546 lines
28 KiB
Matlab
546 lines
28 KiB
Matlab
function plot(M_, params, idemoments, idehess, idemodel, idelre, advanced, tittxt, name, IdentifDirectoryName, fname, options_, estim_params_, bayestopt_, tit_TeX, name_tex)
|
|
% plot(M_, params,idemoments,idehess,idemodel, idelre, advanced, tittxt, name, IdentifDirectoryName, fname, options_, estim_params_, bayestopt_, tit_TeX, name_tex)
|
|
%
|
|
% INPUTS
|
|
% o M_ [structure] model
|
|
% o params [array] parameter values for identification checks
|
|
% o idemoments [structure] identification results for the moments
|
|
% o idehess [structure] identification results for the Hessian
|
|
% o idemodel [structure] identification results for the reduced form solution
|
|
% o idelre [structure] identification results for the LRE model
|
|
% o advanced [integer] flag for advanced identification checks
|
|
% o tittxt [char] name of the results to plot
|
|
% o name [char] list of parameter names
|
|
% o IdentifDirectoryName [char] directory name
|
|
% o fname [char] file name
|
|
% o options_ [structure] structure describing the current options
|
|
% o estim_params_ [structure] characterizing parameters to be estimated
|
|
% o bayestopt_ [structure] describing the priors
|
|
% o tittxt [char] TeX-name of the results to plot
|
|
% o name_tex [char] TeX-names of the parameters
|
|
%
|
|
% OUTPUTS
|
|
% None
|
|
%
|
|
% SPECIAL REQUIREMENTS
|
|
% None
|
|
|
|
% Copyright © 2008-2023 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/>.
|
|
|
|
if nargin <14 || isempty(tit_TeX)
|
|
tit_TeX=tittxt;
|
|
end
|
|
|
|
if nargin <15
|
|
name_tex=name;
|
|
end
|
|
|
|
[SampleSize, nparam]=size(params);
|
|
si_dMOMENTSnorm = idemoments.si_dMOMENTSnorm;
|
|
si_dTAUnorm = idemodel.si_dREDUCEDFORMnorm;
|
|
si_dLREnorm = idelre.si_dDYNAMICnorm;
|
|
|
|
tittxt1=regexprep(tittxt, ' ', '_');
|
|
tittxt1=strrep(tittxt1, '.', '');
|
|
if SampleSize == 1
|
|
hh_fig = dyn_figure(options_.nodisplay,'Name',[tittxt, ' - Identification using info from observables']);
|
|
subplot(211)
|
|
mmm = (idehess.ide_strength_dMOMENTS);
|
|
[~, is] = sort(mmm);
|
|
if ~all(isnan(idehess.ide_strength_dMOMENTS_prior)) ...
|
|
&& ~(nparam == 1 && ~isoctave && matlab_ver_less_than('9.7')) % MATLAB < R2019b does not accept bar(1, [2 3])
|
|
bar(1:nparam,log([idehess.ide_strength_dMOMENTS(:,is)' idehess.ide_strength_dMOMENTS_prior(:,is)']))
|
|
else
|
|
bar(1:nparam,log(idehess.ide_strength_dMOMENTS(:,is)'))
|
|
end
|
|
hold on
|
|
plot((1:length(idehess.ide_strength_dMOMENTS(:,is)))-0.15,log(idehess.ide_strength_dMOMENTS(:,is)'),'o','MarkerSize',7,'MarkerFaceColor',[0 0 0],'MarkerEdgeColor','none')
|
|
plot((1:length(idehess.ide_strength_dMOMENTS_prior(:,is)))+0.15,log(idehess.ide_strength_dMOMENTS_prior(:,is)'),'o','MarkerSize',7,'MarkerFaceColor',[0 0 0],'MarkerEdgeColor','none')
|
|
if any(isinf(log(idehess.ide_strength_dMOMENTS(idehess.identified_parameter_indices))))
|
|
%-Inf, i.e. 0 strength
|
|
inf_indices=find(isinf(log(idehess.ide_strength_dMOMENTS(idehess.identified_parameter_indices))) & log(idehess.ide_strength_dMOMENTS(idehess.identified_parameter_indices))<0);
|
|
inf_pos=ismember(is,idehess.identified_parameter_indices(inf_indices));
|
|
plot(find(inf_pos)-0.15,zeros(sum(inf_pos),1),'o','MarkerSize',7,'MarkerFaceColor',[1 0 0],'MarkerEdgeColor',[0 0 0])
|
|
%+Inf, i.e. Inf strength
|
|
inf_indices=find(isinf(log(idehess.ide_strength_dMOMENTS(idehess.identified_parameter_indices))) & log(idehess.ide_strength_dMOMENTS(idehess.identified_parameter_indices))>0);
|
|
inf_pos=ismember(is,idehess.identified_parameter_indices(inf_indices));
|
|
plot(find(inf_pos)-0.15,zeros(sum(inf_pos),1),'o','MarkerSize',7,'MarkerFaceColor',[1 1 1],'MarkerEdgeColor',[0 0 0])
|
|
end
|
|
if any(isinf(log(idehess.ide_strength_dMOMENTS_prior(idehess.identified_parameter_indices))))
|
|
%-Inf, i.e. 0 strength
|
|
inf_indices=find(isinf(log(idehess.ide_strength_dMOMENTS_prior(idehess.identified_parameter_indices))) & log(idehess.ide_strength_dMOMENTS_prior(idehess.identified_parameter_indices))<0);
|
|
inf_pos=ismember(is,idehess.identified_parameter_indices(inf_indices));
|
|
plot(find(inf_pos)+0.15,zeros(sum(inf_pos),1),'o','MarkerSize',7,'MarkerFaceColor',[1 0 0],'MarkerEdgeColor',[0 0 0])
|
|
%+Inf, i.e. 0 strength
|
|
inf_indices=find(isinf(log(idehess.ide_strength_dMOMENTS_prior(idehess.identified_parameter_indices))) & log(idehess.ide_strength_dMOMENTS_prior(idehess.identified_parameter_indices))>0);
|
|
inf_pos=ismember(is,idehess.identified_parameter_indices(inf_indices));
|
|
plot(find(inf_pos)+0.15,zeros(sum(inf_pos),1),'o','MarkerSize',7,'MarkerFaceColor',[1 1 1],'MarkerEdgeColor',[0 0 0])
|
|
end
|
|
set(gca,'xlim',[0 nparam+1])
|
|
set(gca,'xticklabel','')
|
|
dy = get(gca,'ylim');
|
|
for ip=1:nparam
|
|
if options_.TeX
|
|
text(ip,dy(1),name_tex{is(ip)},'rotation',90,'HorizontalAlignment','right','interpreter','latex')
|
|
else
|
|
text(ip,dy(1),name{is(ip)},'rotation',90,'HorizontalAlignment','right','interpreter','none')
|
|
end
|
|
end
|
|
if ~all(isnan(idehess.ide_strength_dMOMENTS_prior))
|
|
legend('relative to param value','relative to prior std','Location','Best')
|
|
else
|
|
legend('relative to param value','Location','Best')
|
|
end
|
|
if idehess.flag_score
|
|
title('Identification strength with asymptotic Information matrix (log-scale)')
|
|
else
|
|
title('Identification strength with moments Information matrix (log-scale)')
|
|
end
|
|
|
|
subplot(212)
|
|
if ~all(isnan(idehess.deltaM_prior)) ...
|
|
&& ~(nparam == 1 && ~isoctave && matlab_ver_less_than('9.7')) % MATLAB < R2019b does not accept bar(1, [2 3])
|
|
bar(1:nparam, log([idehess.deltaM(is) idehess.deltaM_prior(is)]))
|
|
else
|
|
bar(1:nparam, log([idehess.deltaM(is)]))
|
|
end
|
|
hold on
|
|
plot((1:length(idehess.deltaM(is)))-0.15,log(idehess.deltaM(is)'),'o','MarkerSize',7,'MarkerFaceColor',[0 0 0],'MarkerEdgeColor','none')
|
|
plot((1:length(idehess.deltaM_prior(is)))+0.15,log(idehess.deltaM_prior(is)'),'o','MarkerSize',7,'MarkerFaceColor',[0 0 0],'MarkerEdgeColor','none')
|
|
inf_pos=find(isinf(log(idehess.deltaM)));
|
|
if ~isempty(inf_pos)
|
|
inf_indices=~ismember(inf_pos,idehess.sensitivity_zero_pos);
|
|
inf_pos=ismember(is,inf_pos(inf_indices));
|
|
plot(find(inf_pos)-0.15,zeros(sum(inf_pos),1),'o','MarkerSize',7,'MarkerFaceColor',[1 1 1],'MarkerEdgeColor',[0 0 0])
|
|
end
|
|
inf_pos=find(isinf(log(idehess.deltaM_prior)));
|
|
if ~isempty(inf_pos)
|
|
inf_indices=~ismember(inf_pos,idehess.sensitivity_zero_pos);
|
|
inf_pos=ismember(is,inf_pos(inf_indices));
|
|
plot(find(inf_pos)+0.15,zeros(sum(inf_pos),1),'o','MarkerSize',7,'MarkerFaceColor',[1 1 1],'MarkerEdgeColor',[0 0 0])
|
|
end
|
|
set(gca,'xlim',[0 nparam+1])
|
|
set(gca,'xticklabel','')
|
|
dy = get(gca,'ylim');
|
|
for ip=1:nparam
|
|
if options_.TeX
|
|
text(ip,dy(1),name_tex{is(ip)},'rotation',90,'HorizontalAlignment','right','interpreter','latex')
|
|
else
|
|
text(ip,dy(1),name{is(ip)},'rotation',90,'HorizontalAlignment','right','interpreter','none')
|
|
end
|
|
end
|
|
if ~all(isnan(idehess.deltaM_prior))
|
|
legend('relative to param value','relative to prior std','Location','Best')
|
|
else
|
|
legend('relative to param value','Location','Best')
|
|
end
|
|
if idehess.flag_score
|
|
title('Sensitivity component with asymptotic Information matrix (log-scale)')
|
|
else
|
|
title('Sensitivity component with moments Information matrix (log-scale)')
|
|
end
|
|
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
|
|
fidTeX = fopen([IdentifDirectoryName '/' fname '_ident_strength_' tittxt1,'.tex'],'w');
|
|
fprintf(fidTeX,'%% TeX eps-loader file generated by identification.plot.m (Dynare).\n');
|
|
fprintf(fidTeX,['%% ' datestr(now,0) '\n\n']);
|
|
fprintf(fidTeX,'\\begin{figure}[H]\n');
|
|
fprintf(fidTeX,'\\centering \n');
|
|
fprintf(fidTeX,'\\includegraphics[width=0.8\\textwidth]{%s_ident_strength_%s}\n',[IdentifDirectoryName '/' fname],tittxt1);
|
|
fprintf(fidTeX,'\\caption{%s - Identification using info from observables.}',tit_TeX);
|
|
fprintf(fidTeX,'\\label{Fig:ident:%s}\n',deblank(tittxt));
|
|
fprintf(fidTeX,'\\end{figure}\n\n');
|
|
fprintf(fidTeX,'%% End Of TeX file. \n');
|
|
fclose(fidTeX);
|
|
end
|
|
dyn_saveas(hh_fig,[IdentifDirectoryName '/' fname '_ident_strength_' tittxt1],options_.nodisplay,options_.graph_format);
|
|
|
|
if advanced
|
|
if ~options_.nodisplay
|
|
skipline()
|
|
disp('Plotting advanced diagnostics')
|
|
end
|
|
if all(isnan([si_dMOMENTSnorm';si_dTAUnorm';si_dLREnorm']))
|
|
fprintf('\nIDENTIFICATION: Skipping sensitivity plot, because standard deviation of parameters is NaN, possibly due to the use of ML.\n')
|
|
else
|
|
hh_fig = dyn_figure(options_.nodisplay,'Name',[tittxt, ' - Sensitivity plot']);
|
|
subplot(211)
|
|
mmm = (si_dMOMENTSnorm)'./max(si_dMOMENTSnorm);
|
|
mmm1 = (si_dTAUnorm)'./max(si_dTAUnorm);
|
|
mmm=[mmm mmm1];
|
|
mmm1 = (si_dLREnorm)'./max(si_dLREnorm);
|
|
offset=length(si_dTAUnorm)-length(si_dLREnorm);
|
|
mmm1 = [NaN(offset,1); mmm1];
|
|
mmm=[mmm mmm1];
|
|
|
|
bar(log(mmm(is,:).*100))
|
|
set(gca,'xlim',[0 nparam+1])
|
|
set(gca,'xticklabel','')
|
|
dy = get(gca,'ylim');
|
|
for ip=1:nparam
|
|
if options_.TeX
|
|
text(ip,dy(1),name_tex{is(ip)},'rotation',90,'HorizontalAlignment','right','interpreter','latex')
|
|
else
|
|
text(ip,dy(1),name{is(ip)},'rotation',90,'HorizontalAlignment','right','interpreter','none')
|
|
end
|
|
end
|
|
legend('Moments','Model','LRE model','Location','Best')
|
|
title('Sensitivity bars using derivatives (log-scale)')
|
|
dyn_saveas(hh_fig,[IdentifDirectoryName '/' fname '_sensitivity_' tittxt1 ],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
|
|
fidTeX = fopen([IdentifDirectoryName '/' fname '_sensitivity_' tittxt1,'.tex'],'w');
|
|
fprintf(fidTeX,'%% TeX eps-loader file generated by identification.plot.m (Dynare).\n');
|
|
fprintf(fidTeX,['%% ' datestr(now,0) '\n\n']);
|
|
fprintf(fidTeX,'\\begin{figure}[H]\n');
|
|
fprintf(fidTeX,'\\centering \n');
|
|
fprintf(fidTeX,'\\includegraphics[width=0.8\\textwidth]{%s_sensitivity_%s}\n',[IdentifDirectoryName '/' fname],tittxt1);
|
|
fprintf(fidTeX,'\\caption{%s - Sensitivity plot.}',tit_TeX);
|
|
fprintf(fidTeX,'\\label{Fig:sensitivity:%s}\n',deblank(tittxt));
|
|
fprintf(fidTeX,'\\end{figure}\n\n');
|
|
fprintf(fidTeX,'%% End Of TeX file. \n');
|
|
fclose(fidTeX);
|
|
end
|
|
end
|
|
% identificaton patterns
|
|
for j=1:size(idemoments.cosndMOMENTS,2)
|
|
pax=NaN(nparam,nparam);
|
|
for i=1:nparam
|
|
namx='';
|
|
for in=1:j
|
|
dumpindx = idemoments.pars{i,j}(in);
|
|
if isnan(dumpindx)
|
|
namx=[namx ' ' sprintf('%-15s','--')];
|
|
else
|
|
if options_.TeX
|
|
namx=[namx ' ' sprintf('%-15s',name_tex{dumpindx})];
|
|
else
|
|
namx=[namx ' ' sprintf('%-15s',name{dumpindx})];
|
|
end
|
|
pax(i,dumpindx)=idemoments.cosndMOMENTS(i,j);
|
|
end
|
|
end
|
|
end
|
|
hh_fig = dyn_figure(options_.nodisplay,'Name',[tittxt,' - Collinearity patterns with ', int2str(j) ,' parameter(s)']);
|
|
imagesc(pax,[0 1]);
|
|
set(gca,'xticklabel','')
|
|
set(gca,'yticklabel','')
|
|
for ip=1:nparam
|
|
if options_.TeX
|
|
text(ip,(0.5),name_tex{ip},'rotation',90,'HorizontalAlignment','left','interpreter','latex')
|
|
text(0.5,ip,name_tex{ip},'rotation',0,'HorizontalAlignment','right','interpreter','latex')
|
|
else
|
|
text(ip,(0.5),name{ip},'rotation',90,'HorizontalAlignment','left','interpreter','none')
|
|
text(0.5,ip,name{ip},'rotation',0,'HorizontalAlignment','right','interpreter','none')
|
|
end
|
|
end
|
|
colorbar;
|
|
colormap('jet');
|
|
ax=colormap;
|
|
ax(1,:)=[0.9 0.9 0.9];
|
|
colormap(ax);
|
|
if nparam>10
|
|
set(gca,'xtick',(5:5:nparam))
|
|
set(gca,'ytick',(5:5:nparam))
|
|
end
|
|
set(gca,'xgrid','on')
|
|
set(gca,'ygrid','on')
|
|
xlabel([tittxt,' - Collinearity patterns with ', int2str(j) ,' parameter(s)'],'interpreter','none')
|
|
dyn_saveas(hh_fig,[ IdentifDirectoryName '/' fname '_ident_collinearity_' tittxt1 '_' int2str(j) ],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
|
|
fidTeX = fopen([ IdentifDirectoryName '/' fname '_ident_collinearity_' tittxt1 '_' int2str(j),'.tex'],'w');
|
|
fprintf(fidTeX,'%% TeX eps-loader file generated by identification.plot.m (Dynare).\n');
|
|
fprintf(fidTeX,['%% ' datestr(now,0) '\n\n']);
|
|
fprintf(fidTeX,'\\begin{figure}[H]\n');
|
|
fprintf(fidTeX,'\\centering \n');
|
|
fprintf(fidTeX,'\\includegraphics[width=0.8\\textwidth]{%s_ident_collinearity_%s_%u}\n',[IdentifDirectoryName '/' fname],tittxt1,j);
|
|
fprintf(fidTeX,'\\caption{%s - Collinearity patterns with %u parameter(s).}',tit_TeX,j);
|
|
fprintf(fidTeX,'\\label{Fig:collinearity:%s:%u_pars}\n',deblank(tittxt),j);
|
|
fprintf(fidTeX,'\\end{figure}\n\n');
|
|
fprintf(fidTeX,'%% End Of TeX file. \n');
|
|
fclose(fidTeX);
|
|
end
|
|
end
|
|
skipline()
|
|
[~,S,V]=svd(idehess.AHess,0);
|
|
S=diag(S);
|
|
if idehess.flag_score
|
|
if nparam<5
|
|
f1 = dyn_figure(options_.nodisplay,'Name',[tittxt,' - Identification patterns (Information matrix)']);
|
|
tex_tit_1=[tittxt,' - Identification patterns (Information matrix)'];
|
|
else
|
|
f1 = dyn_figure(options_.nodisplay,'Name',[tittxt,' - Identification patterns (Information matrix): SMALLEST SV']);
|
|
tex_tit_1=[tittxt,' - Identification patterns (Information matrix): SMALLEST SV'];
|
|
f2 = dyn_figure(options_.nodisplay,'Name',[tittxt,' - Identification patterns (Information matrix): HIGHEST SV']);
|
|
tex_tit_2=[tittxt,' - Identification patterns (Information matrix): HIGHEST SV'];
|
|
end
|
|
else
|
|
if nparam<5
|
|
f1 = dyn_figure(options_.nodisplay,'Name',[tittxt,' - Identification patterns (moments Information matrix)']);
|
|
tex_tit_1=[tittxt,' - Identification patterns (moments Information matrix)'];
|
|
else
|
|
f1 = dyn_figure(options_.nodisplay,'Name',[tittxt,' - Identification patterns (moments Information matrix): SMALLEST SV']);
|
|
tex_tit_1=[tittxt,' - Identification patterns (moments Information matrix): SMALLEST SV'];
|
|
f2 = dyn_figure(options_.nodisplay,'Name',[tittxt,' - Identification patterns (moments Information matrix): HIGHEST SV']);
|
|
tex_tit_2=[tittxt,' - Identification patterns (moments Information matrix): HIGHEST SV'];
|
|
end
|
|
end
|
|
for j=1:min(nparam,8)
|
|
if j<5
|
|
set(0,'CurrentFigure',f1),
|
|
jj=j;
|
|
else
|
|
set(0,'CurrentFigure',f2),
|
|
jj=j-4;
|
|
end
|
|
subplot(4,1,jj)
|
|
if j<5
|
|
bar(abs(V(:,end-j+1)))
|
|
Stit = S(end-j+1);
|
|
else
|
|
bar(abs(V(:,jj))),
|
|
Stit = S(jj);
|
|
end
|
|
set(gca,'xticklabel','')
|
|
if j==4 || j==nparam || j==8
|
|
for ip=1:nparam
|
|
if options_.TeX
|
|
text(ip,-0.02,name_tex{ip},'rotation',90,'HorizontalAlignment','right','interpreter','latex')
|
|
else
|
|
text(ip,-0.02,name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
|
|
end
|
|
end
|
|
end
|
|
title(['Singular value ',num2str(Stit)])
|
|
end
|
|
dyn_saveas(f1,[ IdentifDirectoryName '/' fname '_ident_pattern_' tittxt1 '_1' ],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
|
|
fidTeX = fopen([ IdentifDirectoryName '/' fname '_ident_pattern_' tittxt1 '_1','.tex'],'w');
|
|
fprintf(fidTeX,'%% TeX eps-loader file generated by identification.plot.m (Dynare).\n');
|
|
fprintf(fidTeX,['%% ' datestr(now,0) '\n\n']);
|
|
fprintf(fidTeX,'\\begin{figure}[H]\n');
|
|
fprintf(fidTeX,'\\centering \n');
|
|
fprintf(fidTeX,'\\includegraphics[width=0.8\\textwidth]{%s_ident_pattern_%s_1}\n',[IdentifDirectoryName '/' fname],tittxt1);
|
|
fprintf(fidTeX,'\\caption{%s.}',tex_tit_1);
|
|
fprintf(fidTeX,'\\label{Fig:ident_pattern:%s:1}\n',tittxt1);
|
|
fprintf(fidTeX,'\\end{figure}\n\n');
|
|
fprintf(fidTeX,'%% End Of TeX file. \n');
|
|
fclose(fidTeX);
|
|
end
|
|
if nparam>4
|
|
dyn_saveas(f2,[ IdentifDirectoryName '/' fname '_ident_pattern_' tittxt1 '_2' ],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
|
|
fidTeX = fopen([ IdentifDirectoryName '/' fname '_ident_pattern_' tittxt1 '_2.tex'],'w');
|
|
fprintf(fidTeX,'%% TeX eps-loader file generated by identification.plot.m (Dynare).\n');
|
|
fprintf(fidTeX,['%% ' datestr(now,0) '\n\n']);
|
|
fprintf(fidTeX,'\\begin{figure}[H]\n');
|
|
fprintf(fidTeX,'\\centering \n');
|
|
fprintf(fidTeX,'\\includegraphics[width=0.8\\textwidth]{%s_ident_pattern_%s_2}\n',[IdentifDirectoryName '/' fname],tittxt1);
|
|
fprintf(fidTeX,'\\caption{%s.}',tex_tit_2);
|
|
fprintf(fidTeX,'\\label{Fig:ident_pattern:%s:2}\n',tittxt1);
|
|
fprintf(fidTeX,'\\end{figure}\n\n');
|
|
fprintf(fidTeX,'%% End Of TeX file. \n');
|
|
fclose(fidTeX);
|
|
end
|
|
end
|
|
end
|
|
|
|
else
|
|
hh_fig = dyn_figure(options_.nodisplay,'Name','MC sensitivities');
|
|
subplot(211)
|
|
mmm = (idehess.ide_strength_dMOMENTS);
|
|
[~, is] = sort(mmm);
|
|
mmm = mean(si_dMOMENTSnorm)';
|
|
mmm = mmm./max(mmm);
|
|
if advanced
|
|
mmm1 = mean(si_dTAUnorm)';
|
|
mmm=[mmm mmm1./max(mmm1)];
|
|
mmm1 = mean(si_dLREnorm)';
|
|
offset=size(si_dTAUnorm,2)-size(si_dLREnorm,2);
|
|
mmm1 = [NaN(offset,1); mmm1./max(mmm1)];
|
|
mmm=[mmm mmm1];
|
|
end
|
|
|
|
bar(mmm(is,:))
|
|
set(gca,'xlim',[0 nparam+1])
|
|
set(gca,'xticklabel','')
|
|
dy = get(gca,'ylim');
|
|
for ip=1:nparam
|
|
if options_.TeX
|
|
text(ip,dy(1),name_tex{is(ip)},'rotation',90,'HorizontalAlignment','right','interpreter','latex')
|
|
else
|
|
text(ip,dy(1),name{is(ip)},'rotation',90,'HorizontalAlignment','right','interpreter','none')
|
|
end
|
|
end
|
|
if advanced
|
|
legend('Moments','Model','LRE model','Location','Best')
|
|
end
|
|
title('MC mean of sensitivity measures')
|
|
dyn_saveas(hh_fig,[ IdentifDirectoryName '/' fname '_MC_sensitivity' ],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
|
|
fidTeX = fopen([ IdentifDirectoryName '/' fname '_MC_sensitivity.tex'],'w');
|
|
fprintf(fidTeX,'%% TeX eps-loader file generated by identification.plot.m (Dynare).\n');
|
|
fprintf(fidTeX,['%% ' datestr(now,0) '\n\n']);
|
|
fprintf(fidTeX,'\\begin{figure}[H]\n');
|
|
fprintf(fidTeX,'\\centering \n');
|
|
fprintf(fidTeX,'\\includegraphics[width=0.8\\textwidth]{%s_MC_sensitivity}\n',[IdentifDirectoryName '/' fname]);
|
|
fprintf(fidTeX,'\\caption{MC mean of sensitivity measures}');
|
|
fprintf(fidTeX,'\\label{Fig:_MC_sensitivity}\n');
|
|
fprintf(fidTeX,'\\end{figure}\n\n');
|
|
fprintf(fidTeX,'%% End Of TeX file. \n');
|
|
fclose(fidTeX);
|
|
end
|
|
|
|
if advanced
|
|
if ~options_.nodisplay
|
|
skipline()
|
|
disp('Displaying advanced diagnostics')
|
|
end
|
|
hh_fig = dyn_figure(options_.nodisplay,'Name','MC Condition Number');
|
|
subplot(221)
|
|
if isoctave
|
|
hist(log10(idemodel.cond))
|
|
else
|
|
histogram(log10(idemodel.cond))
|
|
end
|
|
title('log10 of Condition number in the model')
|
|
subplot(222)
|
|
if isoctave
|
|
hist(log10(idemoments.cond))
|
|
else
|
|
histogram(log10(idemoments.cond))
|
|
end
|
|
title('log10 of Condition number in the moments')
|
|
subplot(223)
|
|
if isoctave
|
|
hist(log10(idelre.cond))
|
|
else
|
|
histogram(log10(idelre.cond))
|
|
end
|
|
title('log10 of Condition number in the LRE model')
|
|
dyn_saveas(hh_fig,[IdentifDirectoryName '/' fname '_ident_COND' ],options_.nodisplay,options_.graph_format);
|
|
options_mcf.pvalue_ks = 0.1;
|
|
options_mcf.pvalue_corr = 0.001;
|
|
options_mcf.alpha2 = 0;
|
|
options_mcf.param_names = name;
|
|
options_mcf.param_names_tex = name_tex;
|
|
options_mcf.fname_ = fname;
|
|
options_mcf.OutputDirectoryName = IdentifDirectoryName;
|
|
options_mcf.beha_title = 'LOW condition nbr';
|
|
options_mcf.nobeha_title = 'HIGH condition nbr';
|
|
if options_.TeX
|
|
options_mcf.beha_title_latex = 'LOW condition nbr';
|
|
options_mcf.nobeha_title_latex = 'HIGH condition nbr';
|
|
end
|
|
options_mcf.amcf_name = 'MC_HighestCondNumberLRE';
|
|
options_mcf.amcf_title = 'MC Highest Condition Number LRE Model';
|
|
options_mcf.title = 'MC Highest Condition Number LRE Model';
|
|
ncut=floor(SampleSize/10*9);
|
|
[~,is]=sort(idelre.cond);
|
|
gsa.monte_carlo_filtering_analysis(params, is(1:ncut), is(ncut+1:end), options_mcf, M_, options_, bayestopt_, estim_params_);
|
|
options_mcf.amcf_name = 'MC_HighestCondNumberModel';
|
|
options_mcf.amcf_title = 'MC Highest Condition Number Model Solution';
|
|
options_mcf.title = 'MC Highest Condition Number Model Solution';
|
|
[~,is]=sort(idemodel.cond);
|
|
gsa.monte_carlo_filtering_analysis(params, is(1:ncut), is(ncut+1:end), options_mcf, M_, options_, bayestopt_, estim_params_);
|
|
options_mcf.amcf_name = 'MC_HighestCondNumberMoments';
|
|
options_mcf.amcf_title = 'MC Highest Condition Number Model Moments';
|
|
options_mcf.title = 'MC Highest Condition Number Model Moments';
|
|
[~,is]=sort(idemoments.cond);
|
|
gsa.monte_carlo_filtering_analysis(params, is(1:ncut), is(ncut+1:end), options_mcf, M_, options_, bayestopt_, estim_params_);
|
|
|
|
if nparam<5
|
|
f1 = dyn_figure(options_.nodisplay,'Name',[tittxt,' - MC Identification patterns (moments): HIGHEST SV']);
|
|
tex_tit_1=[tittxt,' - MC Identification patterns (moments): HIGHEST SV'];
|
|
else
|
|
f1 = dyn_figure(options_.nodisplay,'Name',[tittxt,' - MC Identification patterns (moments): SMALLEST SV']);
|
|
tex_tit_1=[tittxt,' - MC Identification patterns (moments): SMALLEST SV'];
|
|
f2 = dyn_figure(options_.nodisplay,'Name',[tittxt,' - MC Identification patterns (moments): HIGHEST SV']);
|
|
tex_tit_2=[tittxt,' - MC Identification patterns (moments): HIGHEST SV'];
|
|
end
|
|
nplots=min(nparam,8);
|
|
if nplots>4
|
|
nsubplo=ceil(nplots/2);
|
|
else
|
|
nsubplo=nplots;
|
|
end
|
|
for j=1:nplots
|
|
if (nparam>4 && j<=ceil(nplots/2)) || nparam<5
|
|
set(0,'CurrentFigure',f1),
|
|
jj=j;
|
|
VVV=squeeze(abs(idemoments.V(:,:,end-j+1)));
|
|
SSS = idemoments.S(:,end-j+1);
|
|
else
|
|
set(0,'CurrentFigure',f2),
|
|
jj=j-ceil(nplots/2);
|
|
VVV=squeeze(abs(idemoments.V(:,:,jj)));
|
|
SSS = idemoments.S(:,jj);
|
|
end
|
|
subplot(nsubplo,1,jj)
|
|
post_median=NaN(1,nparam);
|
|
hpd_interval=NaN(nparam,2);
|
|
for i=1:nparam
|
|
[~, post_median(:,i), ~, hpd_interval(i,:)] = posterior_moments(VVV(:,i),0,0.9);
|
|
end
|
|
bar(post_median)
|
|
hold on, plot(hpd_interval,'--*r'),
|
|
Stit=mean(SSS);
|
|
|
|
set(gca,'xticklabel','')
|
|
if j==4 || j==nparam || j==8
|
|
for ip=1:nparam
|
|
if options_.TeX
|
|
text(ip,-0.02,name_tex{ip},'rotation',90,'HorizontalAlignment','right','interpreter','latex')
|
|
else
|
|
text(ip,-0.02,name{ip},'rotation',90,'HorizontalAlignment','right','interpreter','none')
|
|
end
|
|
end
|
|
end
|
|
title(['MEAN Singular value ',num2str(Stit)])
|
|
end
|
|
dyn_saveas(f1,[IdentifDirectoryName '/' fname '_MC_ident_pattern_1' ],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
|
|
fidTeX = fopen([IdentifDirectoryName '/' fname '_MC_ident_pattern_1.tex'],'w');
|
|
fprintf(fidTeX,'%% TeX eps-loader file generated by identification.plot.m (Dynare).\n');
|
|
fprintf(fidTeX,['%% ' datestr(now,0) '\n\n']);
|
|
fprintf(fidTeX,'\\begin{figure}[H]\n');
|
|
fprintf(fidTeX,'\\centering \n');
|
|
fprintf(fidTeX,'\\includegraphics[width=0.8\\textwidth]{%s_MC_ident_pattern_1}\n',[IdentifDirectoryName '/' fname]);
|
|
fprintf(fidTeX,'\\caption{%s.}',tex_tit_1);
|
|
fprintf(fidTeX,'\\label{Fig:MC_ident_pattern:1}\n');
|
|
fprintf(fidTeX,'\\end{figure}\n\n');
|
|
fprintf(fidTeX,'%% End Of TeX file. \n');
|
|
fclose(fidTeX);
|
|
end
|
|
if nparam>4
|
|
dyn_saveas(f2,[ IdentifDirectoryName '/' fname '_MC_ident_pattern_2' ],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
|
|
fidTeX = fopen([ IdentifDirectoryName '/' fname '_MC_ident_pattern_2.tex'],'w');
|
|
fprintf(fidTeX,'%% TeX eps-loader file generated by identification.plot.m (Dynare).\n');
|
|
fprintf(fidTeX,['%% ' datestr(now,0) '\n\n']);
|
|
fprintf(fidTeX,'\\begin{figure}[H]\n');
|
|
fprintf(fidTeX,'\\centering \n');
|
|
fprintf(fidTeX,'\\includegraphics[width=0.8\\textwidth]{%s_MC_ident_pattern_2}\n',[IdentifDirectoryName '/' fname]);
|
|
fprintf(fidTeX,'\\caption{%s.}',tex_tit_2);
|
|
fprintf(fidTeX,'\\label{Fig:MC_ident_pattern:2}\n');
|
|
fprintf(fidTeX,'\\end{figure}\n\n');
|
|
fprintf(fidTeX,'%% End Of TeX file. \n');
|
|
fclose(fidTeX);
|
|
end
|
|
end
|
|
end
|
|
end
|