Added posterior impulse response functions.
git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@477 ac1d8469-bf42-47a9-8791-bf33cf982152time-shift
adjemian
parent
8145b7e3f5
commit
a6ec6bd2ec
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@ -2,7 +2,6 @@ function PosteriorIRF()
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% stephane.adjemian@ens.fr [09-25-2005]
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global options_ estim_params_ oo_ M_
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nvx = estim_params_.nvx;
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nvn = estim_params_.nvn;
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ncx = estim_params_.ncx;
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@ -10,7 +9,12 @@ ncn = estim_params_.ncn;
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np = estim_params_.np ;
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npar = nvx+nvn+ncx+ncn+np;
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offset = npar-np;
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%%
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MaxNumberOfPlotPerFigure = 4;% The square root must be an integer!
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nn = sqrt(MaxNumberOfPlotPerFigure);
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%%
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CheckPath('Plots\IRFs');
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CheckPath('metropolis\IRFs');
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DirectoryName = CheckPath('metropolis');
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load([ DirectoryName '\' M_.fname '_mh_history'])
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FirstMhFile = record.KeepedDraws.FirstMhFile;
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@ -20,26 +24,28 @@ TotalNumberOfMhDraws = sum(record.MhDraws(:,1));
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NumberOfDraws = TotalNumberOfMhDraws-floor(options_.mh_drop*TotalNumberOfMhDraws);
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clear record;
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MAX_nruns = ceil(options_.MaxNumberOfBytes/(npar+2)/8);
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MAX_nirfs = ceil(options_.MaxNumberOfBytes/(options_.irf*length(oo_.steady_state)*M_.exo_nbr)/8);
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MAX_nirfs = ceil(options_.MaxNumberOfBytes/(options_.irf*length(oo_.steady_state)*M_.exo_nbr)/8)+50;
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%%
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B = round(0.25*NumberOfDraws);
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if B <= MAX_nirfs
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stock_irf = zeros(options_.irf,size(M_.endo_names,1),M_.exo_nbr,B);
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elseif nvn & B > MAX_nirfs
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stock_irf = zeros(options_.irf,size(M_.endo_names,1),M_.exo_nbr,MAX_nirfs);
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end
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%%
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irun = 0;
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ifil = 1;
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h = waitbar(0,'Bayesian IRFs...');
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if B >= MAX_nirfs
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stock_irf = zeros(options_.irf,M_.endo_nbr,M_.exo_nbr,MAX_nirfs);
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else
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stock_irf = zeros(options_.irf,M_.endo_nbr,M_.exo_nbr,B);
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end
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for b=1:B
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irun = irun+1;
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deep = GetOneDraw(NumberOfDraws,FirstMhFile,LastMhFile,FirstLine,MAX_nruns,DirectoryName);
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M_.params(estim_params_.param_vals(:,1)) = deep(offset+1:end);
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dr = resol(oo_.steady_state,0)
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dr = resol(oo_.steady_state,0);
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if nvx
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ip = 1;
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for i=1:nvx
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@ -66,9 +72,9 @@ for b=1:B
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if options_.relative_irf
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y = 100*y/cs(i,i);
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end
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for j = 1:size(M_.endo_names,1)
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for j = 1:M_.endo_nbr%size(M_.endo_names,1)
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if max(y(j,:)) - min(y(j,:)) > 1e-10
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stock_irf(:,j,i,b) = transpose(y(j,:));
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stock_irf(:,j,i,irun) = transpose(y(j,:));
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end
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end
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end
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@ -85,13 +91,31 @@ for b=1:B
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end
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ifil = ifil-1;
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close(h)
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varlist = options_.varlist;
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if isempty(varlist)
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varlist = M_.endo_names;
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SelecVariables = transpose(1:M_.endo_nbr);
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nvar = M_.endo_nbr;
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else
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nvar = size(varlist,1);
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SelecVariables = [];
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for i=1:nvar
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if ~isempty(strmatch(varlist(i,:),M_.endo_names,'exact'))
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SelecVariables = [SelecVariables;strmatch(varlist(i,:),M_.endo_names,'exact')];
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end
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end
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end
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MeanIRF = zeros(options_.irf,nvar,M_.exo_nbr);
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MedianIRF = zeros(options_.irf,nvar,M_.exo_nbr);
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StdIRF = zeros(options_.irf,nvar,M_.exo_nbr);
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DistribIRF = zeros(options_.irf,9,nvar,M_.exo_nbr);
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HPDIRF = zeros(options_.irf,2,nvar,M_.exo_nbr);
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if options_.TeX
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varlist_TeX = [];
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for i=1:nvar
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varlist_TeX = strvcat(varlist_TeX,M_.endo_names_tex(SelecVariables(i),:));
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end
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end
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fprintf('MH: Posterior IRFs...\n');
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tit(M_.exo_names_orig_ord,:) = M_.exo_names;
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for i = 1:M_.exo_nbr
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@ -106,8 +130,8 @@ for i = 1:M_.exo_nbr
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StartLine = StartLine+DeProfundis;
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end
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[MeanIRF(k,j,i),MedianIRF(k,j,i),VarIRF(k,j,i),HPDIRF(k,:,j,i),DistribIRF(k,:,j,i)] = posterior_moments(tmp,0);
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disp([' Variable: ' deblank(M_.endo_names(SelecVariables(j),:)) ', orthogonalized shock to ' deblank(tit(i,:))])
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end
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disp([' Variable: ' deblank(M_.endo_names(SelecVariables(j),:)) ', orthogonalized shock to ' deblank(tit(i,:))])
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end
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end
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clear stock_irf;
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@ -122,179 +146,79 @@ for i = 1:M_.exo_nbr
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eval(['oo_.PosteriorIRF.HPDsup.' name ' = HPDIRF(:,2,j,i);']);
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end
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end
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return
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%%
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%% Finally i build the plots.
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%%
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if TeX
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fidTeX = fopen([M_.fname '_BayesianIRF.TeX'],'w');
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if options_.TeX
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fidTeX = fopen([M_.dname '\Plots\IRFs\' M_.fname '_BayesianIRF.TeX'],'w');
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fprintf(fidTeX,'%% TeX eps-loader file generated by PosteriorIRF.m (Dynare).\n');
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fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
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fprintf(fidTeX,' \n');
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titTeX(M_.exo_names_orig_ord,:) = M_.exo_names_tex;
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end
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if TeX; titTeX(M_.exo_name_orig_ord,:) = M_.exo_names_tex; end;
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% $$$ for i=1:M_.exo_nbr
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% $$$ number_of_plots_to_draw = 0;
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% $$$ index = [];
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% $$$ for j=1:nvar
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% $$$ if MeanIRF(1,j,i)
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% $$$ number_of_plots_to_draw = number_of_plots_to_draw + 1;
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% $$$ index = cat(1,index,j);
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% $$$ end
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% $$$ end
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% $$$ [nbplt,nr,nc,lr,lc,nstar] = pltorg(number_of_plots_to_draw);
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% $$$ if nbplt == 1
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% $$$ if options_.relative_irf
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% $$$ hh = figure('Name',['Relative response to orthogonalized' ...
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% $$$ ' shock to ' tit(i,:)]);
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% $$$ else
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% $$$ hh = figure('Name',['Orthogonalized shock to ' tit(i, ...
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% $$$ :)]);
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% $$$ end
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% $$$ NAMES = [];
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% $$$ if TeX; TEXNAMES = []; end;
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% $$$ for j=1:number_of_plots_to_draw
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% $$$ set(0,'CurrentFigure',hh)
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% $$$ subplot(nr,nc,j);
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% $$$ plot([1 options_.irf],[0 0],'-r','linewidth',0.5);
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% $$$ hold on
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% $$$ for k = 1:9
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% $$$ plot(1:options_.irf,DistribIRF(:,index(j),i,k),'-g','linewidth',0.5)
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% $$$ end
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% $$$ plot(1:options_.irf,MeanIRF(:,index(j),i),'-k','linewidth',1)
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% $$$ xlim([1 options_.irf]);
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% $$$ hold off
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% $$$ name = deblank(M_.endo_names(SelecVariables(index(j)),:));
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% $$$ NAMES = strvcat(NAMES,name);
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% $$$ if TeX
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% $$$ texname = deblank(M_.endo_names_tex(SelecVariables(index(j)),:));
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% $$$ TEXNAMES = strvcat(TEXNAMES,['$' texname '$']);
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% $$$ end
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% $$$ title(name,'Interpreter','none')
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% $$$ end
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% $$$ eval(['print -depsc2 ' M_.fname '_Bayesian_IRF_' deblank(tit(i,:))]);
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% $$$ eval(['print -dpdf ' M_.fname '_Bayesian_IRF_' deblank(tit(i,:))]);
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% $$$ saveas(hh,[M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) '.fig']);
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% $$$ if options_.nograph, close(hh), end
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% $$$ if TeX
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% $$$ fprintf(fidTeX,'\\begin{figure}[H]\n');
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% $$$ for jj = 1:number_of_plots_to_draw
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% $$$ fprintf(fidTeX,['\\psfrag{%s}[1][][0.5][0]{%s}\n'],deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
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% $$$ end
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% $$$ fprintf(fidTeX,'\\centering \n');
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% $$$ fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_Bayesian_IRF_%s}\n',M_.fname,deblank(tit(i,:)));
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% $$$ if options_.relative_irf
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% $$$ fprintf(fidTeX,['\\caption{Bayesian relative' ...
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% $$$ ' IRF.}']);
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% $$$ else
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% $$$ fprintf(fidTeX,'\\caption{Bayesian IRF.}');
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% $$$ end
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% $$$ fprintf(fidTeX,'\\label{Fig:BayesianIRF:%s}\n',deblank(tit(i,:)));
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% $$$ fprintf(fidTeX,'\\end{figure}\n');
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% $$$ fprintf(fidTeX,' \n');
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% $$$ end
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% $$$ elseif nbplt > 1
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% $$$ for fig = 1:nbplt-1
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% $$$ if options_.relative_irf
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% $$$ hh = figure('Name',['Relative response to orthogonalized' ...
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% $$$ ' shock to ' tit(i,:) ' figure ' int2str(fig) '.']);
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% $$$ else
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% $$$ hh = figure('Name',['Orthogonalized shock to ' tit(i,:) ...
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% $$$ ' figure ' int2str(fig) '.']);
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% $$$ end
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% $$$ NAMES = [];
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% $$$ if TeX; TEXNAMES = []; end;
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% $$$ for j=1:nstar
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% $$$ jj = (fig-1)*nstar + j;
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% $$$ subplot(nr,nc,j);
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% $$$ plot([1 options_.irf],[0 0],'-r','linewidth',0.5);
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% $$$ hold on
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% $$$ for k = 1:9
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% $$$ plot(1:options_.irf,DistribIRF(:,index(jj),i,k),'-g','linewidth',0.5)
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% $$$ end
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% $$$ plot(1:options_.irf,MeanIRF(:,index(jj),i),'-k','linewidth',1)
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% $$$ xlim([1 options_.irf]);
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% $$$ hold off
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% $$$ name = deblank(M_.endo_names(SelecVariables(index(jj)),:));
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% $$$ NAMES = strvcat(NAMES,name);
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% $$$ if TeX
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% $$$ texname = deblank(M_.endo_names_tex(SelecVariables(index(jj)),:));
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% $$$ TEXNAMES = strvcat(TEXNAMES,['$' texname '$']);
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% $$$ end
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% $$$ title(name,'Interpreter','none')
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% $$$ end
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% $$$ eval(['print -depsc2 ' M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) int2str(fig)]);
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% $$$ eval(['print -dpdf ' M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) int2str(fig)]);
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% $$$ saveas(hh,[M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) int2str(fig) '.fig']);
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% $$$ if options_.nograph, close(hh), end
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% $$$ if TeX
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% $$$ fprintf(fidTeX,'\\begin{figure}[H]\n');
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% $$$ for jj = 1:nstar
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% $$$ fprintf(fidTeX,['\\psfrag{%s}[1][][0.5][0]{%s}\n'],deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
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% $$$ end
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% $$$ fprintf(fidTeX,'\\centering \n');
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% $$$ fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_Bayesian_IRF_%s%s}\n',M_.fname,deblank(tit(i,:)),int2str(fig));
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% $$$ if options_.relative_irf == 1
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% $$$ fprintf(fidTeX,['\\caption{Bayesian relative' ...
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% $$$ ' IRF.}']);
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% $$$ else
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% $$$ fprintf(fidTeX,'\\caption{Bayesian IRF.}');
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% $$$ end
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% $$$ fprintf(fidTeX,'\\label{Fig:BayesianIRF:%s:%s}\n',deblank(tit(i,:)), int2str(fig));
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% $$$ fprintf(fidTeX,'\\end{figure}\n');
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% $$$ fprintf(fidTeX,' \n');
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% $$$ end
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% $$$ end
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% $$$ hh = figure('Name',['Orthogonalized shock to ' tit(i,:) ' figure ' int2str(nbplt) '.']);
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% $$$ NAMES = [];
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% $$$ if TeX; TEXNAMES = []; end;
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% $$$ for j=1:number_of_plots_to_draw -(nbplt-1)*nstar
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% $$$ jj = (nbplt-1)*nstar + j;
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% $$$ subplot(nr,nc,j);
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% $$$ plot([1 options_.irf],[0 0],'-r','linewidth',0.5);
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% $$$ hold on
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% $$$ for k = 1:9
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% $$$ plot(1:options_.irf,DistribIRF(:,index(jj),i,k),'-g','linewidth',0.5)
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% $$$ end
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% $$$ plot(1:options_.irf,MeanIRF(:,index(jj),i),'-k','linewidth',1)
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% $$$ xlim([1 options_.irf]);
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% $$$ hold off
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% $$$ name = deblank(M_.endo_names(SelecVariables(index(jj)),:));
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% $$$ NAMES = strvcat(NAMES,name);
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% $$$ if TeX
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% $$$ texname = deblank(M_.endo_names_tex(SelecVariables(index(jj)),:));
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% $$$ TEXNAMES = strvcat(TEXNAMES,['$' texname '$']);
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% $$$ end
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% $$$ title(name,'Interpreter','none')
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% $$$ end
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% $$$ eval(['print -depsc2 ' M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) int2str(nbplt)]);
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% $$$ eval(['print -dpdf ' M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) int2str(nbplt)]);
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% $$$ saveas(hh,[M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) int2str(nbplt) '.fig']);
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% $$$ if options_.nograph, close(hh), end
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% $$$ if TeX
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% $$$ fprintf(fidTeX,'\\begin{figure}[H]\n');
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% $$$ for jj = 1:nstar
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% $$$ fprintf(fidTeX,['\\psfrag{%s}[1][][0.5][0]{%s}\n'],deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
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% $$$ end
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% $$$ fprintf(fidTeX,'\\centering \n');
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% $$$ fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_Bayesian_IRF_%s%s}\n',M_.fname,deblank(tit(i,:)),int2str(nbplt));
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% $$$ fprintf(fidTeX,'\\caption{Bayesian IRF.}');
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% $$$ fprintf(fidTeX,'\\label{Fig:BayesianIRF:%s:%s}\n',deblank(tit(i,:)), int2str(nbplt));
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% $$$ fprintf(fidTeX,'\\end{figure}\n');
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% $$$ fprintf(fidTeX,' \n');
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% $$$ end
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% $$$ else % nbplt = 0
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% $$$ disp('There''s nothing to plot here!')
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% $$$ end
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% $$$ end
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% $$$ if TeX
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% $$$ fprintf(fidTeX,'%% End of TeX file.\n');
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% $$$ fclose(fidTeX);
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% $$$ end
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% $$$ fprintf('MH: Posterior IRFs, done!\n');
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%%
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figunumber = 0;
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subplotnum = 0;
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for i=1:M_.exo_nbr
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NAMES = [];
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if options_.TeX
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TEXNAMES = [];
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end
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for j=1:nvar
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if max(abs(MeanIRF(:,j,i))) > 10^(-6)
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subplotnum = subplotnum+1;
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if subplotnum == 1 & options_.relative_irf
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hh = figure('Name',['Relative response to orthogonalized shock to ' tit(i,:)]);
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elseif subplotnum == 1 & ~options_.relative_irf
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hh = figure('Name',['Orthogonalized shock to ' tit(i,:)]);
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end
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set(0,'CurrentFigure',hh)
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subplot(nn,nn,subplotnum);
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plot([1 options_.irf],[0 0],'-r','linewidth',0.5);
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hold on
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for k = 1:9
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plot(1:options_.irf,DistribIRF(:,k,j,i),'-g','linewidth',0.5)
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end
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plot(1:options_.irf,MeanIRF(:,j,i),'-k','linewidth',1)
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xlim([1 options_.irf]);
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hold off
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name = deblank(varlist(j,:));
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NAMES = strvcat(NAMES,name);
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if options_.TeX
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texname = deblank(varlist_TeX(j,:));
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TEXNAMES = strvcat(TEXNAMES,['$' texname '$']);
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end
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title(name,'Interpreter','none')
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end
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if subplotnum == MaxNumberOfPlotPerFigure | j == nvar
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eval(['print -depsc2 ' M_.dname '\Plots\IRFs\' M_.fname '_Bayesian_IRF_' deblank(tit(i,:))]);
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eval(['print -dpdf ' M_.dname '\Plots\IRFs\' M_.fname '_Bayesian_IRF_' deblank(tit(i,:))]);
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saveas(hh,[M_.dname '\Plots\IRFs\' M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) '.fig']);
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if options_.nograph, close(hh), end
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if options_.TeX
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fprintf(fidTeX,'\\begin{figure}[H]\n');
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for jj = 1:size(TEXNAMES,1)
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fprintf(fidTeX,['\\psfrag{%s}[1][][0.5][0]{%s}\n'],deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
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end
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fprintf(fidTeX,'\\centering \n');
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fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_Bayesian_IRF_%s}\n',M_.fname,deblank(tit(i,:)));
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if options_.relative_irf
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fprintf(fidTeX,['\\caption{Bayesian relative IRF.}']);
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else
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fprintf(fidTeX,'\\caption{Bayesian IRF.}');
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end
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fprintf(fidTeX,'\\label{Fig:BayesianIRF:%s}\n',deblank(tit(i,:)));
|
||||
fprintf(fidTeX,'\\end{figure}\n');
|
||||
fprintf(fidTeX,' \n');
|
||||
end
|
||||
subplotnum = 0;
|
||||
figunumber = figunumber+1;
|
||||
end
|
||||
end% loop over selected endo_var
|
||||
end% loop over exo_var
|
||||
%%
|
||||
if options_.TeX
|
||||
fprintf(fidTeX,'%% End of TeX file.\n');
|
||||
fclose(fidTeX);
|
||||
end
|
||||
fprintf('MH: Posterior IRFs, done!\n');
|
||||
|
|
@ -471,7 +471,7 @@ if any(bayestopt_.pshape > 0) & options_.TeX %% Bayesian estimation (posterior m
|
|||
ip = nvx+nvn+ncx+ncn+1;
|
||||
for i=1:np
|
||||
fprintf(fidTeX,'$%s$ & %s & %7.3f & %6.4f & %8.4f & %7.4f \\\\ \n',...
|
||||
deblank(estim_params_.tex(i,:)),...
|
||||
M_.param_names_tex(estim_params_.param_vals(i,1),:),...%deblank(estim_params_.tex(i,:)),...
|
||||
deblank(pnames(bayestopt_.pshape(ip)+1,:)),...
|
||||
bayestopt_.pmean(ip),...
|
||||
estim_params_.param_vals(i,6),...
|
||||
|
|
|
|||
Loading…
Reference in New Issue