dynare/matlab/PlotPosteriorDistributions.m

165 lines
6.3 KiB
Matlab

function oo_ = PlotPosteriorDistributions(estim_params_, M_, options_, bayestopt_, oo_)
% function PlotPosteriorDistributions()
% plots posterior distributions
%
% INPUTS
% estim_params_ [structure]
% M_ [structure]
% options_ [structure]
% bayestopt_ [structure]
% oo_ [structure]
%
% OUTPUTS
% oo_ [structure]
%
% SPECIAL REQUIREMENTS
% none
% Copyright © 2005-2018 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 <https://www.gnu.org/licenses/>.
OutputDirectoryName = CheckPath('Output',M_.dname);
TeX = options_.TeX;
nblck = options_.mh_nblck;
nvx = estim_params_.nvx;
nvn = estim_params_.nvn;
ncx = estim_params_.ncx;
ncn = estim_params_.ncn;
np = estim_params_.np ;
npar = nvx+nvn+ncx+ncn+np;
MaxNumberOfPlotPerFigure = 9;% The square root must be an integer!
nn = sqrt(MaxNumberOfPlotPerFigure);
figurename = 'Priors and posteriors';
if TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fidTeX = fopen([OutputDirectoryName '/' M_.fname '_PriorsAndPosteriors.tex'],'w');
fprintf(fidTeX,'%% TeX eps-loader file generated by PlotPosteriorDistributions.m (Dynare).\n');
fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
fprintf(fidTeX,' \n');
end
figunumber = 0;
subplotnum = 0;
for i=1:npar
subplotnum = subplotnum+1;
if subplotnum == 1
figunumber = figunumber+1;
hfig=dyn_figure(options_.nodisplay, 'Name', figurename);
end
[nam,texnam] = get_the_name(i, TeX, M_, estim_params_, options_);
[x2, f2, abscissa, dens, binf2, bsup2] = draw_prior_density(i, bayestopt_);
top2 = max(f2);
if i <= nvx
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;
oo_.prior_density.shocks_std.(name)(:,2) = f2;
if ~options_.mh_posterior_mode_estimation
pmod = oo_.posterior_mode.shocks_std.(name);
end
elseif i <= nvx+nvn
name = options_.varobs{estim_params_.nvn_observable_correspondence(i-nvx,1)};
x1 = oo_.posterior_density.measurement_errors_std.(name)(:,1);
f1 = oo_.posterior_density.measurement_errors_std.(name)(:,2);
oo_.prior_density.measurement_errors_std.(name)(:,1) = x2;
oo_.prior_density.measurement_errors_std.(name)(:,2) = f2;
if ~options_.mh_posterior_mode_estimation
pmod = oo_.posterior_mode.measurement_errors_std.(name);
end
elseif i <= nvx+nvn+ncx
j = i - (nvx+nvn);
k1 = estim_params_.corrx(j,1);
k2 = estim_params_.corrx(j,2);
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;
oo_.prior_density.shocks_corr.(name)(:,2) = f2;
if ~options_.mh_posterior_mode_estimation
pmod = oo_.posterior_mode.shocks_corr.(name);
end
elseif i <= nvx+nvn+ncx+ncn
j = i - (nvx+nvn+ncx);
k1 = estim_params_.corrn(j,1);
k2 = estim_params_.corrn(j,2);
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;
oo_.prior_density.measurement_errors_corr.(name)(:,2) = f2;
if ~options_.mh_posterior_mode_estimation
pmod = oo_.posterior_mode.measurement_errors_corr.(name);
end
else
j = i - (nvx+nvn+ncx+ncn);
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;
oo_.prior_density.parameters.(name)(:,2) = f2;
if ~options_.mh_posterior_mode_estimation
pmod = oo_.posterior_mode.parameters.(name);
end
end
top1 = max(f1);
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]);
hold on;
plot(x1, f1, '-k', 'linewidth', 2);
if ~options_.mh_posterior_mode_estimation
plot([pmod pmod], [0.0 1.1*top0], '--g', 'linewidth', 2);
end
box on
axis([borneinf bornesup 0 1.1*top0])
if TeX
title(texnam, 'Interpreter', 'latex')
else
title(nam, 'Interpreter', 'none')
end
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');
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,'\\end{figure}\n');
fprintf(fidTeX,' \n');
if i == npar
fprintf(fidTeX,'%% End of TeX file.\n');
fclose(fidTeX);
end
end
subplotnum = 0;
end
end