)+2, ...
label_width);
else %use default length
label_width = max(size(deblank(char(headers(1,:),labels)),2))+2;
% Set width of label column
if isempty(label_width)
label_width = cellofchararraymaxlength(vertcat(headers{1}, labels))+2;
else
label_width = max(cellofchararraymaxlength(vertcat(headers{1}, labels))+2, label_width);
end
label_format_leftbound = sprintf('%%-%ds',label_width);
label_format_leftbound = sprintf('%%-%ds', label_width);
%% get width of label column
% Set width of other columns
if all(~isfinite(values))
values_length = 4;
else
@ -50,32 +54,32 @@ end
if any(values) < 0 %add one character for minus sign
values_length = values_length+1;
end
%% get width of header strings
headers_length = max(size(deblank(headers(2:end,:)),2));
if ~isempty(val_width)
val_width = max(max(headers_length,values_length)+2,val_width);
headers_length = cellofchararraymaxlength(headers(2:end));
if isempty(val_width)
val_width = max(headers_length, values_length)+2;
else
val_width = max(headers_length,values_length)+2;
val_width = max(max(headers_length, values_length)+2, val_width);
end
value_format = sprintf('%%%d.%df',val_width,val_precis);
header_string_format = sprintf('%%%ds',val_width);
value_format = sprintf('%%%d.%df', val_width, val_precis);
header_string_format = sprintf('%%%ds', val_width);
if length(title) > 0
fprintf('\n\n%s\n',title);
end
%Create and print header string
% Create and print header string
if nargin==9
disp(optional_header)
end
if length(headers) > 0
hh = sprintf(label_format_leftbound ,deblank(headers(1,:)));
for i=2:size(headers,1)
hh = [hh sprintf(header_string_format,deblank(headers(i,:)))];
hh = sprintf(label_format_leftbound , headers{1});
for i=2:length(headers)
hh = [hh sprintf(header_string_format, headers{i})];
end
disp(hh);
disp(hh)
end
for i=1:size(values,1)
disp([sprintf(label_format_leftbound ,deblank(labels(i,:))) sprintf(value_format ,values(i,:))]);
disp([sprintf(label_format_leftbound, labels{i}) sprintf(value_format, values(i,:))])
end

20
matlab/endogenous_prior_restrictions.m
View File

@ -15,7 +15,7 @@ function [info, info_irf, info_moment, data_irf, data_moment] = endogenous_prior
% info_moment [double] array of test checks for all individual moment restrictions
%
% Copyright (C) 2013-2017 Dynare Team
% Copyright (C) 2013-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -47,22 +47,22 @@ if ~isempty(endo_prior_restrictions.irf)
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,:);
varlist = Model.endo_names(DynareResults.dr.order_var);
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)
varlist=varlist(DynareResults.dr.restrict_var_list,:);
if size(T,1)<length(varlist)
varlist = varlist(DynareResults.dr.restrict_var_list);
end
% check if endo_prior_restrictions.irf{:,1} variables are in varlist
varlistok=1;
for j=1:size(endo_prior_restrictions.irf,1)
if isempty(strmatch(endo_prior_restrictions.irf{j,1},varlist,'exact'))
if isempty(strmatch(endo_prior_restrictions.irf{j,1}, varlist, 'exact'))
varlistok=0;
end
end
if ~varlistok
varlist=Model.endo_names(DynareResults.dr.order_var,:);
varlist = Model.endo_names(DynareResults.dr.order_var);
[T,R,SteadyState,infox,Model,DynareOptions,DynareResults] = dynare_resolve(Model,DynareOptions,DynareResults);
end
end
@ -81,8 +81,8 @@ if ~isempty(endo_prior_restrictions.irf)
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');
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))
info_irf(j,:)=info_irf(j,:).*[0, 0];
@ -108,7 +108,7 @@ if ~isempty(endo_prior_restrictions.moment)
return
end
data_moment=cell(size(endo_prior_restrictions.moment,1),1);
var_list_=endo_prior_restrictions.moment{1,1};
var_list_ = endo_prior_restrictions.moment{1,1};
for j=1:size(endo_prior_restrictions.moment,1)
tmp=endo_prior_restrictions.moment{j,1};
if ~ismember(tmp,cellstr(var_list_))
@ -129,7 +129,7 @@ if ~isempty(endo_prior_restrictions.moment)
nvar = size(var_list_,1);
ivar=zeros(nvar,1);
for i=1:nvar
i_tmp = strmatch(var_list_(i,:),Model.endo_names,'exact');
i_tmp = strmatch(var_list_(i,:), Model.endo_names, 'exact');
if isempty(i_tmp)
error (['One of the variable specified does not exist'])
else

4
matlab/ep/extended_path.m
View File

@ -19,7 +19,7 @@ function [ts, DynareResults] = extended_path(initialconditions, samplesize, exog
%
% SPECIAL REQUIREMENTS
% Copyright (C) 2009-2017 Dynare Team
% Copyright (C) 2009-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -98,7 +98,7 @@ if any(isnan(endogenous_variables_paths(:)))
nn = size(endogenous_variables_paths, 1);
endogenous_variables_paths = reshape(endogenous_variables_paths(sl), nn, length(sl)/nn);
end
ts = dseries(transpose(endogenous_variables_paths), initial_period, cellstr(DynareModel.endo_names));
ts = dseries(transpose(endogenous_variables_paths), initial_period, DynareModel.endo_names);
DynareResults.endo_simul = transpose(ts.data);
assignin('base', 'Simulated_time_series', ts);

4
matlab/evaluate_planner_objective.m
View File

@ -11,7 +11,7 @@ function planner_objective_value = evaluate_planner_objective(M,options,oo)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2007-2017 Dynare Team
% Copyright (C) 2007-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -39,7 +39,7 @@ if nspred > 180
planner_objective_value = NaN;
return
end
beta = get_optimal_policy_discount_factor(M.params,M.param_names);
beta = get_optimal_policy_discount_factor(M.params, M.param_names);
Gy = dr.ghx(nstatic+(1:nspred),:);
Gu = dr.ghu(nstatic+(1:nspred),:);

6
matlab/evaluate_steady_state.m
View File

@ -22,7 +22,7 @@ function [ys,params,info] = evaluate_steady_state(ys_init,M,options,oo,steadysta
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2001-2017 Dynare Team
% Copyright (C) 2001-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -124,14 +124,14 @@ if options.ramsey_policy
if ~isempty(infrow)
fprintf('\nevaluate_steady_state: The initial values for the steady state of the following variables are Inf:\n');
for iter=1:length(infrow)
fprintf('%s\n',M.endo_names(infrow(iter),:));
fprintf('%s\n',M.endo_names{infrow(iter)});
end
end
nanrow=find(isnan(ys_init));
if ~isempty(nanrow)
fprintf('\nevaluate_steady_state: The initial values for the steady state of the following variables are NaN:\n');
for iter=1:length(nanrow)
fprintf('%s\n',M.endo_names(nanrow(iter),:));
fprintf('%s\n',M.endo_names{nanrow(iter)});
end
end
end

14
matlab/evaluate_steady_state_file.m
View File

@ -19,7 +19,7 @@ function [ys,params,info] = evaluate_steady_state_file(ys_init,exo_ss,M,options,
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2001-2017 Dynare Team
% Copyright (C) 2001-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -117,19 +117,19 @@ if length(M.aux_vars) > 0 && ~options.ramsey_policy
ys3 = ys;
idx = find(abs(ys0-ys1)>0);
if ~isempty(idx)
M.endo_names(idx,:)
M.endo_names{idx}
else
disp('1-invariant')
end
idx = find(abs(ys2-ys1)>0);
if ~isempty(idx)
M.endo_names(idx,:)
M.endo_names{idx}
else
disp('2-invariant')
end
idx = find(abs(ys3-ys3)>0);
if ~isempty(idx)
M.endo_names(idx,:)
M.endo_names{idx}
else
disp('3-invariant')
end
@ -160,9 +160,7 @@ elseif ~isempty(options.steadystate_partial)
nov = length(ssvar);
indv = zeros(nov,1);
for i = 1:nov
indv(i) = strmatch(ssvar(i),M.endo_names,'exact');
indv(i) = strmatch(ssvar(i), M.endo_names, 'exact');
end
[ys,check] = dynare_solve('restricted_steadystate',...
ys(indv),...
options, exo_ss,indv);
[ys,check] = dynare_solve('restricted_steadystate', ys(indv), options, exo_ss,indv);
end

34
matlab/forcst.m
View File

@ -22,7 +22,7 @@ function [yf,int_width,int_width_ME]=forcst(dr,y0,horizon,var_list,M_,oo_,option
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2017 Dynare Team
% Copyright (C) 2003-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -48,16 +48,16 @@ endo_nbr = M_.endo_nbr;
inv_order_var = dr.inv_order_var;
[A,B] = kalman_transition_matrix(dr,nstatic+(1:nspred),1:nc,M_.exo_nbr);
if size(var_list,1) == 0
var_list = M_.endo_names(1:M_.orig_endo_nbr,:);
if isempty(var_list)
var_list = M_.endo_names(1:M_.orig_endo_nbr);
end
nvar = size(var_list,1);
ivar=zeros(nvar,1);
nvar = length(var_list);
ivar = zeros(nvar, 1);
for i=1:nvar
i_tmp = strmatch(var_list(i,:),M_.endo_names,'exact');
i_tmp = strmatch(var_list{i}, M_.endo_names, 'exact');
if isempty(i_tmp)
disp(var_list(i,:));
error (['One of the variable specified does not exist']) ;
disp(var_list{i});
error ('One of the variable specified does not exist') ;
else
ivar(i) = i_tmp;
end
@ -71,8 +71,8 @@ sigma_u = B*M_.Sigma_e*B';
sigma_u1 = ghu1*M_.Sigma_e*ghu1';
sigma_y = 0; %no uncertainty about the states
var_yf=NaN(horizon,nvar); %initialize
for i=1:horizon
var_yf = NaN(horizon,nvar); %initialize
for i = 1:horizon
%map uncertainty about states into uncertainty about observables
sigma_y1 = ghx1*sigma_y*ghx1'+sigma_u1;
var_yf(i,:) = diag(sigma_y1)';
@ -85,18 +85,18 @@ for i=1:horizon
end
if nargout==3
var_yf_ME=var_yf;
[loc_H,loc_varlist]=ismember(options_.varobs',options_.varlist);
loc_varlist(loc_varlist==0)=[];
[loc_H, loc_varlist] = ismember(options_.varobs', options_.varlist);
loc_varlist(loc_varlist==0) = [];
if ~isempty(loc_varlist)
var_yf_ME(:,loc_varlist)=var_yf(:,loc_varlist)+ repmat(diag(M_.H(loc_H,loc_H))',horizon,1);
var_yf_ME(:,loc_varlist) = var_yf(:,loc_varlist)+repmat(diag(M_.H(loc_H,loc_H))', horizon, 1);
end
int_width_ME = zeros(horizon,nvar);
int_width_ME = zeros(horizon, nvar);
end
fact = norminv((1-options_.forecasts.conf_sig)/2,0,1);
fact = norminv((1-options_.forecasts.conf_sig)/2, 0, 1);
int_width = zeros(horizon,nvar);
for i=1:nvar
int_width = zeros(horizon, nvar);
for i = 1:nvar
int_width(:,i) = -fact*sqrt(var_yf(:,i));
if nargout==3
int_width_ME(:,i) = -fact*sqrt(var_yf_ME(:,i));

32
matlab/forecast_graphs.m
View File

@ -8,7 +8,7 @@ function forecast_graphs(var_list,M_, oo_,options_)
% o oo_ outputs structure
% o options_ options structure
% Copyright (C) 2008-2017 Dynare Team
% Copyright (C) 2008-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -35,13 +35,13 @@ yf = oo_.forecast.Mean;
hpdinf = oo_.forecast.HPDinf;
hpdsup = oo_.forecast.HPDsup;
if isempty(var_list)
var_list = endo_names(1:M_.orig_endo_nbr,:);
var_list = endo_names(1:M_.orig_endo_nbr);
end
i_var = [];
for i = 1:size(var_list)
tmp = strmatch(var_list(i,:),endo_names,'exact');
for i = 1:length(var_list)
tmp = strmatch(var_list{i}, endo_names, 'exact');
if isempty(tmp)
error([var_list(i,:) ' isn''t an endogenous variable'])
error([var_list{i} ' isn''t an endogenous variable'])
end
i_var = [i_var; tmp];
end
@ -55,17 +55,18 @@ if ~exist([dname '/graphs'],'dir')
mkdir(dname,'graphs');
end
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fidTeX=write_LaTeX_header([M_.dname '/graphs/',fname,'_forcst.tex']);
if options_.TeX && any(strcmp('eps', cellstr(options_.graph_format)))
fidTeX = write_LaTeX_header([M_.dname '/graphs/', fname, '_forcst.tex']);
end
m = 1;
n_fig = 1;
hh=dyn_figure(options_.nodisplay,'Name','Forecasts (I)');
hh = dyn_figure(options_.nodisplay, 'Name', 'Forecasts (I)');
for j= 1:nvar
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)))
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');
fprintf(fidTeX,'\\centering \n');
fprintf(fidTeX,'\\includegraphics[width=0.8\\textwidth]{%s/graphs/forcst%d}\n',dname,n_fig);
@ -78,16 +79,9 @@ for j= 1:nvar
eval(['hh=dyn_figure(options_.nodisplay,''Name'',''Forecasts (' int2str(n_fig) ')'');']);
m = 1;
end
subplot(nr,nc,m);
vn = deblank(endo_names(i_var(j),:));
subplot(nr, nc, m);
vn = endo_names{i_var(j)};
obs = 0;
% $$$ k = strmatch(vn,varobs,'exact');
% $$$ if ~isempty(k)
% $$$ yy = y.(vn)(end-9:end) + repmat(ys(i_var(j)),10,1)+trend(k,:)';
% $$$ plot(yy);
% $$$ hold on
% $$$ obs = 10;
% $$$ end
plot([NaN(obs,1); yf.(vn)],'b-');
hold on
plot([NaN(obs,1); hpdinf.(vn)],'b-');

16
matlab/formdata.m
View File

@ -11,7 +11,7 @@ function formdata(fname,date)
% SPECIAL REQUIREMENT
% none
% Copyright (C) 2007-2017 Dynare Team
% Copyright (C) 2007-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -31,11 +31,11 @@ function formdata(fname,date)
global M_ oo_
fid = fopen([fname '_endo.frm'],'w');
n=size(oo_.endo_simul,1);
t=size(oo_.endo_simul,2);
SN=upper(cellstr(M_.endo_names));
for i=1:n
str=char(SN(i));
n = size(oo_.endo_simul, 1);
t = size(oo_.endo_simul, 2);
SN = upper(M_.endo_names);
for i = 1:n
str=SN{i};
fprintf(fid,'USER: x x DATAFILE: x %s\n',str);
fprintf(fid,'PER: 1 YEAR: %s FRAC: 1 NOBS: %d CLINES: 0 DLINES: ???\n',date,t);
fprintf(fid,'%10.5f %10.5f %10.5f %10.5f\n',reshape(oo_.endo_simul(i,1:floor(t/4)*4),floor(t/4),4));
@ -56,9 +56,9 @@ fclose(fid);
fid = fopen([fname '_exo.frm'],'w');
n=size(oo_.exo_simul,2);
t=size(oo_.exo_simul,1);
SN=upper(cellstr(M_.exo_names));
SN=upper(M_.exo_names);
for i=1:n
str=char(SN(i));
str = SN{i};
fprintf(fid,'USER: x x DATAFILE: x %s\n',str);
fprintf(fid,'PER: 1 YEAR: %s FRAC: 1 NOBS: %d CLINES: 0 DLINES: ???\n',date,t);
fprintf(fid,'%10.5f %10.5f %10.5f %10.5f\n',reshape(oo_.exo_simul(1:floor(t/4)*4,i),floor(t/4),4));

40
matlab/generate_trace_plots.m
View File

@ -11,7 +11,7 @@ function generate_trace_plots(chain_number)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2016 Dynare Team
% Copyright (C) 2016-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -32,37 +32,37 @@ global M_ options_ estim_params_
% Get informations about the posterior draws:
MetropolisFolder = CheckPath('metropolis',M_.dname);
MetropolisFolder = CheckPath('metropolis', M_.dname);
load_last_mh_history_file(MetropolisFolder, M_.fname);
if chain_number>record.Nblck
error('generate_trace_plots:: chain number is bigger than existing number of chains')
end
trace_plot(options_,M_,estim_params_,'PosteriorDensity',chain_number)
trace_plot(options_, M_, estim_params_, 'PosteriorDensity', chain_number)
for ii=1:size(estim_params_.param_vals,1)
parameter_name=deblank(M_.param_names(estim_params_.param_vals(ii,1),:));
trace_plot(options_,M_,estim_params_,'DeepParameter',chain_number,parameter_name)
for ii=1:size(estim_params_.param_vals, 1)
parameter_name = M_.param_names{estim_params_.param_vals(ii,1)};
trace_plot(options_, M_, estim_params_, 'DeepParameter', chain_number, parameter_name)
end
for ii=1:size(estim_params_.var_exo,1)
parameter_name=deblank(M_.exo_names(estim_params_.var_exo(ii,1),:));
trace_plot(options_,M_,estim_params_,'StructuralShock',chain_number,parameter_name)
for ii=1:size(estim_params_.var_exo, 1)
parameter_name = M_.exo_names{estim_params_.var_exo(ii,1)};
trace_plot(options_, M_, estim_params_, 'StructuralShock', chain_number, parameter_name)
end
for ii=1:size(estim_params_.var_endo,1)
parameter_name=deblank(M_.endo_names(estim_params_.var_endo(ii,1),:));
trace_plot(options_,M_,estim_params_,'MeasurementError',chain_number,parameter_name)
for ii=1:size(estim_params_.var_endo, 1)
parameter_name = M_.endo_names{estim_params_.var_endo(ii,1)};
trace_plot(options_, M_, estim_params_, 'MeasurementError', chain_number, parameter_name)
end
for ii=1:size(estim_params_.corrn,1)
parameter_name_1=deblank(M_.endo_names(estim_params_.corrn(ii,1),:));
parameter_name_2=deblank(M_.endo_names(estim_params_.corrn(ii,2),:));
trace_plot(options_,M_,estim_params_,'MeasurementError',chain_number,parameter_name_1,parameter_name_2)
for ii=1:size(estim_params_.corrn, 1)
parameter_name_1 = M_.endo_names{estim_params_.corrn(ii,1)};
parameter_name_2 = M_.endo_names{estim_params_.corrn(ii,2)};
trace_plot(options_, M_, estim_params_, 'MeasurementError', chain_number, parameter_name_1, parameter_name_2)
end
for ii=1:size(estim_params_.corrx,1)
parameter_name_1=deblank(M_.exo_names(estim_params_.corrx(ii,1),:));
parameter_name_2=deblank(M_.exo_names(estim_params_.corrx(ii,2),:));
trace_plot(options_,M_,estim_params_,'StructuralShock',chain_number,parameter_name_1,parameter_name_2)
for ii=1:size(estim_params_.corrx, 1)
parameter_name_1 = M_.exo_names{estim_params_.corrx(ii,1)};
parameter_name_2 = M_.exo_names{estim_params_.corrx(ii,2)};
trace_plot(options_, M_, estim_params_, 'StructuralShock', chain_number, parameter_name_1, parameter_name_2)
end

4
matlab/getIrfShocksIndx.m
View File

@ -8,7 +8,7 @@ function irf_shocks_indx=getIrfShocksIndx()
% Outputs:
% irf_shocks_indx: [1 by n_irf_shocks] vector storing the indices
%
% Copyright (C) 2011-2017 Dynare Team
% Copyright (C) 2011-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -32,7 +32,7 @@ if (isfield(options_,'irf_shocks')==0)
else
irf_shocks_indx = zeros(1,size(options_.irf_shocks,1));
for i=1:size(options_.irf_shocks,1)
irf_shocks_indx(i) = find(strcmp(deblank(options_.irf_shocks(i,:)), cellstr(M_.exo_names)));
irf_shocks_indx(i) = find(strcmp(deblank(options_.irf_shocks(i,:)), M_.exo_names));
end
irf_shocks_indx_unique=unique(irf_shocks_indx);
if options_.debug && (length(irf_shocks_indx_unique) ~= length(irf_shocks_indx))

4
matlab/get_optimal_policy_discount_factor.m
View File

@ -13,7 +13,7 @@ function discount_factor=get_optimal_policy_discount_factor(params,param_names)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2007-2017 Dynare Team
% Copyright (C) 2007-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -30,4 +30,4 @@ function discount_factor=get_optimal_policy_discount_factor(params,param_names)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
discount_factor = params(find(strcmp('optimal_policy_discount_factor',cellstr(param_names))));
discount_factor = params(find(strcmp('optimal_policy_discount_factor', param_names)));

10
matlab/get_posterior_parameters.m
View File

@ -15,7 +15,7 @@ function xparam = get_posterior_parameters(type,M_,estim_params_,oo_,options_,fi
% SPECIAL REQUIREMENTS
% None.
% Copyright (C) 2006-2017 Dynare Team
% Copyright (C) 2006-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -46,7 +46,7 @@ xparam = zeros(nvx+nvn+ncx+ncn+np,1);
m = 1;
for i=1:nvx
k1 = estim_params_.var_exo(i,1);
name1 = deblank(M_.exo_names(k1,:));
name1 = M_.exo_names{k1};
xparam(m) = oo_.([field1 type]).shocks_std.(name1);
m = m+1;
end
@ -61,8 +61,8 @@ end
for i=1:ncx
k1 = estim_params_.corrx(i,1);
k2 = estim_params_.corrx(i,2);
name1 = deblank(M_.exo_names(k1,:));
name2 = deblank(M_.exo_names(k2,:));
name1 = M_.exo_names{k1};
name2 = M_.exo_names{k2};
xparam(m) = oo_.([field1 type]).shocks_corr.([name1 '_' name2]);
m = m+1;
end
@ -79,7 +79,7 @@ end
FirstDeep = m;
for i=1:np
name1 = deblank(M_.param_names(estim_params_.param_vals(i,1),:));
name1 = M_.param_names{estim_params_.param_vals(i,1)};
xparam(m) = oo_.([field1 type]).parameters.(name1);
m = m+1;
end

38
matlab/get_the_name.m
View File

@ -1,4 +1,4 @@
function [nam,texnam] = get_the_name(k,TeX,M_,estim_params_,options_)
function [nam, texnam] = get_the_name(k, TeX, M_, estim_params_, options_)
%@info:
%! @deftypefn {Function File} {[@var{nam},@var{texnam}] =} get_the_name (@var{k},@var{TeX},@var{M_},@var{estim_params_},@var{options_})
@ -40,7 +40,7 @@ function [nam,texnam] = get_the_name(k,TeX,M_,estim_params_,options_)
%! @end deftypefn
%@eod:
% Copyright (C) 2004-2013 Dynare Team
% Copyright (C) 2004-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -66,44 +66,44 @@ ncx = estim_params_.ncx;
ncn = estim_params_.ncn;
if k <= nvx
vname = deblank(M_.exo_names(estim_params_.var_exo(k,1),:));
nam = ['SE_',vname];
vname = M_.exo_names{estim_params_.var_exo(k,1)};
nam = sprintf('SE_%s', vname);
if TeX
tname = deblank(M_.exo_names_tex(estim_params_.var_exo(k,1),:));
texnam = ['$ SE_{' tname '} $'];
tname = M_.exo_names_tex{estim_params_.var_exo(k,1)};
texnam = sprintf('$ SE_{%s} $', tname);
end
elseif k <= (nvx+nvn)
vname = options_.varobs{estim_params_.nvn_observable_correspondence(k-estim_params_.nvx,1)};
nam=['SE_EOBS_',vname];
nam = sprintf('SE_EOBS_%s', vname);
if TeX
tname = deblank(M_.endo_names_tex(estim_params_.var_endo(k-estim_params_.nvx,1),:));
texnam = ['$ EOBS SE_{' tname '} $'];
tname = M_.endo_names_tex{estim_params_.var_endo(k-estim_params_.nvx,1)};
texnam = sprintf('$ EOBS SE_{%s} $', tname);
end
elseif k <= (nvx+nvn+ncx)
jj = k - (nvx+nvn);
k1 = estim_params_.corrx(jj,1);
k2 = estim_params_.corrx(jj,2);
vname = [deblank(M_.exo_names(k1,:)) '_' deblank(M_.exo_names(k2,:))];
nam=['CC_',vname];
vname = sprintf('%s_%s', M_.exo_names{k1}, M_.exo_names{k2});
nam = sprintf('CC_%s', vname);
if TeX
tname = [deblank(M_.exo_names_tex(k1,:)) ',' deblank(M_.exo_names_tex(k2,:))];
texnam = ['$ CC_{' tname '} $'];
tname = sprintf('%s,%s', M_.exo_names_tex{k1}, M_.exo_names_tex{k2});
texnam = sprintf('$ CC_{%s} $', tname);
end
elseif k <= (nvx+nvn+ncx+ncn)
jj = k - (nvx+nvn+ncx);
k1 = estim_params_.corrn(jj,1);
k2 = estim_params_.corrn(jj,2);
vname = [deblank(M_.endo_names(k1,:)) '_' deblank(M_.endo_names(k2,:))];
nam=['CC_EOBS_' vname];
vname = sprintf('%s_%s', M_.endo_names{k1}, M_.endo_names{k2});
nam = sprintf('CC_EOBS_%s', vname);
if TeX
tname = [deblank(M_.endo_names_tex(k1,:)) ',' deblank(M_.endo_names_tex(k2,:))];
texnam =['$ EOBS CC_{' tname '} $'];
tname = sprintf('%s,%s', M_.endo_names_tex{k1}, M_.endo_names_tex{k2});
texnam = sprintf('$ EOBS CC_{%s} $', tname);
end
else
jj = k - (nvx+nvn+ncx+ncn);
jj1 = estim_params_.param_vals(jj,1);
nam = deblank(M_.param_names(jj1,:));
nam = M_.param_names{jj1};
if TeX
texnam = ['$ ' deblank(M_.param_names_tex(jj1,:)) ' $'];
texnam = sprintf('$ %s $', M_.param_names_tex{jj1});
end
end

25
matlab/get_variables_list.m
View File

@ -1,14 +1,16 @@
function [ivar,vartan,options_] = get_variables_list(options_,M_)
function [ivar, vartan, options_] = get_variables_list(options_, M_)
% This function builds a vector of indices in varlist or varobs.
%
% INPUTS
% o options_ [structure] Describes global options.
% o M_ [structure] Describes the model.
% o options_ [structure] Describes global options.
% o M_ [structure] Describes the model.
%
% OUTPUTS
% o ivar [integer] nvar*1 vector of indices (nvar is the number
% of variables).
% o vartan [char] array of characters (with nvar rows).
% o options_ [structure] Describes global options.
% o ivar [integer] nvar*1 vector of indices (nvar is the number
% of variables).
% o vartan [cell of char arrays] array of characters (with nvar rows).
% o options_ [structure] Describes global options.
%
% ALGORITHM
% None.
@ -16,7 +18,7 @@ function [ivar,vartan,options_] = get_variables_list(options_,M_)
% SPECIAL REQUIREMENTS
% None.
% Copyright (C) 2007-2017 Dynare Team
% Copyright (C) 2007-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -35,13 +37,12 @@ function [ivar,vartan,options_] = get_variables_list(options_,M_)
varlist = options_.varlist;
if isempty(varlist)
varlist = char(options_.varobs);
varlist = options_.varobs;
options_.varlist = varlist;
end
nvar = rows(varlist);
nvar = length(varlist);
vartan = varlist;
nvar = size(vartan,1);
ivar = zeros(nvar,1);
for i = 1:nvar
ivar(i) = strmatch(deblank(vartan(i,:)),M_.endo_names,'exact');
ivar(i) = strmatch(vartan{i}, M_.endo_names, 'exact');
end

4
matlab/global_initialization.m
View File

@ -11,7 +11,7 @@ function global_initialization()
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2017 Dynare Team
% Copyright (C) 2003-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -678,7 +678,7 @@ options_.particleswarm = particleswarm;
% prior analysis
options_.prior_mc = 20000;
options_.prior_analysis_endo_var_list = [];
options_.prior_analysis_endo_var_list = {};
% did model undergo block decomposition + minimum feedback set computation ?
options_.block = 0;

14
matlab/graph_decomp.m
View File

@ -11,7 +11,7 @@ function []=graph_decomp(z,shock_names,endo_names,i_var,initial_date,DynareModel
% DynareModel [structure] Dynare model structure
% DynareOptions [structure] Dynare options structure
% Copyright (C) 2010-2017 Dynare Team
% Copyright (C) 2010-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -109,7 +109,7 @@ for j=1:nvar
z1 = squeeze(z(i_var(j),:,:));
if screen_shocks
[junk, isort] = sort(mean(abs(z1(1:end-2,:)')), 'descend');
labels = char(char(shock_names(isort(1:16),:)),'Others', 'Initial values');
labels = char(char(shock_names(isort(1:16))),'Others', 'Initial values');
zres = sum(z1(isort(17:end),:),1);
z1 = [z1(isort(1:16),:); zres; z1(comp_nbr0:end,:)];
comp_nbr=18;
@ -128,7 +128,7 @@ for j=1:nvar
if ymax-ymin < 1e-6
continue
end
fhandle = dyn_figure(DynareOptions.plot_shock_decomp.nodisplay,'Name',[preamble_txt fig_name_long strrep(fig_mode1, '_', ' ') ': ' deblank(endo_names(i_var(j),:)) '.'], 'PaperPositionMode', 'auto','PaperOrientation','landscape','renderermode','auto');
fhandle = dyn_figure(DynareOptions.plot_shock_decomp.nodisplay,'Name',[preamble_txt fig_name_long strrep(fig_mode1, '_', ' ') ': ' endo_names{i_var(j)} '.'], 'PaperPositionMode', 'auto','PaperOrientation','landscape','renderermode','auto');
set(fhandle,'position' ,[50 50 1500 750])
ax=axes('Position',[0.1 0.1 0.6 0.8],'box','on');
% plot(ax,x(2:end),z1(end,:),'k-','LineWidth',2)
@ -213,13 +213,13 @@ for j=1:nvar
colormap(new_colormap)
end
hold off
dyn_saveas(fhandle,[GraphDirectoryName, filesep, DynareModel.fname,'_shock_decomposition_',deblank(endo_names(i_var(j),:)),fig_mode1,fig_name],DynareOptions.plot_shock_decomp.nodisplay,DynareOptions.plot_shock_decomp.graph_format);
dyn_saveas(fhandle,[GraphDirectoryName, filesep, DynareModel.fname,'_shock_decomposition_',endo_names{i_var(j)},fig_mode1,fig_name],DynareOptions.plot_shock_decomp.nodisplay,DynareOptions.plot_shock_decomp.graph_format);
if DynareOptions.TeX && any(strcmp('eps',cellstr(DynareOptions.plot_shock_decomp.graph_format)))
fprintf(fidTeX,'\\begin{figure}[H]\n');
fprintf(fidTeX,'\\centering \n');
fprintf(fidTeX,'\\includegraphics[width=0.8\\textwidth]{%s/graphs/%s_shock_decomposition_%s}\n',DynareModel.fname,DynareModel.fname,[deblank(endo_names(i_var(j),:)) fig_mode1 fig_name]);
fprintf(fidTeX,'\\label{Fig:shock_decomp:%s}\n',[fig_mode deblank(endo_names(i_var(j),:)) fig_name]);
fprintf(fidTeX,['\\caption{' preamble_txt fig_name_long strrep(fig_mode1, '_', ' ') ': $ %s $.}\n'],deblank(DynareModel.endo_names_tex(i_var(j),:)));
fprintf(fidTeX,'\\includegraphics[width=0.8\\textwidth]{%s/graphs/%s_shock_decomposition_%s}\n',DynareModel.fname,DynareModel.fname,[endo_names{i_var(j)} fig_mode1 fig_name]);
fprintf(fidTeX,'\\label{Fig:shock_decomp:%s}\n',[fig_mode endo_names{i_var(j)} fig_name]);
fprintf(fidTeX,['\\caption{' preamble_txt fig_name_long strrep(fig_mode1, '_', ' ') ': $ %s $.}\n'],DynareModel.endo_names_tex{i_var(j)});
fprintf(fidTeX,'\\end{figure}\n');
fprintf(fidTeX,' \n');
end

17
matlab/graph_decomp_detail.m
View File

@ -11,7 +11,7 @@ function []=graph_decomp_detail(z,shock_names,endo_names,i_var,initial_date,Dyna
% DynareModel [structure] Dynare model structure
% DynareOptions [structure] Dynare options structure
% Copyright (C) 2010-2017 Dynare Team
% Copyright (C) 2010-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -133,7 +133,7 @@ for j=1:nvar
z1 = squeeze(z(i_var(j),:,:));
if screen_shocks,
[junk, isort] = sort(mean(abs(z1(1:end-2,:)')), 'descend');
labels = char(char(shock_names(isort(1:16),:)),'Others', 'Initial values');
labels = char(char(shock_names(isort(1:16))),'Others', 'Initial values');
zres = sum(z1(isort(17:end),:),1);
z1 = [z1(isort(1:16),:); zres; z1(comp_nbr0:end,:)];
comp_nbr=18;
@ -151,7 +151,7 @@ for j=1:nvar
continue
end
for jf = 1:nfigs
fhandle = dyn_figure(DynareOptions.plot_shock_decomp.nodisplay,'Name',[preamble_txt fig_name_long strrep(fig_mode1, '_', ' ') ': ' deblank(endo_names(i_var(j),:)) ' (detail).'],'position',[200 100 650 850], 'PaperPositionMode', 'auto','PaperOrientation','portrait','renderermode','auto');
fhandle = dyn_figure(DynareOptions.plot_shock_decomp.nodisplay,'Name',[preamble_txt fig_name_long strrep(fig_mode1, '_', ' ') ': ' endo_names{i_var(j)} ' (detail).'],'position',[200 100 650 850], 'PaperPositionMode', 'auto','PaperOrientation','portrait','renderermode','auto');
a0=zeros(1,4);
a0(3)=inf;
a0(4)=-inf;
@ -183,7 +183,7 @@ for j=1:nvar
mydata.use_shock_groups = DynareOptions.plot_shock_decomp.use_shock_groups;
mydata.shock_group = shock_groups.(shock_ind{ic});
mydata.shock_decomp = DynareOptions.plot_shock_decomp;
if ~isempty(mydata.shock_group.shocks{1})
if ~isempty(mydata.shock_group.shocks)
c = uicontextmenu;
hax.UIContextMenu=c;
browse_menu = uimenu(c,'Label','Browse group');
@ -224,13 +224,14 @@ for j=1:nvar
else
suffix = ['_detail'];
end
dyn_saveas(fhandle,[GraphDirectoryName, filesep, DynareModel.fname,'_shock_decomposition_',deblank(endo_names(i_var(j),:)),fig_mode1,fig_name suffix],DynareOptions.plot_shock_decomp.nodisplay,DynareOptions.plot_shock_decomp.graph_format);
dyn_saveas(fhandle,[GraphDirectoryName, filesep, DynareModel.fname, ...
'_shock_decomposition_', endo_names{i_var(j)}, fig_mode1,fig_name suffix],DynareOptions.plot_shock_decomp.nodisplay,DynareOptions.plot_shock_decomp.graph_format);
if DynareOptions.TeX && any(strcmp('eps',cellstr(DynareOptions.plot_shock_decomp.graph_format)))
fprintf(fidTeX,'\\begin{figure}[H]\n');
fprintf(fidTeX,'\\centering \n');
fprintf(fidTeX,'\\includegraphics[width=0.8\\textwidth]{%s/graphs/%s_shock_decomposition_%s}\n',DynareModel.fname,DynareModel.fname,[deblank(endo_names(i_var(j),:)) fig_mode1 fig_name suffix]);
fprintf(fidTeX,'\\label{Fig:shock_decomp_detail:%s}\n',[fig_mode deblank(endo_names(i_var(j),:)) fig_name suffix]);
fprintf(fidTeX,['\\caption{' preamble_txt fig_name_long strrep(fig_mode1, '_', ' ') ': $ %s $ (detail).}\n'],deblank(DynareModel.endo_names_tex(i_var(j),:)));
fprintf(fidTeX,'\\includegraphics[width=0.8\\textwidth]{%s/graphs/%s_shock_decomposition_%s}\n',DynareModel.fname,DynareModel.fname,[endo_names{i_var(j)} fig_mode1 fig_name suffix]);
fprintf(fidTeX,'\\label{Fig:shock_decomp_detail:%s}\n',[fig_mode endo_names{i_var(j)} fig_name suffix]);
fprintf(fidTeX,['\\caption{' preamble_txt fig_name_long strrep(fig_mode1, '_', ' ') ': $ %s $ (detail).}\n'], DynareModel.endo_names_tex{i_var(j)});
fprintf(fidTeX,'\\end{figure}\n');
fprintf(fidTeX,' \n');
end

362
matlab/gsa/filt_mc_.m
View File

@ -14,7 +14,7 @@ function [rmse_MC, ixx] = filt_mc_(OutDir,options_gsa_,dataset_,dataset_info)
% marco.ratto@ec.europa.eu
% Copyright (C) 2012-2016 European Commission
% Copyright (C) 2012-2017 Dynare Team
% Copyright (C) 2012-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -38,12 +38,11 @@ vvarvecm = options_gsa_.var_rmse;
if options_.TeX
vvarvecm_tex = options_gsa_.var_rmse_tex;
else
vvarvecm_tex = [];
vvarvecm_tex = {};
end
loadSA = options_gsa_.load_rmse;
pfilt = options_gsa_.pfilt_rmse;
alpha = options_gsa_.alpha_rmse;
% alpha2 = options_gsa_.alpha2_rmse;
alpha2 = 0;
pvalue = options_gsa_.alpha2_rmse;
istart = max(2,options_gsa_.istart_rmse);
@ -133,7 +132,6 @@ if ~loadSA
M_ = set_all_parameters(xparam1_mean,estim_params_,M_);
ys_mean=steady_(M_,options_,oo_);
end
% eval(options_.datafile)
Y = transpose(dataset_.data);
gend = dataset_.nobs;
data_index = dataset_info.missing.aindex;
@ -141,8 +139,6 @@ if ~loadSA
for jx=1:gend
data_indx(jx,data_index{jx})=true;
end
%stock_gend=data_info.gend;
%stock_data = data_info.data;
load([DirectoryName filesep M_.fname '_data.mat']);
filfilt = dir([DirectoryName filesep M_.fname '_filter_step_ahead*.mat']);
temp_smooth_file_list = dir([DirectoryName filesep M_.fname '_smooth*.mat']);
@ -159,7 +155,6 @@ if ~loadSA
logpo2=[];
sto_ys=[];
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]);
x=[x; stock];
@ -173,11 +168,10 @@ 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)
vj=deblank(vvarvecm(i,:));
jxj(i) = strmatch(vj,lgy_(dr_.order_var,:),'exact');
js(i) = strmatch(vj,lgy_,'exact');
for i = 1:length(vvarvecm)
vj = vvarvecm{i};
jxj(i) = strmatch(vj, lgy_(dr_.order_var), 'exact');
js(i) = strmatch(vj, lgy_, 'exact');
yss(i,:,:)=repmat(sto_ys(:,js(i))',[gend,1]);
end
if exist('xparam1','var')
@ -213,7 +207,6 @@ if ~loadSA
r2_MC(j,:) = 1-mean((yobs(:,istart:end,j)'-y0(:,istart:end,j)').^2)./mean((yobs(:,istart:end,j)').^2);
end
if exist('xparam1_mean','var')
%eval(['rmse_pmean(i) = sqrt(mean((',vj,'(fobs-1+istart:fobs-1+nobs)-y0M(istart:end-1)).^2));'])
[alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK] = DsgeSmoother(xparam1_mean,gend,Y,data_index,missing_value,M_,oo_,options_,bayestopt_,estim_params_);
y0 = reshape( squeeze(aK(1,jxj,1:gend)),[gend length(jxj)]);% + kron(ys_mean(js),ones(1,gend)));
yobs = transpose( ahat(jxj,:));% + kron(ys_mean(js),ones(1,gend)));
@ -260,14 +253,14 @@ else
nfilt=floor(pfilt*nruns);
end
% smirnov tests
nfilt0=nfilt*ones(size(vvarvecm,1),1);
nfilt0 = nfilt*ones(length(vvarvecm), 1);
logpo2=logpo2(:);
if ~options_.opt_gsa.ppost
[dum, ipost]=sort(-logpo2);
[dum, ilik]=sort(-likelihood);
end
%% visual scatter analysis!
% visual scatter analysis!
if options_.opt_gsa.ppost
tmp_title='R2 Posterior:';
atitle='R2 Posterior:';
@ -291,8 +284,7 @@ options_scatter.amcf_name = asname;
options_scatter.amcf_title = atitle;
options_scatter.title = tmp_title;
scatter_analysis(r2_MC, x,options_scatter, options_);
%% end of visual scatter analysis
% end of visual scatter analysis
if ~options_.opt_gsa.ppost && options_.opt_gsa.lik_only
if options_.opt_gsa.pprior
@ -307,12 +299,12 @@ if ~options_.opt_gsa.ppost && options_.opt_gsa.lik_only
options_mcf.alpha2 = alpha2;
if options_.TeX
[pnames,pnames_tex]=get_LaTeX_parameter_names(M_,options_,estim_params_,bayestopt_);
options_mcf.param_names = char(pnames);
options_mcf.param_names_tex = char(pnames_tex);
options_mcf.param_names = pnames;
options_mcf.param_names_tex = pnames_tex;
else
[pnames]=get_LaTeX_parameter_names(M_,options_,estim_params_,bayestopt_);
options_mcf.param_names = char(pnames);
options_mcf.param_names_tex = [];
options_mcf.param_names = pnames;
options_mcf.param_names_tex = {};
end
options_mcf.fname_ = fname_;
options_mcf.OutputDirectoryName = OutDir;
@ -322,7 +314,6 @@ if ~options_.opt_gsa.ppost && options_.opt_gsa.lik_only
options_mcf.beha_title = 'better posterior kernel';
options_mcf.nobeha_title = 'worse posterior kernel';
mcf_analysis(x, ipost(1:nfilt), ipost(nfilt+1:end), options_mcf, options_);
if options_.opt_gsa.pprior
anam = 'rmse_prior_lik';
atitle = 'RMSE prior: Log Likelihood Kernel';
@ -351,22 +342,21 @@ else
r2_txt=NaN(1,size(r2_MC,2));
end
else
%nfilt0(i)=length(find(rmse_MC(:,i)<rmse_pmean(i)));
rmse_txt=rmse_pmean;
r2_txt=r2_pmean;
end
end
for i=1:size(vvarvecm,1)
[dum, ixx(:,i)]=sort(rmse_MC(:,i));
for i = 1:length(vvarvecm)
[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)
[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);
PP = ones(npar+nshock, length(vvarvecm));
PPV = ones(length(vvarvecm), length(vvarvecm), npar+nshock);
SS = zeros(npar+nshock, length(vvarvecm));
for j = 1:npar+nshock
for i = 1:length(vvarvecm)
[H, P, KSSTAT] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j), alpha);
[H1, P1, KSSTAT1] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j),alpha,1);
[H2, P2, KSSTAT2] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j),alpha,-1);
if H1 & H2==0
SS(j,i)=1;
elseif H1==0
@ -376,17 +366,11 @@ else
end
PP(j,i)=P;
end
for i=1:size(vvarvecm,1)
for l=1:size(vvarvecm,1)
for i = 1:length(vvarvecm)
for l = 1:length(vvarvecm)
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);
% PP(j,i)=min(P,PP(j,i));
% PP(j,l)=min(P,PP(j,l));
%if P<P1
% if SS(j,i)*SS(j,l)
PPV(i,l,j) = P;
% end
elseif l==i
PPV(i,l,j) = PP(j,i);
end
@ -395,7 +379,7 @@ else
end
if ~options_.nograph
ifig=0;
for i=1:size(vvarvecm,1)
for i=1:length(vvarvecm)
if options_.opt_gsa.ppost
temp_name='RMSE Posterior: Log Prior';
else
@ -416,8 +400,8 @@ else
set(h,'color','k','linewidth',1)
h=cumplot(lnprior(ixx(nfilt0(i)+1:end,i)));
set(h,'color','red','linewidth',2)
title(vvarvecm(i,:),'interpreter','none')
if mod(i,9)==0 || i==size(vvarvecm,1)
title(vvarvecm{i},'interpreter','none')
if mod(i,9)==0 || i==length(vvarvecm)
if ~isoctave
annotation('textbox', [0.1,0,0.35,0.05],'String', 'Log-prior for BETTER R2','Color','Blue','horizontalalignment','center');
annotation('textbox', [0.55,0,0.35,0.05],'String', 'Log-prior for WORSE R2', 'Color','Red','horizontalalignment','center');
@ -443,7 +427,7 @@ else
end
end
ifig=0;
for i=1:size(vvarvecm,1)
for i=1:length(vvarvecm)
if options_.opt_gsa.ppost
temp_name='RMSE Posterior: Log Likelihood';
else
@ -464,11 +448,11 @@ else
set(h,'color','k','linewidth',1)
h=cumplot(likelihood(ixx(nfilt0(i)+1:end,i)));
set(h,'color','red','linewidth',2)
title(vvarvecm(i,:),'interpreter','none')
title(vvarvecm{i},'interpreter','none')
if options_.opt_gsa.ppost==0
set(gca,'xlim',[min( likelihood(ixx(1:nfilt0(i),i)) ) max( likelihood(ixx(1:nfilt0(i),i)) )])
end
if mod(i,9)==0 || i==size(vvarvecm,1)
if mod(i,9)==0 || i==length(vvarvecm)
if ~isoctave
annotation('textbox', [0.1,0,0.35,0.05],'String', 'Log-likelihood for BETTER R2','Color','Blue','horizontalalignment','center');
annotation('textbox', [0.55,0,0.35,0.05],'String', 'Log-likelihood for WORSE R2', 'Color','Red','horizontalalignment','center');
@ -494,7 +478,7 @@ else
end
end
ifig=0;
for i=1:size(vvarvecm,1)
for i=1:length(vvarvecm)
if options_.opt_gsa.ppost
temp_name='RMSE Posterior: Log Posterior';
else
@ -515,11 +499,11 @@ else
set(h,'color','k','linewidth',1)
h=cumplot(logpo2(ixx(nfilt0(i)+1:end,i)));
set(h,'color','red','linewidth',2)
title(vvarvecm(i,:),'interpreter','none')
title(vvarvecm{i},'interpreter','none')
if options_.opt_gsa.ppost==0
set(gca,'xlim',[min( logpo2(ixx(1:nfilt0(i),i)) ) max( logpo2(ixx(1:nfilt0(i),i)) )])
end
if mod(i,9)==0 || i==size(vvarvecm,1)
if mod(i,9)==0 || i==length(vvarvecm)
if ~isoctave
annotation('textbox', [0.1,0,0.35,0.05],'String', 'Log-posterior for BETTER R2','Color','Blue','horizontalalignment','center');
annotation('textbox', [0.55,0,0.35,0.05],'String', 'Log-posterior for WORSE R2', 'Color','Red','horizontalalignment','center');
@ -545,64 +529,50 @@ else
end
end
end
if options_.TeX
[pnames,pnames_tex]=get_LaTeX_parameter_names(M_,options_,estim_params_,bayestopt_);
param_names = char(pnames);
param_names_tex = char(pnames_tex);
param_names = pnames;
param_names_tex = pnames_tex;
else
[pnames]=get_LaTeX_parameter_names(M_,options_,estim_params_,bayestopt_);
param_names = char(pnames);
param_names_tex = [];
param_names = pnames;
param_names_tex = {};
end
skipline()
title_string='RMSE over the MC sample:';
data_mat=[min(rmse_MC)' max(rmse_MC)'];
headers=strvcat('Variable','min yr RMSE','max yr RMSE');
dyntable(options_,title_string,headers,vvarvecm,data_mat, 0, 15, 5);
headers={'Variable'; 'min yr RMSE'; 'max yr RMSE'};
dyntable(options_, title_string, headers, vvarvecm, data_mat, 0, 15, 5);
if options_.TeX
headers_tex=strvcat('\text{Variable}','\text{min yr RMSE}','\text{max yr RMSE}');
dyn_latex_table(M_,options_,title_string,'RMSE_MC',headers_tex,vvarvecm_tex,data_mat,0,15,5);
headers_tex = {'\text{Variable}'; '\text{min yr RMSE}'; '\text{max yr RMSE}'};
dyn_latex_table(M_, options_, title_string, 'RMSE_MC', headers_tex, vvarvecm_tex, data_mat, 0, 15, 5);
end
invar = find( std(rmse_MC)./mean(rmse_MC)<=0.0001 );
if ~isempty(invar)
skipline(2)
disp('RMSE is not varying significantly over the MC sample for the following variables:')
disp(vvarvecm(invar,:))
disp(vvarvecm{invar})
disp('These variables are excluded from SA')
disp('[Unless you treat these series as exogenous, there is something wrong in your estimation !]')
end
vvarvecm0=vvarvecm;
ivar = find( std(rmse_MC)./mean(rmse_MC)>0.0001 );
vvarvecm=vvarvecm(ivar,:);
rmse_MC=rmse_MC(:,ivar);
vvarvecm = vvarvecm(ivar);
rmse_MC = rmse_MC(:,ivar);
skipline()
% if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior,
disp(['Sample filtered the ',num2str(pfilt*100),'% best RMSE''s for each observed series ...' ])
% else
% disp(['Sample filtered the best RMSE''s smaller than RMSE at the posterior mean ...' ])
% end
% figure, boxplot(rmse_MC)
% set(gca,'xticklabel',vvarvecm)
% saveas(gcf,[fname_,'_SA_RMSE'])
skipline(2)
disp('RMSE ranges after filtering:')
title_string='RMSE ranges after filtering:';
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}');
headers = {'Variable'; 'min'; 'max'; 'min'; 'max'; 'posterior mode'};
headers_tex = {'\text{Variable}'; '\text{min}'; '\text{max}'; '\text{min}'; '\text{max}'; '\text{posterior mode}'};
else
headers=strvcat('Variable','min','max','min','max','posterior mean');
headers_tex=strvcat('\text{Variable}','\text{min}','\text{max}','\text{min}','\text{max}','\text{posterior mean}');
headers = {'Variable'; 'min'; 'max'; 'min'; 'max'; 'posterior mean'};
headers_tex = {'\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)
data_mat=NaN(length(vvarvecm),5);
for j = 1:length(vvarvecm)
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)) ...
@ -610,10 +580,10 @@ else
rmse_txt(j)];
end
%get formatting for additional header line
val_width=15;
val_precis=5;
label_width = max(size(deblank(char(headers(1,:),vvarvecm)),2)+2,0);
label_format_leftbound = sprintf('%%-%ds',label_width);
val_width = 15;
val_precis = 5;
label_width = max(cellofchararraymaxlength(vertcat(headers{1}, vvarvecm))+2, 0);
label_format_leftbound = sprintf('%%-%ds', label_width);
if all(~isfinite(data_mat))
values_length = 4;
else
@ -622,61 +592,55 @@ else
if any(data_mat) < 0 %add one character for minus sign
values_length = values_length+1;
end
headers_length = max(size(deblank(headers(2:end,:)),2));
headers_length = cellofchararraymaxlength(headers(2:end));
if ~isempty(val_width)
val_width = max(max(headers_length,values_length)+2,val_width);
val_width = max(max(headers_length,values_length)+2, val_width);
else
val_width = max(headers_length,values_length)+2;
val_width = max(headers_length, values_length)+2;
end
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
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);
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
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}\\']};
end
dyn_latex_table(M_,options_,title_string,'RMSE_ranges_after_filtering',headers_tex,vvarvecm_tex,data_mat,0,val_width,val_precis,optional_header);
dyn_latex_table(M_, options_, title_string, 'RMSE_ranges_after_filtering', headers_tex, vvarvecm_tex, data_mat, 0, val_width, val_precis, optional_header);
end
%%%%% R2 table
% R2 table
vvarvecm=vvarvecm0;
skipline()
title_string='R2 over the MC sample:';
data_mat=[min(r2_MC)' max(r2_MC)'];
headers=strvcat('Variable','min yr R2','max yr R2');
dyntable(options_,title_string,headers,vvarvecm,data_mat, 0, 15, 5);
headers = {'Variable'; 'min yr R2'; 'max yr R2'};
dyntable(options_, title_string, headers, vvarvecm, data_mat, 0, 15, 5);
if options_.TeX
headers_tex=strvcat('\text{Variable}','\text{min yr R2}','\text{max yr R2}');
dyn_latex_table(M_,options_,title_string,'R2_MC',headers_tex,vvarvecm_tex,data_mat,0,15,5);
headers_tex = {'\text{Variable}'; '\text{min yr R2}'; '\text{max yr R2}'};
dyn_latex_table(M_, options_, title_string, 'R2_MC', headers_tex, vvarvecm_tex, data_mat, 0, 15, 5);
end
r2_MC=r2_MC(:,ivar);
vvarvecm=vvarvecm(ivar,:);
vvarvecm=vvarvecm(ivar);
skipline()
disp(['Sample filtered the ',num2str(pfilt*100),'% best R2''s for each observed series ...' ])
skipline()
disp('R2 ranges after filtering:')
title_string='R2 ranges after filtering:';
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}');
headers = {'Variable'; 'min'; 'max'; 'min'; 'max'; 'posterior mode'};
headers_tex = {'\text{Variable}'; '\text{min}'; '\text{max}'; '\text{min}'; '\text{max}'; '\text{posterior mode}'};
else
headers=strvcat('Variable','min','max','min','max','posterior mean');
headers_tex=strvcat('\text{Variable}','\text{min}','\text{max}','\text{min}','\text{max}','\text{posterior mean}');
headers = {'Variable'; 'min'; 'max'; 'min'; 'max'; 'posterior mean'};
headers_tex = {'\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)
data_mat=NaN(length(vvarvecm),5);
for j = 1:length(vvarvecm)
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)) ...
@ -684,10 +648,10 @@ else
r2_txt(j)];
end
%get formatting for additional header line
val_width=15;
val_precis=5;
label_width = max(size(deblank(char(headers(1,:),vvarvecm)),2)+2,0);
label_format_leftbound = sprintf('%%-%ds',label_width);
val_width = 15;
val_precis = 5;
label_width = max(cellofchararraymaxlength(vertcat(headers{1}, vvarvecm))+2, 0);
label_format_leftbound = sprintf('%%-%ds', label_width);
if all(~isfinite(data_mat))
values_length = 4;
else
@ -696,35 +660,32 @@ else
if any(data_mat) < 0 %add one character for minus sign
values_length = values_length+1;
end
headers_length = max(size(deblank(headers(2:end,:)),2));
headers_length = cellofchararraymaxlength(headers(2:end));
if ~isempty(val_width)
val_width = max(max(headers_length,values_length)+2,val_width);
val_width = max(max(headers_length, values_length)+2, val_width);
else
val_width = max(headers_length,values_length)+2;
val_width = max(headers_length, values_length)+2;
end
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
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%');
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');
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);
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
optional_header={[' & \multicolumn{2}{c}{best ',num2str(pfilt*100),' filtered} & \multicolumn{2}{c}{remaining 90\%}\\']};
if ~options_.opt_gsa.ppost && 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}\\']};
optional_header = {[' & \multicolumn{2}{c}{best filtered} & \multicolumn{2}{c}{remaining}\\']};
end
dyn_latex_table(M_,options_,title_string,'R2_ranges_after_filtering',headers_tex,vvarvecm_tex,data_mat,0,val_width,val_precis,optional_header);
dyn_latex_table(M_, options_, title_string, 'R2_ranges_after_filtering', headers_tex, vvarvecm_tex, data_mat, 0, val_width, val_precis, optional_header);
end
%%%% R2 table
SP=zeros(npar+nshock,size(vvarvecm,1));
for j=1:size(vvarvecm,1)
% R2 table
SP = zeros(npar+nshock, length(vvarvecm));
for j = 1:length(vvarvecm)
ns=find(PP(:,j)<alpha);
SP(ns,j)=ones(size(ns));
SS(:,j)=SS(:,j).*SP(:,j);
@ -733,33 +694,24 @@ else
for j=1:npar+nshock %estim_params_.np,
nsp(j)=length(find(SP(j,:)));
end
snam0=param_names(find(nsp==0),:);
snam1=param_names(find(nsp==1),:);
snam2=param_names(find(nsp>1),:);
snam=param_names(find(nsp>0),:);
% snam0=bayestopt_.name(find(nsp==0));
% snam1=bayestopt_.name(find(nsp==1));
% snam2=bayestopt_.name(find(nsp>1));
% snam=bayestopt_.name(find(nsp>0));
snam0=param_names(find(nsp==0));
snam1=param_names(find(nsp==1));
snam2=param_names(find(nsp>1));
snam=param_names(find(nsp>0));
nsnam=(find(nsp>1));
skipline(2)
disp('These parameters do not affect significantly the fit of ANY observed series:')
disp(snam0)
disp(char(snam0))
skipline()
disp('These parameters affect ONE single observed series:')
disp(snam1)
disp(char(snam1))
skipline()
disp('These parameters affect MORE THAN ONE observed series: trade off exists!')
disp(snam2)
%pnam=bayestopt_.name(end-estim_params_.np+1:end);
disp(char(snam2))
pnam=bayestopt_.name;
% plot trade-offs
if ~options_.nograph
a00=jet(size(vvarvecm,1));
a00=jet(length(vvarvecm));
if options_.opt_gsa.ppost
temp_name='RMSE Posterior Tradeoffs:';
atitle='RMSE Posterior Map:';
@ -783,33 +735,30 @@ else
options_mcf.param_names_tex = param_names_tex;
options_mcf.fname_ = fname_;
options_mcf.OutputDirectoryName = OutDir;
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,:))];
options_mcf.nobeha_title = ['worse fit of ' deblank(vvarvecm(iy,:))];
options_mcf.title = ['the fit of ' deblank(vvarvecm(iy,:))];
for iy = 1:length(vvarvecm)
options_mcf.amcf_name = [asname '_' vvarvecm{iy} '_map' ];
options_mcf.amcf_title = [atitle ' ' vvarvecm{iy}];
options_mcf.beha_title = ['better fit of ' vvarvecm{iy}];
options_mcf.nobeha_title = ['worse fit of ' vvarvecm{iy}];
options_mcf.title = ['the fit of ' 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:length(vvarvecm)
ipar = find(any(squeeze(PPV(iy,:,:))<alpha));
for ix=1:ceil(length(ipar)/5)
hh = dyn_figure(options_.nodisplay,'name',[temp_name,' observed variable ',deblank(vvarvecm(iy,:))]);
hh = dyn_figure(options_.nodisplay,'name',[temp_name,' observed variable ', vvarvecm{iy}]);
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)
%h0=cumplot(x(ixx(1:nfilt,np(i)),nsnam(j)+nshock));
% h0=cumplot(x(ixx(1:nfilt0(np(i)),np(i)),nsnam(j)));
for i = 1:length(vvarvecm)
if any(iobs==i) || i==iy
h0=cumplot(x(ixx(1:nfilt0(i),i),ipar(j)));
if ~isoctave
hcmenu = uicontextmenu;
uimenu(hcmenu,'Label',deblank(vvarvecm(i,:)));
uimenu(hcmenu,'Label',vvarvecm{i});
set(h0,'uicontextmenu',hcmenu)
end
else
@ -818,7 +767,6 @@ else
set(h0,'color',a00(i,:),'linewidth',2)
end
ydum=get(gca,'ylim');
%xdum=xparam1(nshock+nsnam(j));
if exist('xparam1')
xdum=xparam1(ipar(j));
h1=plot([xdum xdum],ydum);
@ -827,65 +775,55 @@ else
xlabel('')
title([pnam{ipar(j)}],'interpreter','none')
end
%subplot(3,2,6)
if isoctave
legend(char('base',vvarvecm),'location','eastoutside');
legend(vertcat('base',vvarvecm),'location','eastoutside');
else
h0=legend(char('base',vvarvecm));
h0=legend(vertcat('base',vvarvecm));
set(h0,'fontsize',6,'position',[0.7 0.1 0.2 0.3],'interpreter','none');
end
%h0=legend({'base',vnam{np}}',0);
%set(findobj(get(h0,'children'),'type','text'),'interpreter','none')
if options_.opt_gsa.ppost
dyn_saveas(hh,[ OutDir filesep fname_ '_rmse_post_' deblank(vvarvecm(iy,:)) '_' int2str(ix)],options_.nodisplay,options_.graph_format);
dyn_saveas(hh,[ OutDir filesep fname_ '_rmse_post_' vvarvecm{iy} '_' int2str(ix)],options_.nodisplay,options_.graph_format);
if options_.TeX
create_TeX_loader(options_,[ OutDir filesep fname_ '_rmse_post_' deblank(vvarvecm(iy,:)) '_' int2str(ix)],ix,[temp_name,' observed variable $',deblank(vvarvecm_tex(iy,:)) '$'],['rmse_post_' deblank(vvarvecm(iy,:))],1)
create_TeX_loader(options_,[ OutDir filesep fname_ '_rmse_post_' vvarvecm{iy} '_' int2str(ix)],ix,[temp_name,' observed variable $',vvarvecm_tex{iy} '$'],['rmse_post_' vvarvecm{iy}],1)
end
else
if options_.opt_gsa.pprior
dyn_saveas(hh,[OutDir filesep fname_ '_rmse_prior_' deblank(vvarvecm(iy,:)) '_' int2str(ix) ],options_.nodisplay,options_.graph_format);
dyn_saveas(hh,[OutDir filesep fname_ '_rmse_prior_' vvarvecm{iy} '_' int2str(ix) ],options_.nodisplay,options_.graph_format);
if options_.TeX
create_TeX_loader(options_,[OutDir filesep fname_ '_rmse_prior_' deblank(vvarvecm(iy,:)) '_' int2str(ix) ],ix,[temp_name,' observed variable $',deblank(vvarvecm_tex(iy,:)) '$'],['rmse_prior_' deblank(vvarvecm(iy,:))],1)
create_TeX_loader(options_,[OutDir filesep fname_ '_rmse_prior_' vvarvecm{iy} '_' int2str(ix) ],ix,[temp_name,' observed variable $',vvarvecm_tex{iy} '$'],['rmse_prior_' vvarvecm{iy}],1)
end
else
dyn_saveas(hh,[OutDir filesep fname_ '_rmse_mc_' deblank(vvarvecm(iy,:)) '_' int2str(ix)],options_.nodisplay,options_.graph_format);
dyn_saveas(hh,[OutDir filesep fname_ '_rmse_mc_' vvarvecm{iy} '_' int2str(ix)],options_.nodisplay,options_.graph_format);
if options_.TeX
create_TeX_loader(options_,[OutDir filesep fname_ '_rmse_mc_' deblank(vvarvecm(iy,:)) '_' int2str(ix)],ix,[temp_name,' observed variable $',deblank(vvarvecm_tex(iy,:)) '$'],['rmse_mc_' deblank(vvarvecm(iy,:))],1)
create_TeX_loader(options_,[OutDir filesep fname_ '_rmse_mc_' vvarvecm{iy} '_' int2str(ix)],ix,[temp_name,' observed variable $',vvarvecm_tex{iy} '$'],['rmse_mc_' vvarvecm{iy}],1)
end
end
end
end
end
% now I plot by individual parameters
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)
subplot(2,3,j-5*(ix-1))
%h0=cumplot(x(:,nsnam(j)+nshock));
h0=cumplot(x(:,nsnam(j)));
set(h0,'color',[0 0 0])
hold on,
npx=find(SP(nsnam(j),:)==0);
%a0=jet(nsp(nsnam(j)));
% a0=a00(np,:);
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)));
for i = 1:length(vvarvecm)
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)));
if ~isoctave
hcmenu = uicontextmenu;
uimenu(hcmenu,'Label',deblank(vvarvecm(i,:)));
uimenu(hcmenu,'Label', vvarvecm{i});
set(h0,'uicontextmenu',hcmenu)
end
end
set(h0,'color',a00(i,:),'linewidth',2)
end
ydum=get(gca,'ylim');
%xdum=xparam1(nshock+nsnam(j));
if exist('xparam1')
xdum=xparam1(nsnam(j));
h1=plot([xdum xdum],ydum);
@ -896,13 +834,11 @@ else
end
%subplot(3,2,6)
if isoctave
legend(char('base',vvarvecm),'location','eastoutside');
legend(vertcat('base',vvarvecm),'location','eastoutside');
else
h0=legend(char('base',vvarvecm));
h0=legend(vertcat('base',vvarvecm));
set(h0,'fontsize',6,'position',[0.7 0.1 0.2 0.3],'interpreter','none');
end
%h0=legend({'base',vnam{np}}',0);
%set(findobj(get(h0,'children'),'type','text'),'interpreter','none')
if options_.opt_gsa.ppost
dyn_saveas(hh,[ OutDir filesep fname_ '_rmse_post_params_' int2str(ix)],options_.nodisplay,options_.graph_format);
if options_.TeX
@ -923,66 +859,6 @@ else
end
end
end
% for j=1:size(SP,2),
% nsx(j)=length(find(SP(:,j)));
% end
% skipline(2)
% disp('Sensitivity table (significance and direction):')
% vav=char(zeros(1, size(param_names,2)+3 ));
% ibl = 12-size(vvarvecm,2);
% for j=1:size(vvarvecm,1),
% vav = [vav, char(zeros(1,ibl)),vvarvecm(j,:)];
% end
% disp(vav)
% for j=1:npar+nshock, %estim_params_.np,
% %disp([param_names(j,:), sprintf('%8.5g',SP(j,:))])
% disp([param_names(j,:),' ', sprintf('%12.3g',PP(j,:))])
% disp([char(zeros(1, size(param_names,2)+3 )),sprintf(' (%6g)',SS(j,:))])
% end
% skipline()
% disp('Starting bivariate analysis:')
%
% for i=1:size(vvarvecm,1)
% if options_.opt_gsa.ppost
% fnam = ['rmse_post_',deblank(vvarvecm(i,:))];
% else
% if options_.opt_gsa.pprior
% fnam = ['rmse_prior_',deblank(vvarvecm(i,:))];
% else
% fnam = ['rmse_mc_',deblank(vvarvecm(i,:))];
% end
% end
% stab_map_2(x(ixx(1:nfilt0(i),i),:),alpha2,pvalue,fnam, OutDir,[],[temp_name ' observed variable ' deblank(vvarvecm(i,:))]);
%
% % [pc,latent,explained] = pcacov(c0);
% % %figure, bar([explained cumsum(explained)])
% % ifig=0;
% % j2=0;
% % for j=1:npar+nshock,
% % i2=find(abs(pc(:,j))>alphaPC);
% % if ~isempty(i2),
% % j2=j2+1;
% % if mod(j2,12)==1,
% % ifig=ifig+1;
% % figure('name',['PCA of the filtered sample ',deblank(vvarvecm(i,:)),' ',num2str(ifig)]),
% % end
% % subplot(3,4,j2-(ifig-1)*12)
% % bar(pc(i2,j)),
% % set(gca,'xticklabel',bayestopt_.name(i2)),
% % set(gca,'xtick',[1:length(i2)])
% % title(['PC ',num2str(j),'. Explained ',num2str(explained(j)),'%'])
% % end
% % if (mod(j2,12)==0 | j==(npar+nshock)) & j2,
% % saveas(gcf,[fname_,'_SA_PCA_',deblank(vvarvecm(i,:)),'_',int2str(ifig)])
% % end
% % end
% % close all
% end
end
function []=create_TeX_loader(options_,figpath,label_number,caption,label_name,scale_factor)

12
matlab/gsa/map_calibration.m
View File

@ -5,7 +5,7 @@ function map_calibration(OutputDirectoryName, Model, DynareOptions, DynareResult
% marco.ratto@ec.europa.eu
% Copyright (C) 2014-2016 European Commission
% Copyright (C) 2014-2017 Dynare Team
% Copyright (C) 2014-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -48,9 +48,9 @@ init = ~DynareOptions.opt_gsa.load_stab;
options_mcf.pvalue_ks = DynareOptions.opt_gsa.pvalue_ks;
options_mcf.pvalue_corr = DynareOptions.opt_gsa.pvalue_corr;
options_mcf.alpha2 = DynareOptions.opt_gsa.alpha2_stab;
options_mcf.param_names = char(pnames);
options_mcf.param_names = pnames;
if DynareOptions.TeX
options_mcf.param_names_tex=char(pnames_tex);
options_mcf.param_names_tex = pnames_tex;
end
options_mcf.fname_ = fname_;
options_mcf.OutputDirectoryName = OutputDirectoryName;
@ -375,11 +375,11 @@ if ~isempty(indx_moment)
name{jj,1} = param_name_temp;
end
end
options_mcf.param_names = char(name);
options_mcf.param_names = name;
if DynareOptions.TeX
options_mcf.param_names_tex = char(name_tex);
options_mcf.param_names_tex = name_tex;
end
options_mcf.param_names = char(BayesInfo.name);
options_mcf.param_names = BayesInfo.name;
all_moment_couples = cellstr([char(endo_prior_restrictions.moment(:,1)) char(endo_prior_restrictions.moment(:,2))]);
moment_couples = unique(all_moment_couples);
nbr_moment_couples = size(moment_couples,1);

6
matlab/gsa/map_ident_.m
View File

@ -5,7 +5,7 @@ function map_ident_(OutputDirectoryName,opt_gsa)
% marco.ratto@ec.europa.eu
% Copyright (C) 2012-2016 European Commission
% Copyright (C) 2012-2017 Dynare Team
% Copyright (C) 2012-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -37,7 +37,7 @@ else
gsa_flag=-2;
end
pnames = M_.param_names(estim_params_.param_vals(:,1),:);
pnames = M_.param_names(estim_params_.param_vals(:,1));
if opt_gsa.pprior
filetoload=[OutputDirectoryName '/' fname_ '_prior'];
@ -106,7 +106,7 @@ if opt_gsa.load_ident_files==0
end
xlabel(' ')
ylabel(' ')
title(M_.exo_names(j,:),'interpreter','none')
title(M_.exo_names{j},'interpreter','none')
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))

4
matlab/gsa/mc_moments.m
View File

@ -1,6 +1,6 @@
function [vdec, cc, ac] = mc_moments(mm, ss, dr)
% Copyright (C) 2012-2017 Dynare Team
% Copyright (C) 2012-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -20,7 +20,7 @@ function [vdec, cc, ac] = mc_moments(mm, ss, dr)
global options_ M_ estim_params_ oo_
[nr1, nc1, nsam] = size(mm);
nobs=size(options_.varobs,2);
nobs=length(options_.varobs);
disp('Computing theoretical moments ...')
h = dyn_waitbar(0,'Theoretical moments ...');
vdec = zeros(nobs,M_.exo_nbr,nsam);

10
matlab/gsa/mcf_analysis.m
View File

@ -6,7 +6,7 @@ function indmcf = mcf_analysis(lpmat, ibeha, inobeha, options_mcf, DynareOptions
%
% Copyright (C) 2014 European Commission
% Copyright (C) 2016-2017 Dynare Team
% Copyright (C) 2016-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -53,13 +53,13 @@ indmcf=find(proba<pvalue_ks);
indmcf = indmcf(jtmp);
if ~isempty(indmcf)
skipline()
headers=char('Parameter','d-stat','p-value');
labels=char(param_names(indmcf,:));
headers = {'Parameter','d-stat','p-value'};
labels = param_names(indmcf);
data_mat=[dproba(indmcf)' proba(indmcf)'];
options_temp.noprint=0;
dyntable(options_temp,['Smirnov statistics in driving ', title],headers,labels,data_mat,size(labels,2)+2,16,3);
if DynareOptions.TeX
labels_TeX=param_names_tex(indmcf,:);
labels_TeX=param_names_tex(indmcf);
M_temp.dname=OutputDirectoryName ;
M_temp.fname=fname_;
dyn_latex_table(M_temp,options_temp,['Smirnov statistics in driving ', strrep(title,'_','\\_')],amcf_name,headers,labels_TeX,data_mat,size(labels,2)+2,16,6);
@ -78,7 +78,7 @@ if ~isempty(indmcf) && ~DynareOptions.nograph
skipline()
xx=[];
if ~ isempty(xparam1), xx=xparam1(indmcf); end
scatter_mcf(lpmat(ibeha,indmcf),lpmat(inobeha,indmcf), param_names(indmcf,:), ...
scatter_mcf(lpmat(ibeha,indmcf),lpmat(inobeha,indmcf), param_names(indmcf), ...
'.', [fname_,'_',amcf_name], OutputDirectoryName, amcf_title,xx, DynareOptions, ...
beha_title, nobeha_title)
end

28
matlab/gsa/redform_map.m
View File

@ -16,7 +16,7 @@ function redform_map(dirname,options_gsa_)
% marco.ratto@ec.europa.eu
% Copyright (C) 2012-2016 European Commission
% Copyright (C) 2012-2017 Dynare Team
% Copyright (C) 2012-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -86,9 +86,9 @@ end
options_mcf.pvalue_ks = options_gsa_.ksstat_redform;
options_mcf.pvalue_corr = options_gsa_.alpha2_redform;
options_mcf.alpha2 = options_gsa_.alpha2_redform;
options_mcf.param_names = char(pnames);
options_mcf.param_names = pnames;
if options_.TeX
options_mcf.param_names_tex=char(pnames_tex);
options_mcf.param_names_tex = pnames_tex;
end
options_mcf.fname_ = M_.fname;
options_mcf.OutputDirectoryName = adir;
@ -147,14 +147,14 @@ nsok = length(find(M_.lead_lag_incidence(M_.maximum_lag,:)));
lpmat=[];
lpmat0=[];
js=0;
for j=1:size(anamendo,1)
namendo=deblank(anamendo(j,:));
iendo=strmatch(namendo,M_.endo_names(oo_.dr.order_var,:),'exact');
ifig=0;
iplo=0;
for jx=1:size(anamexo,1)
namexo=deblank(anamexo(jx,:));
iexo=strmatch(namexo,M_.exo_names,'exact');
for j = 1:length(anamendo)
namendo = anamendo{j};
iendo = strmatch(namendo, M_.endo_names(oo_.dr.order_var), 'exact');
ifig = 0;
iplo = 0;
for jx = 1:length(anamexo)
namexo = anamexo{jx};
iexo=strmatch(namexo, M_.exo_names, 'exact');
skipline()
disp(['[', namendo,' vs ',namexo,']'])
@ -289,9 +289,9 @@ for j=1:size(anamendo,1)
end
ifig=0;
iplo=0;
for je=1:size(anamlagendo,1)
namlagendo=deblank(anamlagendo(je,:));
ilagendo=strmatch(namlagendo,M_.endo_names(oo_.dr.order_var(M_.nstatic+1:M_.nstatic+nsok),:),'exact');
for je=1:length(anamlagendo)
namlagendo = anamlagendo{je};
ilagendo=strmatch(namlagendo, M_.endo_names(oo_.dr.order_var(M_.nstatic+1:M_.nstatic+nsok)), 'exact');
skipline()
disp(['[', namendo,' vs lagged ',namlagendo,']'])

37
matlab/gsa/redform_screen.m
View File

@ -11,7 +11,7 @@ function redform_screen(dirname, options_gsa_)
% marco.ratto@ec.europa.eu
% Copyright (C) 2012-2016 European Commission
% Copyright (C) 2012-2017 Dynare Team
% Copyright (C) 2012-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -38,7 +38,7 @@ anamexo = options_gsa_.namexo;
iload = options_gsa_.load_redform;
nliv = options_gsa_.morris_nliv;
pnames = M_.param_names(estim_params_.param_vals(:,1),:);
pnames = M_.param_names(estim_params_.param_vals(:,1));
if nargin==0
dirname='';
end
@ -54,36 +54,33 @@ nsok = length(find(M_.lead_lag_incidence(M_.maximum_lag,:)));
js=0;
for j=1:size(anamendo,1)
namendo=deblank(anamendo(j,:));
iendo=strmatch(namendo,M_.endo_names(oo_.dr.order_var,:),'exact');
namendo = deblank(anamendo(j,:));
iendo = strmatch(namendo, M_.endo_names(oo_.dr.order_var), 'exact');
iplo=0;
ifig=0;
for jx=1:size(anamexo,1)
namexo=deblank(anamexo(jx,:));
iexo=strmatch(namexo,M_.exo_names,'exact');
namexo = deblank(anamexo(jx,:));
iexo = strmatch(namexo, M_.exo_names, 'exact');
if ~isempty(iexo)
y0=teff(T(iendo,iexo+nspred,:),kn,istable);
y0=teff(T(iendo,iexo+nspred,:), kn, istable);
if ~isempty(y0)
if mod(iplo,9)==0
ifig=ifig+1;
hh=dyn_figure(options_.nodisplay,'name',[namendo,' vs. shocks ',int2str(ifig)]);
iplo=0;
ifig = ifig+1;
hh = dyn_figure(options_.nodisplay, 'name', [namendo,[' vs. shocks '], int2str(ifig)]);
iplo = 0;
end
iplo=iplo+1;
js=js+1;
subplot(3,3,iplo),
[SAmeas, SAMorris] = Morris_Measure_Groups(np+nshock, [lpmat0 lpmat], y0,nliv);
iplo = iplo+1;
js = js+1;
subplot(3, 3, iplo)
[SAmeas, SAMorris] = Morris_Measure_Groups(np+nshock, [lpmat0 lpmat], y0, nliv);
SAM = squeeze(SAMorris(nshock+1:end,1));
SA(:,js)=SAM./(max(SAM)+eps);
SA(:,js) = SAM./(max(SAM)+eps);
[saso, iso] = sort(-SA(:,js));
bar(SA(iso(1:min(np,10)),js))
%set(gca,'xticklabel',pnames(iso(1:min(np,10)),:),'fontsize',8)
set(gca,'xticklabel',' ','fontsize',10)
set(gca,'xlim',[0.5 10.5])
for ip=1:min(np,10)
text(ip,-0.02,deblank(pnames(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
text(ip,-0.02,pnames(iso(ip)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
end
title([namendo,' vs. ',namexo],'interpreter','none')
if iplo==9
@ -103,7 +100,7 @@ for j=1:size(anamendo,1)
ifig=0;
for je=1:size(anamlagendo,1)
namlagendo=deblank(anamlagendo(je,:));
ilagendo=strmatch(namlagendo,M_.endo_names(oo_.dr.order_var(M_.nstatic+1:M_.nstatic+nsok),:),'exact');
ilagendo=strmatch(namlagendo, M_.endo_names(oo_.dr.order_var(M_.nstatic+1:M_.nstatic+nsok)), 'exact');
if ~isempty(ilagendo)
y0=teff(T(iendo,ilagendo,:),kn,istable);

6
matlab/gsa/scatter_callback.m
View File

@ -6,7 +6,7 @@ function scatter_callback(K, type)
%
% Copyright (C) 2017 European Commission
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2018 Dynare Team
%
% This file is part of Dynare.
%
@ -34,9 +34,7 @@ xparam1=x(K,:)';
switch type
case 'save'
save(['my_params_' int2str(K)],'xparam1')
case 'eval'
disp('Evaluating smoother ...')
[oo_, M_]=evaluate_smoother(xparam1,M_.endo_names,M_,oo_,options_,bayestopt_,estim_params_);
% [rmse, lnam, r2,vv] = plot_fit(obsname{:});
[oo_, M_]=evaluate_smoother(xparam1, M_.endo_names, M_, oo_, options_, bayestopt_, estim_params_);
end

10
matlab/gsa/stab_map_.m
View File

@ -35,7 +35,7 @@ function x0 = stab_map_(OutputDirectoryName,opt_gsa)
% marco.ratto@ec.europa.eu
% Copyright (C) 2012-2016 European Commission
% Copyright (C) 2012-2017 Dynare Team
% Copyright (C) 2012-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -130,9 +130,9 @@ for jj=1:np
end
end
if options_.TeX
options_mcf.param_names_tex=char(name_tex);
options_mcf.param_names_tex = name_tex;
end
options_mcf.param_names = char(name);
options_mcf.param_names = name;
options_mcf.fname_ = fname_;
options_mcf.OutputDirectoryName = OutputDirectoryName;
@ -663,9 +663,9 @@ if length(iunstable)>0 || length(iwrong)>0
end
end
if options_.TeX
options_mcf.param_names_tex = char(name_tex);
options_mcf.param_names_tex = name_tex;
end
options_mcf.param_names = char(name);
options_mcf.param_names = name;
options_mcf.amcf_name = acalibname;
options_mcf.amcf_title = acalibtitle;
options_mcf.beha_title = 'prior IRF/moment calibration';

8
matlab/gsa/stab_map_2.m
View File

@ -6,7 +6,7 @@ function indcorr = stab_map_2(x,alpha2, pvalue_crit, fnam, dirname,xparam1,figti
% marco.ratto@ec.europa.eu
% Copyright (C) 2011-2016 European Commission
% Copyright (C) 2011-2017 Dynare Team
% Copyright (C) 2011-2018 Dynare Team
% This file is part of Dynare.
%
% Dynare is free software: you can redistribute it and/or modify
@ -183,10 +183,10 @@ end
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');
dyntable(options_,title_string,headers,char(name),data_mat, 0, 7, 3);
headers={'Parameters'; 'corrcoef'};
dyntable(options_,title_string,headers, name, data_mat, 0, 7, 3);
if options_.TeX
dyn_latex_table(M_,options_,title_string_tex,fig_nam_tex_table,headers,char(name_tex),data_mat,0,7,3);
dyn_latex_table(M_, options_, title_string_tex, fig_nam_tex_table, headers, name_tex, data_mat, 0, 7, 3);
end
end
%close all

6
matlab/gsa/th_moments.m
View File

@ -1,7 +1,7 @@
function [vdec, corr, autocorr, z, zz] = th_moments(dr,var_list)
% [vdec, corr, autocorr, z, zz] = th_moments(dr,var_list)
% Copyright (C) 2012-2017 Dynare Team
% Copyright (C) 2012-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -20,14 +20,14 @@ function [vdec, corr, autocorr, z, zz] = th_moments(dr,var_list)
global M_ oo_ options_
nvar = size(var_list,2);
nvar = length(var_list);
if nvar == 0
nvar = length(dr.order_var);
ivar = [1:nvar]';
else
ivar=zeros(nvar,1);
for i=1:nvar
i_tmp = strmatch(var_list{:,i},M_.endo_names,'exact');
i_tmp = strmatch(var_list{i}, M_.endo_names, 'exact');
if isempty(i_tmp)
error(['One of the variables specified does not exist']) ;
else

6
matlab/histvalf.m
View File

@ -1,6 +1,6 @@
function histvalf(fname)
% Copyright (C) 2014-2017 Dynare Team
% Copyright (C) 2014-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -61,10 +61,10 @@ for i = 1:length(outvars)
end
if M_.aux_vars(i).type == 1
% Endogenous
orig_var = deblank(M_.endo_names(M_.aux_vars(i).orig_index, :));
orig_var = M_.endo_names{M_.aux_vars(i).orig_index};
else
% Exogenous
orig_var = deblank(M_.exo_names(M_.aux_vars(i).orig_index, :));
orig_var = M_.exo_names{M_.aux_vars(i).orig_index};
end
if strcmp(orig_var, ov) && M_.aux_vars(i).orig_lead_lag == lead_lag
j = M_.aux_vars(i).endo_index;

10
matlab/homotopy2.m
View File

@ -25,7 +25,7 @@ function homotopy2(values, step_nbr)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2008-2017 Dynare Team
% Copyright (C) 2008-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -82,11 +82,11 @@ end
for i = 1:nv
switch values(i,1)
case 1
varname = M_.exo_names(values(i,2), :);
varname = M_.exo_names{values(i,2)};
case 2
varname = M_.exo_det_names(values(i,2), :);
varname = M_.exo_det_names{values(i,2)};
case 4
varname = M_.param_names(values(i,2), :);
varname = M_.param_names{values(i,2)};
end
for v = oldvalues(i):(values(i,4)-oldvalues(i))/step_nbr:values(i,4)
switch values(i,1)
@ -98,7 +98,7 @@ for i = 1:nv
M_.params(values(i,2)) = v;
end
disp([ 'HOMOTOPY mode 2: lauching solver with ' deblank(varname) ' = ' num2str(v) ' ...'])
disp([ 'HOMOTOPY mode 2: lauching solver with ' varname ' = ' num2str(v) ' ...'])
oo_.steady_state = steady_(M_,options_,oo_);
end

6
matlab/ident_bruteforce.m
View File

@ -17,7 +17,7 @@ function [pars, cosnJ] = ident_bruteforce(J,n,TeX, pnames_TeX,tittxt)
% pars : cell array with groupf of params for each column of J for 1 to n
% cosnJ : the cosn of each column with the selected group of columns
% Copyright (C) 2009-2017 Dynare Team
% Copyright (C) 2009-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -105,13 +105,13 @@ for ll = 1:n
plist='';
for ii=1:ll
if ~isnan(pars{i,ll}(ii))
plist = [plist ' $' pnames_TeX(pars{i,ll}(ii),:) '\;\; $ '];
plist = [plist ' $' pnames_TeX{pars{i,ll}(ii)} '\;\; $ '];
else
plist = [plist ' ---- '];
end
end
fprintf(fidTeX,'$%s$ & [%s] & %7.3f \\\\ \n',...
pnames_TeX(i,:),...
pnames_TeX{i},...
plist,...
cosnJ(i,ll));
end

20
matlab/imcforecast.m
View File

@ -26,7 +26,7 @@ function imcforecast(constrained_paths, constrained_vars, options_cond_fcst)
% [1] Results are stored in a structure which is saved in a mat file called conditional_forecasts.mat.
% [2] Use the function plot_icforecast to plot the results.
% Copyright (C) 2006-2017 Dynare Team
% Copyright (C) 2006-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -146,8 +146,8 @@ if estimated_model
end
% add trend to constant
for obs_iter=1:length(options_.varobs)
j = strmatch(options_.varobs{obs_iter},M_.endo_names,'exact');
constant(j,:) = constant(j,:)+trend_addition(obs_iter,:);
j = strmatch(options_.varobs{obs_iter}, M_.endo_names, 'exact');
constant(j,:) = constant(j,:) + trend_addition(obs_iter,:);
end
trend = constant(oo_.dr.order_var,:);
InitState(:,1) = atT(:,end);
@ -226,7 +226,7 @@ jdx = [];
for i = 1:n1
idx = [idx ; constrained_vars(i,:)];
% idx = [idx ; oo_.dr.inv_order_var(constrained_vars(i,:))];
jdx = [jdx ; strmatch(deblank(options_cond_fcst.controlled_varexo(i,:)),M_.exo_names,'exact')];
jdx = [jdx ; strmatch(options_cond_fcst.controlled_varexo{i},M_.exo_names,'exact')];
end
mv = zeros(n1,NumberOfStates);
mu = zeros(ExoSize,n2);
@ -265,15 +265,15 @@ forecasts.controlled_variables = constrained_vars;
forecasts.instruments = options_cond_fcst.controlled_varexo;
for i = 1:EndoSize
forecasts.cond.Mean.(deblank(M_.endo_names(oo_.dr.order_var(i),:)))= mFORCS1(i,:)';
forecasts.cond.Mean.(M_.endo_names{oo_.dr.order_var(i)}) = mFORCS1(i,:)';
tmp = sort(squeeze(FORCS1(i,:,:))');
forecasts.cond.ci.(deblank(M_.endo_names(oo_.dr.order_var(i),:))) = [tmp(t1,:)' ,tmp(t2,:)' ]';
forecasts.cond.ci.(M_.endo_names{oo_.dr.order_var(i)}) = [tmp(t1,:)' ,tmp(t2,:)' ]';
end
for i = 1:n1
forecasts.controlled_exo_variables.Mean.(deblank(options_cond_fcst.controlled_varexo(i,:))) = mFORCS1_shocks(i,:)';
forecasts.controlled_exo_variables.Mean.(options_cond_fcst.controlled_varexo{i}) = mFORCS1_shocks(i,:)';
tmp = sort(squeeze(FORCS1_shocks(i,:,:))');
forecasts.controlled_exo_variables.ci.(deblank(options_cond_fcst.controlled_varexo(i,:))) = [tmp(t1,:)' ,tmp(t2,:)' ]';
forecasts.controlled_exo_variables.ci.(options_cond_fcst.controlled_varexo{i}) = [tmp(t1,:)' ,tmp(t2,:)' ]';
end
clear FORCS1 mFORCS1_shocks;
@ -292,9 +292,9 @@ end
mFORCS2 = mean(FORCS2,3);
for i = 1:EndoSize
forecasts.uncond.Mean.(deblank(M_.endo_names(oo_.dr.order_var(i),:)))= mFORCS2(i,:)';
forecasts.uncond.Mean.(M_.endo_names{oo_.dr.order_var(i)})= mFORCS2(i,:)';
tmp = sort(squeeze(FORCS2(i,:,:))');
forecasts.uncond.ci.(deblank(M_.endo_names(oo_.dr.order_var(i),:))) = [tmp(t1,:)' ,tmp(t2,:)' ]';
forecasts.uncond.ci.(M_.endo_names{oo_.dr.order_var(i)}) = [tmp(t1,:)' ,tmp(t2,:)' ]';
end
forecasts.graph.title=graph_title;
forecasts.graph.fname=M_.fname;

8
matlab/init_plan.m
View File

@ -9,7 +9,7 @@ function plan = init_plan(date)
% plan [structure] Returns a structure containing a new forecast scenario
%
%
% Copyright (C) 2013-2017 Dynare Team
% Copyright (C) 2013-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -29,10 +29,8 @@ global M_
plan = struct();
plan.date = date;
plan.date_str = strings(date);
endo_names_length = size(M_.endo_names,2);
plan.endo_names = deblank(mat2cell(M_.endo_names(1:M_.orig_endo_nbr,:),ones(1,M_.orig_endo_nbr),endo_names_length));
exo_names_length = size(M_.exo_names,2);
plan.exo_names = deblank(mat2cell(M_.exo_names(1:M_.exo_nbr,:),ones(1,M_.exo_nbr),exo_names_length));
plan.endo_names = M_.endo_names(1:M_.orig_endo_nbr);
plan.exo_names = M_.exo_names(1:M_.exo_nbr);
plan.constrained_vars_ = [];
plan.constrained_paths_ = [];
plan.constrained_date_ = [];

28
matlab/initial_condition_decomposition.m
View File

@ -8,20 +8,20 @@ function oo_ = initial_condition_decomposition(M_,oo_,options_,varlist,bayestopt
% in the order of declaration, i.e. M_.endo_names.
%
% INPUTS
% M_: [structure] Definition of the model
% oo_: [structure] Storage of results
% options_: [structure] Options
% varlist: [char] List of variables
% bayestopt_: [structure] describing the priors
% estim_params_: [structure] characterizing parameters to be estimated
% M_: [structure] Definition of the model
% oo_: [structure] Storage of results
% options_: [structure] Options
% varlist: [cell of char array] List of variables
% bayestopt_: [structure] Description of the priors
% estim_params_: [structure] Estimated parameters
%
% OUTPUTS
% oo_: [structure] Storage of results
% oo_: [structure] Storage of results
%
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2017-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -46,12 +46,12 @@ options_.plot_shock_decomp.plot_init_date = options_.initial_condition_decomp.pl
options_.plot_shock_decomp.plot_end_date = options_.initial_condition_decomp.plot_end_date;
% indices of endogenous variables
if size(varlist,1) == 0
varlist = M_.endo_names(1:M_.orig_endo_nbr,:);
if isempty(varlist)
varlist = M_.endo_names(1:M_.orig_endo_nbr);
end
[i_var,nvar,index_uniques] = varlist_indices(varlist,M_.endo_names);
varlist=varlist(index_uniques,:);
[i_var, nvar, index_uniques] = varlist_indices(varlist, M_.endo_names);
varlist = varlist(index_uniques);
% number of variables
endo_nbr = M_.endo_nbr;
@ -89,7 +89,7 @@ if ~isfield(oo_,'initval_decomposition')
B = dr.ghu;
% initialization
gend = size(oo.SmoothedShocks.(deblank(M_.exo_names(1,:))),1); %+options_.forecast;
gend = length(oo.SmoothedShocks.(M_.exo_names{1})); %+options_.forecast;
z = zeros(endo_nbr,endo_nbr+2,gend);
z(:,end,:) = Smoothed_Variables_deviation_from_mean;
@ -128,5 +128,5 @@ M_.exo_nbr = M_.endo_nbr;
options_.plot_shock_decomp.screen_shocks=1;
options_.plot_shock_decomp.use_shock_groups = '';
options_.plot_shock_decomp.fig_names='initval';
plot_shock_decomposition(M_,oo,options_,varlist);
plot_shock_decomposition(M_, oo, options_, varlist);
% end

4
matlab/initial_estimation_checks.m
View File

@ -20,7 +20,7 @@ function DynareResults = initial_estimation_checks(objective_function,xparam1,Dy
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2017 Dynare Team
% Copyright (C) 2003-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -73,7 +73,7 @@ if isfield(EstimatedParameters,'param_vals') && ~isempty(EstimatedParameters.par
if ~isempty(changed_par_indices)
fprintf('\nThe steady state file internally changed the values of the following estimated parameters:\n')
disp(Model.param_names(EstimatedParameters.param_vals(changed_par_indices,1),:));
disp(char(Model.param_names(EstimatedParameters.param_vals(changed_par_indices,1))))
fprintf('This will override the parameter values drawn from the proposal density and may lead to wrong results.\n')
fprintf('Check whether this is really intended.\n')
warning('The steady state file internally changes the values of the estimated parameters.')

10
matlab/initialize_from_mode.m
View File

@ -14,7 +14,7 @@ function estim_params_ = initialize_from_mode(fname,M_,estim_params_)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2017 Dynare Team
% Copyright (C) 2003-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -44,7 +44,7 @@ corrx = estim_params_.corrx;
corrn = estim_params_.corrn;
for i=1:length(parameter_names)
name = parameter_names{i};
k1 = strmatch(name,param_names,'exact');
k1 = strmatch(name, param_names, 'exact');
if ~isempty(k1)
k2 = find(param_vals(:,1) == k1);
if ~isempty(k2)
@ -64,7 +64,7 @@ for i=1:length(parameter_names)
M_.Sigma_e(k1,k1) = xparam1(i)^2;
continue
end
k1 = strmatch(name,endo_names,'exact');
k1 = strmatch(name, endo_names, 'exact');
if ~isempty(k1)
k2 = find(var_endo(:,1) == k1);
if ~isempty(k2)
@ -85,8 +85,8 @@ for i=1:length(parameter_names)
M_.Sigma_e(k1a,k1) = M_.Sigma_e(k1,k1a);
continue
end
k1 = strmatch(name(1:k3-1),endo_names,'exact');
k1a = strmatch(name(k3+1:end),endo_names,'exact');
k1 = strmatch(name(1:k3-1), endo_names, 'exact');
k1a = strmatch(name(k3+1:end), endo_names, 'exact');
if ~isempty(k1) && ~isempty(k1a)
k2 = find(corrn(:,1) == k1 & corrn(:,2) == k1a);
if ~isempty(k2)

18
matlab/initvalf.m
View File

@ -13,7 +13,7 @@ function initvalf(fname_)
% All variables local to this function have an underscore appended to
% their name, to minimize clashes with model variables loaded by this function.
% Copyright (C) 2003-2017 Dynare Team
% Copyright (C) 2003-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -73,36 +73,36 @@ options_.initval_file = 1;
oo_.endo_simul = [];
oo_.exo_simul = [];
for i_=1:size(M_.endo_names,1)
for i_=1:length(M_.endo_names)
if series_ == 1
x_ = eval(M_.endo_names(i_,:));
x_ = eval(M_.endo_names{i_});
if size(x_,2)>size(x_,1) %oo_.endo_simul must be collection of row vectors
oo_.endo_simul = [oo_.endo_simul; x_];
else %transpose if column vector
oo_.endo_simul = [oo_.endo_simul; x_'];
end
else
k_ = strmatch(deblank(M_.endo_names(i_,:)),names_v_,'exact');
k_ = strmatch(M_.endo_names{i_}, names_v_, 'exact');
if isempty(k_)
error(['INITVAL_FILE: ' deblank(M_.endo_names(i_,:)) ' not found'])
error(['INITVAL_FILE: ' M_.endo_names{i_} ' not found'])
end
x_ = data_(:,k_);
oo_.endo_simul = [oo_.endo_simul; x_'];
end
end
for i_=1:size(M_.exo_names,1)
for i_=1:length(M_.exo_names)
if series_ == 1
x_ = eval(M_.exo_names(i_,:) );
x_ = eval(M_.exo_names{i_});
if size(x_,2)>size(x_,1) %oo_.endo_simul must be collection of row vectors
oo_.exo_simul = [oo_.exo_simul x_'];
else %if column vector
oo_.exo_simul = [oo_.exo_simul x_];
end
else
k_ = strmatch(deblank(M_.exo_names(i_,:)),names_v_,'exact');
k_ = strmatch(M_.exo_names{i_}, names_v_, 'exact');
if isempty(k_)
error(['INITVAL_FILE: ' deblank(M_.exo_names(i_,:)) ' not found'])
error(['INITVAL_FILE: ' M_.exo_names{i_} ' not found'])
end
x_ = data_(:,k_);
oo_.exo_simul = [oo_.exo_simul x_];

9
matlab/k_order_pert.m
View File

@ -1,7 +1,7 @@
function [dr,info] = k_order_pert(dr,M,options)
% Compute decision rules using the k-order DLL from Dynare++
% Copyright (C) 2009-2017 Dynare Team
% Copyright (C) 2009-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -20,7 +20,12 @@ function [dr,info] = k_order_pert(dr,M,options)
info = 0;
M.var_order_endo_names = M.endo_names(dr.order_var,:);
M.var_order_endo_names = M.endo_names(dr.order_var);
% k_order_perturbation expects char array for the names of endogenous and
% exogenous variables (not cells). The mex needs to be fixed...
M.var_order_endo_names = char(M.var_order_endo_names);
M.exo_names = char(M.exo_names);
order = options.order;
endo_nbr = M.endo_nbr;

6
matlab/lmmcp/get_complementarity_conditions.m
View File

@ -12,7 +12,7 @@ function [lb,ub,eq_index] = get_complementarity_conditions(M,ramsey_policy)
% from complementarity setup used in
% perfect_foresight_mcp_problem.m
% Copyright (C) 2014-2017 Dynare Team
% Copyright (C) 2014-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -58,7 +58,7 @@ for i=1:size(etags,1)
str = etags{i,3};
kop = strfind(etags{i,3},'<');
if ~isempty(kop)
k = find(strcmp(strtrim(str(1:kop-1)),cellstr(M.endo_names))); %get variable index with restriction
k = find(strcmp(strtrim(str(1:kop-1)), M.endo_names)); %get variable index with restriction
if isempty(k)
error(sprintf(['Complementarity condition %s: variable %s is ' ...
'not recognized'],etags{i,3},strtrim(str(1:kop-1))))
@ -69,7 +69,7 @@ for i=1:size(etags,1)
else
kop = strfind(etags{i,3},'>');
if ~isempty(kop)
k = find(strcmp(strtrim(str(1:kop-1)),cellstr(M.endo_names))); %get variable index with restriction
k = find(strcmp(strtrim(str(1:kop-1)), M.endo_names)); %get variable index with restriction
if isempty(k)
error(sprintf(['Complementarity condition %s: variable %s is ' ...
'not recognized'],etags{i,3},strtrim(str(1:kop-1))))

8
matlab/lnsrch1.m
View File

@ -24,7 +24,7 @@ function [x,f,fvec,check]=lnsrch1(xold, fold, g, p, stpmax, func, j1, j2, tolx,
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2001-2017 Dynare Team
% Copyright (C) 2001-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -58,14 +58,14 @@ if ~isfinite(summ)
var_string=[];
Model=evalin('base','M_');
for ii=1:length(j2)-1
var_string=[var_string, deblank(Model.endo_names(j2(ii),:)), ', '];
var_string=[var_string, Model.endo_names{j2(ii)}, ', '];
end
var_string=[var_string, deblank(Model.endo_names(j2(end),:))];
var_string=[var_string, Model.endo_names{j2(end)}];
fprintf('\nAn infinite element was encountered when trying to solve equation(s) %s \n',eq_number_string)
fprintf('with respect to the variable(s): %s.\n',var_string)
fprintf('The values of the endogenous variables when the problem was encountered were:\n')
for ii=1:length(xold)
fprintf('%-s % 8.4g \n',Model.endo_names(ii,:),xold(ii));
fprintf('%-s % 8.4g \n', Model.endo_names{ii}, xold(ii));
end
skipline();
end

6
matlab/load_mat_file_data_legacy.m
View File

@ -1,6 +1,6 @@
function data = load_mat_file_data_legacy(datafile, varobs)
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2017-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -32,9 +32,9 @@ else
data_mat=[];
for var_iter=1:length(varobs)
try
data_mat=[data_mat vec(data_file.(varobs{1,var_iter}))];
data_mat=[data_mat vec(data_file.(varobs{var_iter}))];
catch
error('makedataset: The variable %s does not have dimensions conformable with the previous one',varobs{1,var_iter});
error(['makedataset: The variable %s does not have dimensions conformable with the previous one'], varobs{var_iter});
end
end
end

8
matlab/marginal_density.m
View File

@ -15,7 +15,7 @@ function [marginal,oo_] = marginal_density(M_, options_, estim_params_, oo_, bay
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2005-2017 Dynare Team
% Copyright (C) 2005-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -167,7 +167,7 @@ if nvx
ip = 1;
for i=1:nvx
k = estim_params_.var_exo(i,1);
name = deblank(M_.exo_names(k,:));
name = M_.exo_names{k};
eval(['oo_.' field_name '_mode.shocks_std.' name ' = xparam1(ip);']);
eval(['oo_.' field_name '_std_at_mode.shocks_std.' name ' = stdh(ip);']);
ip = ip+1;
@ -188,7 +188,7 @@ if ncx
for i=1:ncx
k1 = estim_params_.corrx(i,1);
k2 = estim_params_.corrx(i,2);
NAME = [deblank(M_.exo_names(k1,:)) '_' deblank(M_.exo_names(k2,:))];
NAME = [M_.exo_names{k1} '_' M_.exo_names{k2}];
eval(['oo_.' field_name '_mode.shocks_corr.' NAME ' = xparam1(ip);']);
eval(['oo_.' field_name '_std_at_mode.shocks_corr.' NAME ' = stdh(ip);']);
ip = ip+1;
@ -200,7 +200,7 @@ if ncn
for i=1:ncn
k1 = estim_params_.corrn(i,1);
k2 = estim_params_.corrn(i,2);
NAME = [deblank(M_.endo_names(k1,:)) '_' deblank(M_.endo_names(k2,:))];
NAME = [M_.endo_names{k1} '_' M_.endo_names{k2}];
eval(['oo_.' field_name '_mode.measurement_errors_corr.' NAME ' = xparam1(ip);']);
eval(['oo_.' field_name '_std_at_mode.measurement_errors_corr.' NAME ' = stdh(ip);']);
ip = ip+1;

50
matlab/model_comparison.m
View File

@ -20,7 +20,7 @@ function oo = model_comparison(ModelNames,ModelPriors,oo,options_,fname)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2007-2017 Dynare Team
% Copyright (C) 2007-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -114,42 +114,36 @@ lmpd = log(ModelPriors)+MarginalLogDensity;
elmpd = exp(lmpd-maxval);
% Now I display the posterior probabilities.
headers = char('Model',ShortModelNames{:});
headers = vertcat('Model', ShortModelNames);
if prior_flag
labels = char('Priors','Log Marginal Density','Bayes Ratio', ...
'Posterior Model Probability');
field_labels={'Prior','Log_Marginal_Density','Bayes_Ratio', ...
'Posterior_Model_Probability'};
values = [ModelPriors';MarginalLogDensity';exp(lmpd-lmpd(1))'; ...
elmpd'/sum(elmpd)];
labels = {'Priors'; 'Log Marginal Density'; 'Bayes Ratio'; 'Posterior Model Probability'};
field_labels={'Prior','Log_Marginal_Density','Bayes_Ratio', 'Posterior_Model_Probability'};
values = [ModelPriors';MarginalLogDensity';exp(lmpd-lmpd(1))'; elmpd'/sum(elmpd)];
else
labels = char('Priors','Log Marginal Density','Bayes Ratio','Posterior Odds Ratio', ...
'Posterior Model Probability');
labels = {'Priors'; 'Log Marginal Density'; 'Bayes Ratio'; 'Posterior Odds Ratio'; 'Posterior Model Probability'};
field_labels={'Prior','Log_Marginal_Density','Bayes_Ratio','Posterior_Odds_Ratio','Posterior_Model_Probability'};
values = [ModelPriors';MarginalLogDensity'; exp(MarginalLogDensity-MarginalLogDensity(1))'; ...
exp(lmpd-lmpd(1))'; elmpd'/sum(elmpd)];
values = [ModelPriors';MarginalLogDensity'; exp(MarginalLogDensity-MarginalLogDensity(1))'; exp(lmpd-lmpd(1))'; elmpd'/sum(elmpd)];
end
for model_iter=1:NumberOfModels
for var_iter=1:size(labels,1)
oo.Model_Comparison.(deblank(headers(1+model_iter,:))).(field_labels{var_iter})=values(var_iter,model_iter);
for model_iter = 1:NumberOfModels
for var_iter = 1:length(labels)
oo.Model_Comparison.(headers{1+model_iter}).(field_labels{var_iter}) = values(var_iter, model_iter);
end
end
dyntable(options_,title,headers,labels,values, 0, 15, 6);
dyntable(options_, title, headers, labels, values, 0, 15, 6);
if options_.TeX
M_temp.fname=fname;
M_temp.dname=fname;
headers_tex='';
for ii=1:size(headers,1)
headers_tex=strvcat(headers_tex,strrep(headers(ii,:),'_', '\_'));
M_temp.fname = fname;
M_temp.dname = fname;
headers_tex = {};
for ii = 1:length(headers)
headers_tex = vertcat(headers_tex, strrep(headers{ii}, '_', '\_'));
end
labels_tex='';
for ii=1:size(labels,1)
labels_tex=strvcat(labels_tex,strrep(labels(ii,:),' ', '\ '));
labels_tex = {};
for ii = 1:length(labels)
labels_tex = vertcat(labels_tex, strrep(labels{ii},' ', '\ '));
end
dyn_latex_table(M_temp,options_,title,['model_comparison',type],headers_tex,labels_tex,values,0,16,6);
dyn_latex_table(M_temp, options_, title, ['model_comparison', type], headers_tex, labels_tex, values, 0, 16, 6);
end
function name = get_model_name_without_path(modelname)
@ -178,9 +172,9 @@ name = modelname(1:end-4);
function modellist = get_short_names(modelnames)
n = length(modelnames);
modellist = {};
modellist = cell(n, 1);
for i=1:n
name = get_model_name_without_extension(modelnames{i});
name = get_model_name_without_path(name);
modellist = {modellist{:} name};
modellist(i) = {name};
end

6
matlab/model_diagnostics.m
View File

@ -16,7 +16,7 @@ function model_diagnostics(M,options,oo)
% none.
%
% Copyright (C) 1996-2017 Dynare Team
% Copyright (C) 1996-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -50,7 +50,7 @@ if ~isempty(k)
disp(['MODEL_DIAGNOSTICS: The following endogenous variables aren''t present at ' ...
'the current period in the model:'])
for i=1:length(k)
disp(endo_names(k(i),:))
disp(endo_names{k(i)})
end
end
@ -154,7 +154,7 @@ for b=1:nb
break
end
end
disp(endo_names(k,:))
disp(endo_names{k})
end
neq = null(jacob');
n_rel = size(neq,2);

28
matlab/model_info.m
View File

@ -1,7 +1,7 @@
function model_info(varargin)
%function model_info;
% Copyright (C) 2008-2017 Dynare Team
% Copyright (C) 2008-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -57,9 +57,9 @@ if(isfield(M_,block_structre_str))
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),:));
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),:));
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
@ -76,7 +76,7 @@ if(isfield(M_,block_structre_str))
last=99999999;
for i=1:size_IM
if(last~=IM(i,2))
fprintf('\n%-30s',M_.endo_names(IM(i,2),:));
fprintf('\n%-30s',M_.endo_names{IM(i,2)});
end
fprintf(' %5d',IM(i,1));
last=IM(i,2);
@ -100,7 +100,7 @@ if(isfield(M_,block_structre_str))
last=99999999;
for i=1:size_IM
if(last~=IM(i,2))
fprintf('\n%-30s',M_.endo_names(IM(i,2),:));
fprintf('\n%-30s',M_.endo_names{IM(i,2)});
end
fprintf(' %5d',IM(i,1));
last=IM(i,2);
@ -122,16 +122,16 @@ if(isfield(M_,block_structre_str))
end
end
seq = 1: M_.endo_nbr;
blank = [ blanks(size(M_.endo_names,2)); blanks(size(M_.endo_names,2))];
blank = [ blanks(cellofchararraymaxlength(M_.endo_names)); blanks(cellofchararraymaxlength(M_.endo_names))];
for i = 1:M_.endo_nbr
if i == 1
var_names = [blank; M_.endo_names(i,:)];
var_names = char(blank, M_.endo_names{i});
else
var_names = [var_names; blank; M_.endo_names(i,:)];
var_names = char(var_names, blank, M_.endo_names{i});
end
end
if incidence
topp = [char(kron(double(blanks(ceil(log10(M_.endo_nbr)))),ones(size(M_.endo_names,2),1))) var_names' ];
topp = [char(kron(double(blanks(ceil(log10(M_.endo_nbr)))),ones(cellofchararraymaxlength(M_.endo_names),1))) var_names' ];
bott = [int2str(seq') blanks(M_.endo_nbr)' blanks(M_.endo_nbr)' IM_star];
fprintf('\n Gross incidence matrix\n');
fprintf(' =======================\n');
@ -141,7 +141,7 @@ if(isfield(M_,block_structre_str))
IM_star_reordered = char([kron(ones(M_.endo_nbr, M_.endo_nbr-1), double(blanks(3))) double(blanks(M_.endo_nbr)')]);
eq(block_structure.equation_reordered) = seq;
va(block_structure.variable_reordered) = seq;
barre_blank = [ barre(size(M_.endo_names,2)); blanks(size(M_.endo_names,2))];
barre_blank = [ barre(cellofchararraymaxlength(M_.endo_names)); blanks(cellofchararraymaxlength(M_.endo_names))];
cur_block = 1;
for i = 1:M_.endo_nbr
past_block = cur_block;
@ -149,16 +149,16 @@ if(isfield(M_,block_structre_str))
cur_block = cur_block + 1;
end
if i == 1
var_names = [blank; M_.endo_names(block_structure.variable_reordered(i),:)];
var_names = [blank; M_.endo_names{block_structure.variable_reordered(i)}];
else
if past_block ~= cur_block
var_names = [var_names; barre_blank; M_.endo_names(block_structure.variable_reordered(i),:)];
var_names = [var_names; barre_blank; M_.endo_names{block_structure.variable_reordered(i)}];
else
var_names = [var_names; blank; M_.endo_names(block_structure.variable_reordered(i),:)];
var_names = [var_names; blank; M_.endo_names{block_structure.variable_reordered(i)}];
end
end
end
topp = [char(kron(double(blanks(ceil(log10(M_.endo_nbr)))),ones(size(M_.endo_names,2),1))) var_names' ];
topp = [char(kron(double(blanks(ceil(log10(M_.endo_nbr)))),ones(cellofchararraymaxlength(M_.endo_names),1))) var_names' ];
n_state_var = length(M_.state_var);
IM_state_var = zeros(n_state_var, n_state_var);
inv_variable_reordered(block_structure.variable_reordered) = 1:M_.endo_nbr;

6
matlab/model_inversion.m
View File

@ -15,7 +15,7 @@ function [endogenousvariables, exogenousvariables] = model_inversion(constraints
%
% REMARKS
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2018 Dynare Team
%
% This file is part of Dynare.
%
@ -69,8 +69,8 @@ if exogenousvariables.vobs>constraints.vobs
end
% Get the list of endogenous and exogenous variables.
endo_names = cellstr(DynareModel.endo_names);
exo_names = cellstr(DynareModel.exo_names);
endo_names = DynareModel.endo_names;
exo_names = DynareModel.exo_names;
% Use specidalized routine if the model is backward looking.
if ~DynareModel.maximum_lead

2
matlab/modules/reporting

@ -1 +1 @@
Subproject commit dfa40f0b7506cfdee02c69c33eeb26180a22e76f
Subproject commit 53d1e479c4e568ce1fda6b52efa202fa32fedefa

18
matlab/ms-sbvar/plot_ms_forecast.m
View File

@ -15,7 +15,7 @@ function plot_ms_forecast(M_, options_, forecast, figure_name)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2011-2017 Dynare Team
% Copyright (C) 2011-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -36,18 +36,18 @@ nc = 2;
nr = 2;
nvars = M_.endo_nbr;
endo_names = M_.endo_names;
var_list = endo_names(1:M_.orig_endo_nbr,:);
var_list = endo_names(1:M_.orig_endo_nbr);
names = {};
tex_names = {};
m = 1;
for i = 1:size(var_list)
tmp = strmatch(var_list(i,:),endo_names,'exact');
for i = 1:length(var_list)
tmp = strmatch(var_list{i}, endo_names, 'exact');
if isempty(tmp)
error([var_list(i,:) ' isn''t and endogenous variable'])
error([var_list{i} ' isn''t and endogenous variable'])
end
tex_name = deblank(M_.endo_names_tex(i,:));
tex_name = M_.endo_names_tex{i};
if ~isempty(tex_name)
names{m} = deblank(var_list(i,:));
names{m} = var_list{i};
tex_names{m} = tex_name;
m = m + 1;
end
@ -98,7 +98,7 @@ for j=1:nvars
m = 1;
end
subplot(nr,nc,m);
vn = deblank(endo_names(j,:));
vn = endo_names{j};
plot(forecast(:,j))
title(vn,'Interpreter','none');
grid on;
@ -130,7 +130,7 @@ for j=1:nvars
m = 1;
end
subplot(nr,nc,m);
vn = deblank(endo_names(j,:));
vn = endo_names{j};
for k=1:num_percentiles
if ceil(num_percentiles/2) == k
plot(forecast(k,:,j),'LineWidth',1.5)

32
matlab/ms-sbvar/plot_ms_irf.m
View File

@ -15,7 +15,7 @@ function plot_ms_irf(M_, options_, irf, figure_name, varlist)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2011-2017 Dynare Team
% Copyright (C) 2011-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -40,29 +40,29 @@ nvars = M_.endo_nbr;
endo_names = M_.endo_names;
if isempty(varlist)
var_list = endo_names(1:M_.orig_endo_nbr,:);
var_list = endo_names(1:M_.orig_endo_nbr);
end
names = {};
tex_names = {};
m = 1;
for i = 1:size(var_list)
tmp = strmatch(var_list(i,:),endo_names,'exact');
for i = 1:length(var_list)
tmp = strmatch(var_list{i}, endo_names, 'exact');
if isempty(tmp)
error([var_list(i,:) ' isn''t and endogenous variable'])
error([var_list{i} ' isn''t and endogenous variable'])
end
tex_name = deblank(M_.endo_names_tex(tmp,:));
tex_name = M_.endo_names_tex{tmp};
if ~isempty(tex_name)
names{m} = deblank(var_list(i,:));
names{m} = var_list{i};
tex_names{m} = tex_name;
m = m + 1;
end
end
for i=1:M_.exo_nbr
tex_name = deblank(M_.exo_names_tex(i,:));
tex_name = M_.exo_names_tex{i};
if ~isempty(tex_name)
names{m} = deblank(M_.exo_names(i,:));
names{m} = M_.exo_names{i};
tex_names{m} = tex_name;
m = m + 1;
end
@ -81,7 +81,7 @@ else
error('The impulse response matrix passed to be plotted does not appear to be the correct size');
end
if size(endo_names,1) ~= nvars
if length(endo_names) ~= nvars
error('The names passed are not the same length as the number of variables');
end
@ -92,7 +92,7 @@ if num_percentiles == 1
for i=1:nvars
shock(:,i) = irf(:,((i-1) + ((s-1)*nvars)+1));
end
plot_point_irf_for_shock(shock, nvars,endo_names, deblank(endo_names(s,:)), ...
plot_point_irf_for_shock(shock, nvars,endo_names, endo_names{s}, ...
figure_name, [options_.ms.output_file_tag filesep 'Output' filesep 'IRF'], options_, names, tex_names);
end
else
@ -103,7 +103,7 @@ else
shock(:,i,n) = irf(n,:,((i-1) + ((s-1)*nvars)+1));
end
end
plot_banded_irf_for_shock(shock, nvars,endo_names, deblank(endo_names(s,:)), ...
plot_banded_irf_for_shock(shock, nvars,endo_names, endo_names{s}, ...
figure_name, [options_.ms.output_file_tag filesep 'Output' filesep 'IRF'], options_, names, tex_names);
end
end
@ -114,8 +114,8 @@ fig = figure('Name',figure_name);
for k=1:nvars
subplot(ceil(sqrt(nvars)), ceil(sqrt(nvars)),k);
plot(irf(:,k))
disp([endo_names(k,:) ' shock from ' shock_name]);
title([endo_names(k,:) ' shock from ' shock_name]);
disp([endo_names{k} ' shock from ' shock_name]);
title([endo_names{k} ' shock from ' shock_name]);
end
dyn_save_graph(dirname,[figure_name ' ' shock_name],options_.graph_save_formats, ...
options_.TeX,names,tex_names,[figure_name ' ' shock_name]);
@ -131,8 +131,8 @@ for k=1:nvars
hold on
end
hold off
disp([endo_names(k,:) ' shock from ' shock_name]);
title([endo_names(k,:) ' shock from ' shock_name]);
disp([endo_names{k} ' shock from ' shock_name]);
title([endo_names{k} ' shock from ' shock_name]);
end
dyn_save_graph(dirname,[figure_name ' ' shock_name],options_.graph_save_formats, ...
options_.TeX,names,tex_names,[figure_name ' ' shock_name]);

10
matlab/ms-sbvar/plot_ms_variance_decomposition.m
View File

@ -22,7 +22,7 @@ function plot_ms_variance_decomposition(M_, options_, vd, figure_name, varargin)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2011-2017 Dynare Team
% Copyright (C) 2011-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -51,9 +51,9 @@ names = {};
tex_names = {};
m = 1;
for i=1:M_.orig_endo_nbr
tex_name = deblank(M_.endo_names_tex(i,:));
tex_name = M_.endo_names_tex{i};
if ~isempty(tex_name)
names{m} = deblank(endo_names(i,:));
names{m} = endo_names{i};
tex_names{m} = tex_name;
m = m + 1;
end
@ -79,8 +79,8 @@ else
end
for i=1:nvars
shock_names{i} = endo_names(i,:);
series_names{i} = endo_names(i,:);
shock_names{i} = endo_names{i};
series_names{i} = endo_names{i};
end
x = [1:T];

26
matlab/ms-sbvar/plot_ms_variance_decomposition_error_bands.m
View File

@ -15,7 +15,7 @@ function plot_ms_variance_decomposition_error_bands(M_, options_, vddata, figure
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2011-2017 Dynare Team
% Copyright (C) 2011-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -34,28 +34,28 @@ function plot_ms_variance_decomposition_error_bands(M_, options_, vddata, figure
nvars = M_.endo_nbr;
endo_names = M_.endo_names;
var_list = endo_names(1:M_.orig_endo_nbr,:);
var_list = endo_names(1:M_.orig_endo_nbr);
names = {};
tex_names = {};
m = 1;
for i = 1:size(var_list)
tmp = strmatch(var_list(i,:), endo_names, 'exact');
for i = 1:length(var_list)
tmp = strmatch(var_list{i}, endo_names, 'exact');
if isempty(tmp)
error([var_list(i,:) ' isn''t an endogenous variable'])
error([var_list{i} ' isn''t an endogenous variable'])
end
tex_name = deblank(M_.endo_names_tex(tmp,:));
tex_name = M_.endo_names_tex{tmp};
if ~isempty(tex_name)
names{m} = deblank(var_list(i,:));
names{m} = var_list{i};
tex_names{m} = tex_name;
m = m + 1;
end
end
for i=1:M_.exo_nbr
tex_name = deblank(M_.exo_names_tex(i,:));
tex_name = M_.exo_names_tex{i};
if ~isempty(tex_name)
names{m} = deblank(M_.exo_names(i,:));
names{m} = M_.exo_names{i};
tex_names{m} = tex_name;
m = m + 1;
end
@ -67,7 +67,7 @@ if length(dims) ~= 3
end
num_percentiles = dims(1);
if size(endo_names, 1) ~= nvars
if length(endo_names) ~= nvars
error('The names passed are not the same length as the number of variables')
end
@ -79,7 +79,7 @@ for s=1:nvars
end
end
plot_banded_vddata_for_shock(shock, nvars, endo_names, ...
deblank(endo_names(s,:)), figure_name, ...
endo_names{s}, figure_name, ...
[options_.ms.output_file_tag filesep 'Output' filesep 'Variance_Decomposition'], ...
options_, names, tex_names);
end
@ -96,8 +96,8 @@ for k=1:nvars
hold on
end
hold off
disp([endo_names(k,:) ' contribution to ' shock_name]);
title([endo_names(k,:) ' contribution to ' shock_name]);
disp([endo_names{k} ' contribution to ' shock_name]);
title([endo_names{k} ' contribution to ' shock_name]);
end
dyn_save_graph(dirname, [figure_name ' ' shock_name], ...
options_.graph_save_formats, options_.TeX, names, tex_names, ...

29
matlab/mult_elimination.m
View File

@ -12,7 +12,7 @@ function dr=mult_elimination(varlist,M_, options_, oo_)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2017 Dynare Team
% Copyright (C) 2003-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -34,7 +34,7 @@ dr = oo_.dr;
nstatic = M_.nstatic;
nspred = M_.nspred;
order_var = dr.order_var;
nstates = M_.endo_names(order_var(nstatic+(1:nspred)),:);
nstates = M_.endo_names(order_var(nstatic+(1:nspred)));
il = strmatch('MULT_',nstates);
nil = setdiff(1:nspred,il);
@ -103,10 +103,10 @@ nvar = length(varlist);
if nvar > 0 && options_.noprint == 0
res_table = zeros(2*(nm_nbr+M_.exo_nbr),nvar);
headers = 'Variables';
headers = {'Variables'};
for i=1:length(varlist)
k = strmatch(varlist{i},M_.endo_names(dr.order_var,:),'exact');
headers = char(headers,varlist{i});
k = strmatch(varlist{i}, M_.endo_names(dr.order_var), 'exact');
headers = vertcat(headers, varlist{i});
res_table(1:nm_nbr,i) = M1(k,:)';
res_table(nm_nbr+(1:nm_nbr),i) = M2(k,:)';
@ -115,19 +115,12 @@ if nvar > 0 && options_.noprint == 0
end
my_title='ELIMINATION OF THE MULTIPLIERS';
lab = nstates(nil,:);
labels = strcat(deblank(lab(i,:)),'(-1)');
for i = 2:size(lab,1)
labels = char(labels,strcat(deblank(lab(i,:)),'(-1)'));
end
for i = 1:size(lab,1)
labels = char(labels,strcat(deblank(lab(i,:)),'(-2)'));
end
labels = char(labels,M_.exo_names);
for i = 1:M_.exo_nbr
labels = char(labels,strcat(deblank(M_.exo_names(i,:)),'(-1)'));
end
lab = nstates(nil);
labels = cellfun(@(x) horzcat(x, '(-1)'), nstates(nil), 'UniformOutput', false);
labels = vertcat(labels, cellfun(@(x) horzcat(x, '(-2)'), nstates(nil), 'UniformOutput', false));
labels = vertcat(labels, M_.exo_names);
labels = vertcat(labels, cellfun(@(x) horzcat(x, '(-1)'), M_.exo_names, 'UniformOutput', false));
lh = size(labels,2)+2;
dyntable(options_,my_title,headers,labels,res_table,lh,10,6);
dyntable(options_, my_title, headers, labels, res_table, lh, 10, 6);
skipline()
end

22
matlab/name2index.m
View File

@ -16,7 +16,7 @@ function i = name2index(options_, M_, estim_params_, type, name1, name2 )
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2008-2017 Dynare Team
% Copyright (C) 2008-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -44,7 +44,7 @@ i = [];
if strcmpi(type,'DeepParameter')
i = nvx + nvn + ncx + ncn + ...
strmatch(name1,M_.param_names(estim_params_.param_vals(:,1),:),'exact');
strmatch(name1, M_.param_names(estim_params_.param_vals(:,1)), 'exact');
if nargin>5
disp('The last input argument is useless!')
end
@ -56,7 +56,7 @@ end
if strcmpi(type,'StructuralShock')
if nargin<6% Covariance matrix diagonal term.
i = strmatch(name1,M_.exo_names(estim_params_.var_exo(:,1),:),'exact');
i = strmatch(name1, M_.exo_names(estim_params_.var_exo(:,1)), 'exact');
if isempty(i)
disp(['The standard deviation of ' name1 ' is not an estimated parameter!'])
return
@ -64,14 +64,14 @@ if strcmpi(type,'StructuralShock')
else% Covariance matrix off-diagonal term
offset = nvx+nvn;
try
list_of_structural_shocks = { M_.exo_names(estim_params_.corrx(:,1),:) , M_.exo_names(estim_params_.corrx(:,2),:) };
k1 = strmatch(name1,list_of_structural_shocks(:,1),'exact');
k2 = strmatch(name2,list_of_structural_shocks(:,2),'exact');
list_of_structural_shocks = [ M_.exo_names(estim_params_.corrx(:,1)) , M_.exo_names(estim_params_.corrx(:,2)) ];
k1 = strmatch(name1, list_of_structural_shocks(:,1), 'exact');
k2 = strmatch(name2, list_of_structural_shocks(:,2), 'exact');
i = offset+intersect(k1,k2);
if isempty(i)
k1 = strmatch(name1,list_of_structural_shocks(:,2),'exact');
k2 = strmatch(name2,list_of_structural_shocks(:,1),'exact');
i = offset+intersect(k1,k2);
k1 = strmatch(name1, list_of_structural_shocks(:,2), 'exact');
k2 = strmatch(name2, list_of_structural_shocks(:,1), 'exact');
i = offset+intersect(k1, k2);
end
if isempty(i)
if isempty(i)
@ -87,7 +87,7 @@ end
if strcmpi(type,'MeasurementError')
if nargin<6% Covariance matrix diagonal term
i = nvx + strmatch(name1,M_.endo_names(estim_params_.var_endo(:,1),:),'exact');
i = nvx + strmatch(name1, M_.endo_names{estim_params_.var_endo(:,1)}, 'exact');
if isempty(i)
disp(['The standard deviation of the measurement error on ' name1 ' is not an estimated parameter!'])
return
@ -95,7 +95,7 @@ if strcmpi(type,'MeasurementError')
else% Covariance matrix off-diagonal term
offset = nvx+nvn+ncx;
try
list_of_measurement_errors = { M_.endo_names(estim_params_.corrn(:,1),:) , M_.endo_names(estim_params_.corrn(:,2),:) };
list_of_measurement_errors = { M_.endo_names{estim_params_.corrn(:,1)} , M_.endo_names{estim_params_.corrn(:,2)} };
k1 = strmatch(name1,list_of_measurement_errors(:,1),'exact');
k2 = strmatch(name2,list_of_measurement_errors(:,2),'exact');
i = offset+intersect(k1,k2);

10
matlab/occbin/call_solve_one_constraint.m
View File

@ -8,14 +8,14 @@
% unpack the IRFs
for i=1:Mbase_.endo_nbr
eval([deblank(Mbase_.endo_names(i,:)),'_uncdifference=zdatalinear(:,i);']);
eval([deblank(Mbase_.endo_names(i,:)),'_difference=zdatapiecewise(:,i);']);
eval([deblank(Mbase_.endo_names(i,:)),'_ss=zdatass(i);']);
eval([Mbase_.endo_names{i}, '_uncdifference=zdatalinear(:,i);']);
eval([Mbase_.endo_names{i}, '_difference=zdatapiecewise(:,i);']);
eval([Mbase_.endo_names{i}, '_ss=zdatass(i);']);
end
nparams = size(Mbase_.param_names,1);
nparams = length(Mbase_.param_names);
for i = 1:nparams
eval([Mbase_.param_names(i,:),'= Mbase_.params(i);']);
eval([Mbase_.param_names{i}, '= Mbase_.params(i);']);
end

14
matlab/occbin/call_solve_two_constraints.m
View File

@ -6,16 +6,16 @@
for i=1:Mbase_.endo_nbr
eval([deblank(Mbase_.endo_names(i,:)),'_uncdifference=zdatalinear(:,i);']);
eval([deblank(Mbase_.endo_names(i,:)),'_difference=zdatapiecewise(:,i);']);
eval([deblank(Mbase_.endo_names(i,:)),'_ss=zdatass(i);']);
eval([Mbase_.endo_names{i}, '_uncdifference=zdatalinear(:,i);']);
eval([Mbase_.endo_names{i}, '_difference=zdatapiecewise(:,i);']);
eval([Mbase_.endo_names{i}, '_ss=zdatass(i);']);
end
constraint1_difference = process_constraint(constraint1,'_difference',Mbase_.endo_names,0);
constraint2_difference = process_constraint(constraint2,'_difference',Mbase_.endo_names,0);
constraint1_difference = process_constraint(constraint1, '_difference', Mbase_.endo_names,0);
constraint2_difference = process_constraint(constraint2, '_difference', Mbase_.endo_names,0);
nparams = size(Mbase_.param_names,1);
nparams = length(Mbase_.param_names);
for i = 1:nparams
eval([Mbase_.param_names(i,:),'= Mbase_.params(i);']);
eval([Mbase_.param_names{i}, '= Mbase_.params(i);']);
end

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