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Commit 4480f5b4 authored by Marco Ratto's avatar Marco Ratto
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Fixes around latex output: use of longtable for parameter estimates and... 

Fixes around latex output: use of longtable for parameter estimates and various fixes for posterior analysis, also for parallel execution.
parent 5af1effd
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matlab/GetPosteriorParametersStatistics.m
View file @ 4480f5b4
......@@ -57,7 +57,7 @@ FirstMhFile = record.KeepedDraws.FirstMhFile;
NumberOfDraws = TotalNumberOfMhDraws-floor(options_.mh_drop*TotalNumberOfMhDraws);
clear record;
pnames=[' ';'beta ';'gamm ';'norm ';'invg ';'unif ';'invg2'];
pnames=[' ';'beta ';'gamma';'norm ';'invg ';'unif ';'invg2'];
header_width = row_header_width(M_,estim_params_,bayestopt_);
tit2 = sprintf('%-*s %10s %10s %16s %6s %10s\n',header_width+2,' ','prior mean','post. mean','conf. interval','prior','pstdev');
pformat = '%-*s %10.3f %10.4f %10.4f %8.4f %6s %10.4f';
......@@ -103,6 +103,8 @@ if np
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);
end
......@@ -147,7 +149,8 @@ if nvx
end
disp(sprintf(pformat,header_width,name,bayestopt_.p1(ip),post_mean,hpd_interval,...
pnames(bayestopt_.pshape(ip)+1,:),bayestopt_.p2(ip)));
if TeX
if TeX,
name = deblank(M_.exo_names_tex(k,:));
TeXCore(fid,name,deblank(pnames(bayestopt_.pshape(ip)+1,:)),bayestopt_.p1(ip),...
bayestopt_.p2(ip),post_mean,sqrt(post_var),hpd_interval);
end
......@@ -188,6 +191,8 @@ if nvn
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);
end
......@@ -241,6 +246,7 @@ if ncx
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);
end
......@@ -291,7 +297,8 @@ if ncn
end
disp(sprintf(pformat, header_width,name,bayestopt_.p1(ip),post_mean,hpd_interval, ...
pnames(bayestopt_.pshape(ip)+1,:),bayestopt_.p2(ip)));
if TeX
if TeX,
name = ['(',deblank(M_.endo_names_tex(k1,:)) ',' deblank(M_.endo_names_tex(k2,:)),')'];
TeXCore(fid,name,deblank(pnames(bayestopt_.pshape(ip)+1,:)),bayestopt_.p1(ip),...
bayestopt_.p2(ip),post_mean,sqrt(post_var),hpd_interval);
end
......@@ -314,13 +321,25 @@ fprintf(fidTeX,['%% RESULTS FROM METROPOLIS HASTINGS (' title ')\n']);
fprintf(fidTeX,['%% ' datestr(now,0)]);
fprintf(fidTeX,' \n');
fprintf(fidTeX,' \n');
fprintf(fidTeX,'\\begin{table}\n');
fprintf(fidTeX,'\\centering\n');
fprintf(fidTeX,'\\begin{tabular}{l|lcccccc} \n');
fprintf(fidTeX,'\\begin{center}\n');
fprintf(fidTeX,'\\begin{longtable}{l|lcccccc} \n');
fprintf(fidTeX,['\\caption{Results from Metropolis-Hastings (' title ')}\n ']);
fprintf(fidTeX,['\\label{Table:MHPosterior:' int2str(fnum) '}\\\\\n']);
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,[' & Prior distribution & Prior mean & Prior ' ...
's.d. & Posterior mean & Posterior s.d. & HPD inf & HPD sup\\\\ \n']);
fprintf(fidTeX,'\\hline \\endfirsthead \n');
fprintf(fidTeX,['\\caption{(continued)}']);
fprintf(fidTeX,['\\label{Table:MHPosterior:' int2str(fnum) '}\\\\\n']);
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,[' & Prior distribution & Prior mean & Prior ' ...
's.d. & Posterior mean & Posterior s.d. & HPD inf & HPD sup\\\\ \n']);
fprintf(fidTeX,'\\hline \\\\ \n');
fprintf(fidTeX,'\\hline \\endhead \n');
fprintf(fidTeX,'\\hline \\multicolumn{8}{r}{(Continued on next page)} \\\\ \\hline \\endfoot \n');
fprintf(fidTeX,'\\hline \\hline \\endlastfoot \n');
fid = fidTeX;
......@@ -337,11 +356,8 @@ fprintf(fid,['$%s$ & %s & %7.3f & %6.4f & %7.3f& %6.4f & %7.4f & %7.4f \\\\ \n']
function TeXEnd(fid,fnum,title)
fprintf(fid,'\\hline\\hline \n');
fprintf(fid,'\\end{tabular}\n ');
fprintf(fid,['\\caption{Results from Metropolis-Hastings (' title ')}\n ']);
fprintf(fid,['\\label{Table:MHPosterior:' int2str(fnum) '}\n']);
fprintf(fid,'\\end{table}\n');
fprintf(fid,'\\end{longtable}\n ');
fprintf(fid,'\\end{center}\n');
fprintf(fid,'%% End of TeX file.\n');
fclose(fid);
......
matlab/McMCDiagnostics.m
View file @ 4480f5b4
......@@ -175,7 +175,7 @@ for i = 1:pages
fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
end
fprintf(fidTeX,'\\centering \n');
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_udiag%s}\n',M_.fname,int2str(i));
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_udiag%s}\n',[DirectoryName '/' M_.fname],int2str(i));
fprintf(fidTeX,'\\caption{Univariate convergence diagnostics for the Metropolis-Hastings.\n');
fprintf(fidTeX,'The first, second and third columns are respectively the criteria based on\n');
fprintf(fidTeX,'the eighty percent interval, the second and third moments.}');
......@@ -238,7 +238,7 @@ if reste
fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
end
fprintf(fidTeX,'\\centering \n');
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_udiag%s}\n',M_.fname,int2str(pages+1));
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_udiag%s}\n',[DirectoryName '/' M_.fname],int2str(pages+1));
if reste == 2
fprintf(fidTeX,'\\caption{Univariate convergence diagnostics for the Metropolis-Hastings.\n');
fprintf(fidTeX,'The first, second and third columns are respectively the criteria based on\n');
......@@ -348,7 +348,7 @@ if TeX
fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(jj,:)),' ');
end
fprintf(fidTeX,'\\centering \n');
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_mdiag}\n',M_.fname);
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_mdiag}\n',[DirectoryName '/' M_.fname]);
fprintf(fidTeX,'\\caption{Multivariate convergence diagnostics for the Metropolis-Hastings.\n');
fprintf(fidTeX,'The first, second and third rows are respectively the criteria based on\n');
fprintf(fidTeX,'the eighty percent interval, the second and third moments. The different \n');
......
matlab/PlotPosteriorDistributions.m
View file @ 4480f5b4
......@@ -159,7 +159,7 @@ for i=1:npar
fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(j,:)),deblank(TeXNAMES(j,:)));
end
fprintf(fidTeX,'\\centering\n');
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_PriorsAndPosteriors%s}\n',M_.fname,int2str(figunumber));
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s/%s_PriorsAndPosteriors%s}\n',OutputDirectoryName,M_.fname,int2str(figunumber));
fprintf(fidTeX,'\\caption{Priors and posteriors.}');
fprintf(fidTeX,'\\label{Fig:PriorsAndPosteriors:%s}\n',int2str(figunumber));
fprintf(fidTeX,'\\end{figure}\n');
......
matlab/dynare_estimation_1.m
View file @ 4480f5b4
......@@ -630,15 +630,20 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
fprintf(fidTeX,['%% ' datestr(now,0)]);
fprintf(fidTeX,' \n');
fprintf(fidTeX,' \n');
fprintf(fidTeX,'{\\tiny \n');
fprintf(fidTeX,'\\begin{table}\n');
fprintf(fidTeX,'\\centering\n');
fprintf(fidTeX,'\\begin{center}\n');
fprintf(fidTeX,'\\begin{longtable}{l|lcccc} \n');
fprintf(fidTeX,'\\caption{Results from posterior maximization (parameters)}\n ');
fprintf(fidTeX,'\\label{Table:Posterior:1}\n');
fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
fprintf(fidTeX,'\\label{Table:Posterior:1}\\\\\n');
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
fprintf(fidTeX,'\\hline \\\\ \n');
fprintf(fidTeX,'\\hline \\endfirsthead \n');
fprintf(fidTeX,'\\caption{(continued)}\n ');
fprintf(fidTeX,'\\label{Table:Posterior:1}\\\\\n');
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
fprintf(fidTeX,'\\hline \\endhead \n');
fprintf(fidTeX,'\\hline \\multicolumn{6}{r}{(Continued on next page)} \\\\ \\hline \\endfoot \n');
fprintf(fidTeX,'\\hline \\hline \\endlastfoot \n');
ip = nvx+nvn+ncx+ncn+1;
for i=1:np
fprintf(fidTeX,'$%s$ & %s & %7.3f & %6.4f & %8.4f & %7.4f \\\\ \n',...
......@@ -649,24 +654,9 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
xparam1(ip),...
stdh(ip));
ip = ip + 1;
if ~mod(i,50) && i<np,
fprintf(fidTeX,'\\hline \n');
fprintf(fidTeX,'\\multicolumn{6}{c}{(Table continues next page ...)} \\\\ \n')';
fprintf(fidTeX,'\\end{tabular}\n ');
fprintf(fidTeX,'\\end{table}\n');
fprintf(fidTeX,'\\begin{table}\n');
fprintf(fidTeX,'\\centering\n');
fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
fprintf(fidTeX,'\\multicolumn{6}{c}{( ... Table continued)} \\\\ \n')';
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
fprintf(fidTeX,'\\hline \\\\ \n');
end
end
fprintf(fidTeX,'\\hline\\hline \n');
fprintf(fidTeX,'\\end{tabular}\n ');
fprintf(fidTeX,'\\end{table}\n');
fprintf(fidTeX,'} \n');
fprintf(fidTeX,'\\end{longtable}\n ');
fprintf(fidTeX,'\\end{center}\n');
fprintf(fidTeX,'%% End of TeX file.\n');
fclose(fidTeX);
end
......@@ -678,15 +668,20 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
fprintf(fidTeX,['%% ' datestr(now,0)]);
fprintf(fidTeX,' \n');
fprintf(fidTeX,' \n');
fprintf(fidTeX,'{\\tiny \n');
fprintf(fidTeX,'\\begin{table}\n');
fprintf(fidTeX,'\\centering\n');
fprintf(fidTeX,'\\begin{center}\n');
fprintf(fidTeX,'\\begin{longtable}{l|lcccc} \n');
fprintf(fidTeX,'\\caption{Results from posterior maximization (standard deviation of structural shocks)}\n ');
fprintf(fidTeX,'\\label{Table:Posterior:2}\n');
fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
fprintf(fidTeX,'\\label{Table:Posterior:2}\\\\\n');
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
fprintf(fidTeX,'\\hline \\\\ \n');
fprintf(fidTeX,'\\hline \\endfirsthead \n');
fprintf(fidTeX,'\\caption{(continued)}\n ');
fprintf(fidTeX,'\\label{Table:Posterior:2}\\\\\n');
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
fprintf(fidTeX,'\\hline \\endhead \n');
fprintf(fidTeX,'\\hline \\multicolumn{6}{r}{(Continued on next page)} \\\\ \\hline \\endfoot \n');
fprintf(fidTeX,'\\hline \\hline \\endlastfoot \n');
ip = 1;
for i=1:nvx
k = estim_params_.var_exo(i,1);
......@@ -698,24 +693,9 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
xparam1(ip), ...
stdh(ip));
ip = ip+1;
if ~mod(i,50) && i<nvx,
fprintf(fidTeX,'\\hline \n');
fprintf(fidTeX,'\\multicolumn{6}{c}{(Table continues next page ...)} \\\\ \n')';
fprintf(fidTeX,'\\end{tabular}\n ');
fprintf(fidTeX,'\\end{table}\n');
fprintf(fidTeX,'\\begin{table}\n');
fprintf(fidTeX,'\\centering\n');
fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
fprintf(fidTeX,'\\multicolumn{6}{c}{( ... Table continued)} \\\\ \n')';
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
fprintf(fidTeX,'\\hline \\\\ \n');
end
end
fprintf(fidTeX,'\\hline\\hline \n');
fprintf(fidTeX,'\\end{tabular}\n ');
fprintf(fidTeX,'\\end{table}\n');
fprintf(fidTeX,'} \n');
fprintf(fidTeX,'\\end{longtable}\n ');
fprintf(fidTeX,'\\end{center}\n');
fprintf(fidTeX,'%% End of TeX file.\n');
fclose(fidTeX);
end
......@@ -727,14 +707,20 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
fprintf(fidTeX,['%% ' datestr(now,0)]);
fprintf(fidTeX,' \n');
fprintf(fidTeX,' \n');
fprintf(fidTeX,'\\begin{table}\n');
fprintf(fidTeX,'\\centering\n');
fprintf(fidTeX,'\\begin{center}\n');
fprintf(fidTeX,'\\begin{longtable}{l|lcccc} \n');
fprintf(fidTeX,'\\caption{Results from posterior maximization (standard deviation of measurement errors)}\n ');
fprintf(fidTeX,'\\label{Table:Posterior:3}\n');
fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
fprintf(fidTeX,'\\label{Table:Posterior:3}\\\\\n');
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n')
fprintf(fidTeX,'\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
fprintf(fidTeX,'\\hline \\endfirsthead \n');
fprintf(fidTeX,'\\caption{(continued)}\n ');
fprintf(fidTeX,'\\label{Table:Posterior:3}\\\\\n');
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
fprintf(fidTeX,'\\hline \\endhead \n');
fprintf(fidTeX,'\\hline \\multicolumn{6}{r}{(Continued on next page)} \\\\ \\hline \\endfoot \n');
fprintf(fidTeX,'\\hline \\hline \\endlastfoot \n');
ip = nvx+1;
for i=1:nvn
idx = strmatch(options_.varobs(estim_params_.var_endo(i,1),:),M_.endo_names);
......@@ -746,23 +732,9 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
xparam1(ip),...
stdh(ip));
ip = ip+1;
if ~mod(i,50) && i<nvn,
fprintf(fidTeX,'\\hline \n');
fprintf(fidTeX,'\\multicolumn{6}{c}{(Table continues next page ...)} \\\\ \n')';
fprintf(fidTeX,'\\end{tabular}\n ');
fprintf(fidTeX,'\\end{table}\n');
fprintf(fidTeX,'\\begin{table}\n');
fprintf(fidTeX,'\\centering\n');
fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
fprintf(fidTeX,'\\multicolumn{6}{c}{( ... Table continued)} \\\\ \n')';
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
fprintf(fidTeX,'\\hline \\\\ \n');
end
end
fprintf(fidTeX,'\\hline\\hline \n');
fprintf(fidTeX,'\\end{tabular}\n ');
fprintf(fidTeX,'\\end{table}\n');
fprintf(fidTeX,'\\end{longtable}\n ');
fprintf(fidTeX,'\\end{center}\n');
fprintf(fidTeX,'%% End of TeX file.\n');
fclose(fidTeX);
end
......@@ -774,14 +746,20 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
fprintf(fidTeX,['%% ' datestr(now,0)]);
fprintf(fidTeX,' \n');
fprintf(fidTeX,' \n');
fprintf(fidTeX,'\\begin{table}\n');
fprintf(fidTeX,'\\centering\n');
fprintf(fidTeX,'\\begin{center}\n');
fprintf(fidTeX,'\\begin{longtable}{l|lcccc} \n');
fprintf(fidTeX,'\\caption{Results from posterior parameters (correlation of structural shocks)}\n ');
fprintf(fidTeX,'\\label{Table:Posterior:4}\n');
fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
fprintf(fidTeX,'\\label{Table:Posterior:4}\\\\\n');
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
fprintf(fidTeX,'\\hline \\endfirsthead \n');
fprintf(fidTeX,'\\caption{(continued)}\n ');
fprintf(fidTeX,'\\label{Table:Posterior:4}\\\\\n');
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n')
fprintf(fidTeX,'\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
fprintf(fidTeX,'\\hline \\endhead \n');
fprintf(fidTeX,'\\hline \\multicolumn{6}{r}{(Continued on next page)} \\\\ \\hline \\endfoot \n');
fprintf(fidTeX,'\\hline \\hline \\endlastfoot \n');
ip = nvx+nvn+1;
for i=1:ncx
k1 = estim_params_.corrx(i,1);
......@@ -794,23 +772,9 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
xparam1(ip), ...
stdh(ip));
ip = ip+1;
if ~mod(i,50) && i<ncx,
fprintf(fidTeX,'\\hline \n');
fprintf(fidTeX,'\\multicolumn{6}{c}{(Table continues next page ...)} \\\\ \n')';
fprintf(fidTeX,'\\end{tabular}\n ');
fprintf(fidTeX,'\\end{table}\n');
fprintf(fidTeX,'\\begin{table}\n');
fprintf(fidTeX,'\\centering\n');
fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
fprintf(fidTeX,'\\multicolumn{6}{c}{( ... Table continued)} \\\\ \n')';
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
fprintf(fidTeX,'\\hline \\\\ \n');
end
end
fprintf(fidTeX,'\\hline\\hline \n');
fprintf(fidTeX,'\\end{tabular}\n ');
fprintf(fidTeX,'\\end{table}\n');
fprintf(fidTeX,'\\end{longtable}\n ');
fprintf(fidTeX,'\\end{center}\n');
fprintf(fidTeX,'%% End of TeX file.\n');
fclose(fidTeX);
end
......@@ -822,14 +786,20 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
fprintf(fidTeX,['%% ' datestr(now,0)]);
fprintf(fidTeX,' \n');
fprintf(fidTeX,' \n');
fprintf(fidTeX,'\\begin{table}\n');
fprintf(fidTeX,'\\centering\n');
fprintf(fidTeX,'\\begin{center}\n');
fprintf(fidTeX,'\\begin{longtabe}{l|lcccc} \n');
fprintf(fidTeX,'\\caption{Results from posterior parameters (correlation of measurement errors)}\n ');
fprintf(fidTeX,'\\label{Table:Posterior:5}\n');
fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
fprintf(fidTeX,'\\label{Table:Posterior:5}\\\\\n');
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
fprintf(fidTeX,'\\hline \\endfirsthead \n');
fprintf(fidTeX,'\\caption{(continued)}\n ');
fprintf(fidTeX,'\\label{Table:Posterior:5}\\\\\n');
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n')
fprintf(fidTeX,'\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
fprintf(fidTeX,'\\hline \\endhead \n');
fprintf(fidTeX,'\\hline \\multicolumn{6}{r}{(Continued on next page)} \\\\ \\hline \\endfoot \n');
fprintf(fidTeX,'\\hline \\hline \\endlastfoot \n');
ip = nvx+nvn+ncx+1;
for i=1:ncn
k1 = estim_params_.corrn(i,1);
......@@ -842,23 +812,9 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
xparam1(ip), ...
stdh(ip));
ip = ip+1;
if ~mod(i,50) && i<ncn,
fprintf(fidTeX,'\\hline \n');
fprintf(fidTeX,'\\multicolumn{6}{c}{(Table continues next page ...)} \\\\ \n')';
fprintf(fidTeX,'\\end{tabular}\n ');
fprintf(fidTeX,'\\end{table}\n');
fprintf(fidTeX,'\\begin{table}\n');
fprintf(fidTeX,'\\centering\n');
fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
fprintf(fidTeX,'\\multicolumn{6}{c}{( ... Table continued)} \\\\ \n')';
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
fprintf(fidTeX,'\\hline \\\\ \n');
end
end
fprintf(fidTeX,'\\hline\\hline \n');
fprintf(fidTeX,'\\end{tabular}\n ');
fprintf(fidTeX,'\\end{table}\n');
fprintf(fidTeX,'\\end{longtable}\n ');
fprintf(fidTeX,'\\end{center}\n');
fprintf(fidTeX,'%% End of TeX file.\n');
fclose(fidTeX);
end
......
matlab/pm3.m
View file @ 4480f5b4
......@@ -41,12 +41,16 @@ else
end
if options_.TeX
% needs to be fixed
if isempty(tit_tex),
tit_tex=M_.endo_names_tex;
end
varlist_TeX = [];
for i=1:nvar
if i==1
varlist_TeX = M_.endo_names_tex(SelecVariables(i),:);
varlist_TeX = tit_tex(SelecVariables(i),:);
else
varlist_TeX = char(varlist_TeX,M_.endo_names_tex(SelecVariables(i),:));
varlist_TeX = char(varlist_TeX,tit_tex(SelecVariables(i),:));
end
end
end
......@@ -97,40 +101,6 @@ end
% %%% The file .TeX! are not saved in parallel.
subplotnum = 0;
if options_.TeX
fidTeX = fopen([M_.dname '/Output/' M_.fname '_' name3 '.TeX'],'w');
fprintf(fidTeX,'%% TeX eps-loader file generated by Dynare.\n');
fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
fprintf(fidTeX,' \n');
for i=1:nvar
NAMES = [];
TEXNAMES = [];
if max(abs(Mean(:,i))) > 10^(-6)
subplotnum = subplotnum+1;
name = deblank(varlist(i,:));
NAMES = name;
texname = deblank(varlist_TeX(i,:));
TEXNAMES = ['$' texname '$'];
end
if subplotnum == MaxNumberOfPlotsPerFigure || i == nvar
fprintf(fidTeX,'\\begin{figure}[H]\n');
for jj = 1:size(TEXNAMES,1)
fprintf(fidTeX,['\\psfrag{%s}[1][][0.5][0]{%s}\n'],deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
end
fprintf(fidTeX,'\\centering \n');
fprintf(fidTeX,['\\includegraphics[scale=0.5]{%s_' name3 '_%s}\n'],M_.fname,deblank(tit3(i,:)));
fprintf(fidTeX,'\\label{Fig:%s:%s}\n',name3,deblank(tit3(i,:)));
fprintf(fidTeX,'\\end{figure}\n');
fprintf(fidTeX,' \n');
subplotnum = 0;
end
end
fprintf(fidTeX,'%% End of TeX file.\n');
fclose(fidTeX);
end
% Store the variable mandatory for local/remote parallel computing.
......@@ -146,7 +116,7 @@ localVars.name3=name3;
localVars.tit3=tit3;
localVars.Mean=Mean;
% Like sequential execution!
nvar0=nvar;
if ~exist('OCTAVE_VERSION')
% Commenting for testing!
......@@ -165,7 +135,7 @@ if ~exist('OCTAVE_VERSION')
globalVars = struct('M_',M_, ...
'options_', options_, ...
'oo_', oo_);
[fout, nBlockPerCPU, totCPU] = masterParallel(options_.parallel, 1, nvar, [],'pm3_core', localVars,globalVars, options_.parallel_info);
[fout, nvar0, totCPU] = masterParallel(options_.parallel, 1, nvar, [],'pm3_core', localVars,globalVars, options_.parallel_info);
end
end
else
......@@ -175,6 +145,54 @@ else
fout = pm3_core(localVars,1,nvar,0);
end
subplotnum = 0;
if options_.TeX,
fidTeX = fopen([M_.dname '/Output/' M_.fname '_' name3 '.TeX'],'w');
fprintf(fidTeX,'%% TeX eps-loader file generated by Dynare.\n');
fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
fprintf(fidTeX,' \n');
nvar0=cumsum(nvar0);
i=0;
for j=1:length(nvar0),
NAMES = [];
TEXNAMES = [];
nvar=nvar0(j);
while i<nvar,
i=i+1;
if max(abs(Mean(:,i))) > 10^(-6)
subplotnum = subplotnum+1;
name = deblank(varlist(i,:));
texname = deblank(varlist_TeX(i,:));
if subplotnum==1
NAMES = name;
TEXNAMES = ['$' texname '$'];
else
NAMES = char(NAMES,name);
TEXNAMES = char(TEXNAMES,['$' texname '$']);
end
end
if subplotnum == MaxNumberOfPlotsPerFigure || i == nvar
fprintf(fidTeX,'\\begin{figure}[H]\n');
for jj = 1:size(TEXNAMES,1)
fprintf(fidTeX,['\\psfrag{%s}[1][][0.5][0]{%s}\n'],deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
end
fprintf(fidTeX,'\\centering \n');
fprintf(fidTeX,['\\includegraphics[scale=0.5]{%s/Output/%s_' name3 '_%s}\n'],M_.dname,M_.fname,deblank(tit3(i,:)));
fprintf(fidTeX,'\\label{Fig:%s:%s}\n',name3,deblank(tit3(i,:)));
fprintf(fidTeX,'\\end{figure}\n');
fprintf(fidTeX,' \n');
subplotnum = 0;
NAMES = [];
TEXNAMES = [];
end
end
end
fprintf(fidTeX,'%% End of TeX file.\n');
fclose(fidTeX);
end
fprintf(['MH: ' tit1 ', done!\n']);
......
matlab/prior_posterior_statistics.m
View file @ 4480f5b4
......@@ -221,13 +221,16 @@ if isnumeric(options_.parallel),
% Parallel execution!
else
[nCPU, totCPU, nBlockPerCPU] = distributeJobs(options_.parallel, 1, B);
ifil=zeros(7,totCPU);
for j=1:totCPU-1,
nfiles = ceil(nBlockPerCPU(j)/MAX_nsmoo);
ifil(1,j+1) =ifil(1,j)+nfiles;
nfiles = ceil(nBlockPerCPU(j)/MAX_ninno);
ifil(2,j+1) =ifil(2,j)+nfiles;
nfiles = ceil(nBlockPerCPU(j)/MAX_nerro);
ifil(3,j+1) =ifil(3,j)+nfiles;
if run_smoother
nfiles = ceil(nBlockPerCPU(j)/MAX_nsmoo);
ifil(1,j+1) =ifil(1,j)+nfiles;
nfiles = ceil(nBlockPerCPU(j)/MAX_ninno);
ifil(2,j+1) =ifil(2,j)+nfiles;
nfiles = ceil(nBlockPerCPU(j)/MAX_nerro);
ifil(3,j+1) =ifil(3,j)+nfiles;
end
if naK
nfiles = ceil(nBlockPerCPU(j)/MAX_naK);
ifil(4,j+1) =ifil(4,j)+nfiles;
......@@ -274,16 +277,16 @@ if ~isnumeric(options_.parallel),
leaveSlaveOpen = options_.parallel_info.leaveSlaveOpen;
if options_.parallel_info.leaveSlaveOpen == 0,
% Commenting for testing!!!
% options_.parallel_info.leaveSlaveOpen = 1; % Force locally to leave open remote matlab sessions (repeated pm3 calls)
options_.parallel_info.leaveSlaveOpen = 1; % Force locally to leave open remote matlab sessions (repeated pm3 calls)
end
end
if options_.smoother
pm3(endo_nbr,gend,ifil(1),B,'Smoothed variables',...
'',M_.endo_names(1:M_.orig_endo_nbr, :),'tit_tex',M_.endo_names,...
'',M_.endo_names(1:M_.orig_endo_nbr, :),M_.endo_names_tex,M_.endo_names,...
varlist,'SmoothedVariables',DirectoryName,'_smooth');
pm3(exo_nbr,gend,ifil(2),B,'Smoothed shocks',...
'',M_.exo_names,'tit_tex',M_.exo_names,...
'',M_.exo_names,M_.exo_names_tex,M_.exo_names,...
M_.exo_names,'SmoothedShocks',DirectoryName,'_inno');
if nvn
% needs to be fixed
......
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