Save Smoother.Trend and Smoother.Constant after MCMC
Johannes Pfeifer
Stéphane Adjemian (Lupi)
parent
1c84ccdc34
commit
3b09ab5424
139
matlab/pm3.m
139
matlab/pm3.m
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@ -83,7 +83,6 @@ if options_.estimation.moments_posterior_density.indicator
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Density = zeros(options_.estimation.moments_posterior_density.gridpoints,2,n2,nvar);
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end
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fprintf(['Estimation::mcmc: ' tit1 '\n']);
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stock1 = zeros(n1,n2,B);
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k = 0;
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filter_step_ahead_indicator=0;
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filter_covar_indicator=0;
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@ -93,6 +92,7 @@ for file = 1:ifil
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if strcmp(var_type,'_filter_step_ahead')
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if file==1 %on first run, initialize variable for storing filter_step_ahead
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stock1_filter_step_ahead=NaN(n1,n2,B,length(options_.filter_step_ahead));
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stock1 = zeros(n1,n2,B);
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end
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filter_step_ahead_indicator=1;
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stock_filter_step_ahead=zeros(n1,n2,size(stock,4),length(options_.filter_step_ahead));
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@ -101,23 +101,29 @@ for file = 1:ifil
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stock_filter_step_ahead(:,:,:,ii)=stock(ii,:,1+K_step_ahead:n2+K_step_ahead,:);
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end
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stock = squeeze(stock(1,:,1+1:1+n2,:)); %1 step ahead starts at entry 2
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end
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if strcmp(var_type,'_filter_covar')
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if file==1 %on first run, initialize variable for storing filter_step_ahead
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stock1_filter_covar=NaN(n1,n2,size(stock,3),B);
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end
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filter_covar_indicator=1;
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end
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if ~strcmp(var_type,'_filter_covar')
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k = k(end)+(1:size(stock,3));
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stock1(:,:,k) = stock;
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else
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k = k(end)+(1:size(stock,4));
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end
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if filter_step_ahead_indicator
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stock1_filter_step_ahead(:,:,k,:) = stock_filter_step_ahead;
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elseif filter_covar_indicator
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elseif strcmp(var_type,'_filter_covar')
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if file==1 %on first run, initialize variable for storing filter_step_ahead
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stock1_filter_covar=NaN(n1,n2,size(stock,3),B);
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end
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filter_covar_indicator=1;
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k = k(end)+(1:size(stock,4));
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stock1_filter_covar(:,:,:,k) = stock;
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elseif strcmp(var_type,'_trend_coeff')
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if file==1 %on first run, initialize variable for storing filter_step_ahead
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stock1_filter_step_ahead=NaN(n1,n2,B,length(options_.filter_step_ahead));
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stock1 = zeros(n1,B);
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end
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k = k(end)+(1:size(stock,2));
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stock1(:,k) = stock;
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else
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if file==1 %on first run, initialize variable for storing filter_step_ahead
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stock1 = zeros(n1,n2,B);
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end
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k = k(end)+(1:size(stock,3));
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stock1(:,:,k) = stock;
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end
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end
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clear stock
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@ -157,30 +163,43 @@ if filter_covar_indicator
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return
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end
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for i = 1:nvar
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for j = 1:n2
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if strcmp(var_type,'_trend_coeff') %two dimensional arrays
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for i = 1:nvar
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if options_.estimation.moments_posterior_density.indicator
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[Mean(j,i),Median(j,i),Var(j,i),HPD(:,j,i),Distrib(:,j,i),Density(:,:,j,i)] = ...
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posterior_moments(squeeze(stock1(SelecVariables(i),j,:)),1,options_.mh_conf_sig,options_.estimation.moments_posterior_density);
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[Mean(1,i),Median(1,i),Var(1,i),HPD(:,1,i),Distrib(:,1,i),Density(:,:,1,i)] = ...
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posterior_moments(squeeze(stock1(SelecVariables(i),:)),1,options_.mh_conf_sig,options_.estimation.moments_posterior_density);
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else
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[Mean(j,i),Median(j,i),Var(j,i),HPD(:,j,i),Distrib(:,j,i)] = ...
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posterior_moments(squeeze(stock1(SelecVariables(i),j,:)),0,options_.mh_conf_sig);
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[Mean(1,i),Median(1,i),Var(1,i),HPD(:,1,i),Distrib(:,1,i)] = ...
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posterior_moments(squeeze(stock1(SelecVariables(i),:)),0,options_.mh_conf_sig);
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end
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if filter_step_ahead_indicator
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end
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else %three dimensional arrays
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for i = 1:nvar
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for j = 1:n2
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if options_.estimation.moments_posterior_density.indicator
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for K_step = 1:length(options_.filter_step_ahead)
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[Mean_filter_step_ahead(K_step,i,j),Median_filter_step_ahead(K_step,i,j),Var_filter_step_ahead(K_step,i,j),HPD_filter_step_ahead(:,K_step,i,j),Distrib_filter_step_ahead(:,K_step,i,j),Density_filter_step_ahead(:,:,K_step,i,j) ] = ...
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posterior_moments(squeeze(stock1_filter_step_ahead(SelecVariables(i),j,:,K_step)),1,options_.mh_conf_sig,options_.estimation.moments_posterior_density);
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end
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[Mean(j,i),Median(j,i),Var(j,i),HPD(:,j,i),Distrib(:,j,i),Density(:,:,j,i)] = ...
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posterior_moments(squeeze(stock1(SelecVariables(i),j,:)),1,options_.mh_conf_sig,options_.estimation.moments_posterior_density);
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else
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for K_step = 1:length(options_.filter_step_ahead)
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[Mean_filter_step_ahead(K_step,i,j),Median_filter_step_ahead(K_step,i,j),Var_filter_step_ahead(K_step,i,j),HPD_filter_step_ahead(:,K_step,i,j),Distrib_filter_step_ahead(:,K_step,i,j)] = ...
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posterior_moments(squeeze(stock1_filter_step_ahead(SelecVariables(i),j,:,K_step)),0,options_.mh_conf_sig);
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[Mean(j,i),Median(j,i),Var(j,i),HPD(:,j,i),Distrib(:,j,i)] = ...
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posterior_moments(squeeze(stock1(SelecVariables(i),j,:)),0,options_.mh_conf_sig);
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end
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if filter_step_ahead_indicator
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if options_.estimation.moments_posterior_density.indicator
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for K_step = 1:length(options_.filter_step_ahead)
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[Mean_filter_step_ahead(K_step,i,j),Median_filter_step_ahead(K_step,i,j),Var_filter_step_ahead(K_step,i,j),HPD_filter_step_ahead(:,K_step,i,j),Distrib_filter_step_ahead(:,K_step,i,j),Density_filter_step_ahead(:,:,K_step,i,j) ] = ...
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posterior_moments(squeeze(stock1_filter_step_ahead(SelecVariables(i),j,:,K_step)),1,options_.mh_conf_sig,options_.estimation.moments_posterior_density);
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end
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else
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for K_step = 1:length(options_.filter_step_ahead)
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[Mean_filter_step_ahead(K_step,i,j),Median_filter_step_ahead(K_step,i,j),Var_filter_step_ahead(K_step,i,j),HPD_filter_step_ahead(:,K_step,i,j),Distrib_filter_step_ahead(:,K_step,i,j)] = ...
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posterior_moments(squeeze(stock1_filter_step_ahead(SelecVariables(i),j,:,K_step)),0,options_.mh_conf_sig);
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end
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end
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end
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end
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end
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end
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clear stock1
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if filter_step_ahead_indicator %write matrices corresponding to ML
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clear stock1_filter_step_ahead
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@ -194,31 +213,51 @@ if filter_step_ahead_indicator %write matrices corresponding to ML
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oo_.FilteredVariablesKStepAheadVariances=FilteredVariablesKStepAheadVariances;
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end
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for i = 1:nvar
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name = deblank(names1(SelecVariables(i),:));
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oo_.(name3).Mean.(name) = Mean(:,i);
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oo_.(name3).Median.(name) = Median(:,i);
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oo_.(name3).Var.(name) = Var(:,i);
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oo_.(name3).deciles.(name) = Distrib(:,:,i);
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oo_.(name3).HPDinf.(name) = HPD(1,:,i)';
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oo_.(name3).HPDsup.(name) = HPD(2,:,i)';
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if options_.estimation.moments_posterior_density.indicator
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oo_.(name3).density.(name) = Density(:,:,:,i);
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if strcmp(var_type,'_trend_coeff') || strcmp(var_type,'_smoothed_trend') || strcmp(var_type,'_smoothed_trend')
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for i = 1:nvar
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name = deblank(names1(SelecVariables(i),:));
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oo_.Smoother.(name3).Mean.(name) = Mean(:,i);
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oo_.Smoother.(name3).Median.(name) = Median(:,i);
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oo_.Smoother.(name3).Var.(name) = Var(:,i);
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oo_.Smoother.(name3).deciles.(name) = Distrib(:,:,i);
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oo_.Smoother.(name3).HPDinf.(name) = HPD(1,:,i)';
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oo_.Smoother.(name3).HPDsup.(name) = HPD(2,:,i)';
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if options_.estimation.moments_posterior_density.indicator
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oo_.Smoother.(name3).density.(name) = Density(:,:,:,i);
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end
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end
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if filter_step_ahead_indicator
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for K_step = 1:length(options_.filter_step_ahead)
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name4=['Filtered_Variables_',num2str(K_step),'_step_ahead'];
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oo_.(name4).Mean.(name) = squeeze(Mean_filter_step_ahead(K_step,i,:));
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oo_.(name4).Median.(name) = squeeze(Median_filter_step_ahead(K_step,i,:));
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oo_.(name4).Var.(name) = squeeze(Var_filter_step_ahead(K_step,i,:));
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oo_.(name4).deciles.(name) = squeeze(Distrib_filter_step_ahead(:,K_step,i,:));
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oo_.(name4).HPDinf.(name) = squeeze(HPD_filter_step_ahead(1,K_step,i,:));
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oo_.(name4).HPDsup.(name) = squeeze(HPD_filter_step_ahead(2,K_step,i,:));
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if options_.estimation.moments_posterior_density.indicator
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oo_.(name4).density.(name) = squeeze(Density_filter_step_ahead(:,:,K_step,i,:));
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else
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for i = 1:nvar
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name = deblank(names1(SelecVariables(i),:));
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oo_.(name3).Mean.(name) = Mean(:,i);
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oo_.(name3).Median.(name) = Median(:,i);
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oo_.(name3).Var.(name) = Var(:,i);
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oo_.(name3).deciles.(name) = Distrib(:,:,i);
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oo_.(name3).HPDinf.(name) = HPD(1,:,i)';
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oo_.(name3).HPDsup.(name) = HPD(2,:,i)';
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if options_.estimation.moments_posterior_density.indicator
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oo_.(name3).density.(name) = Density(:,:,:,i);
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end
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if filter_step_ahead_indicator
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for K_step = 1:length(options_.filter_step_ahead)
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name4=['Filtered_Variables_',num2str(K_step),'_step_ahead'];
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oo_.(name4).Mean.(name) = squeeze(Mean_filter_step_ahead(K_step,i,:));
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oo_.(name4).Median.(name) = squeeze(Median_filter_step_ahead(K_step,i,:));
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oo_.(name4).Var.(name) = squeeze(Var_filter_step_ahead(K_step,i,:));
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oo_.(name4).deciles.(name) = squeeze(Distrib_filter_step_ahead(:,K_step,i,:));
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oo_.(name4).HPDinf.(name) = squeeze(HPD_filter_step_ahead(1,K_step,i,:));
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oo_.(name4).HPDsup.(name) = squeeze(HPD_filter_step_ahead(2,K_step,i,:));
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if options_.estimation.moments_posterior_density.indicator
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oo_.(name4).density.(name) = squeeze(Density_filter_step_ahead(:,:,K_step,i,:));
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end
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end
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end
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end
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end
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end
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if strcmp(var_type,'_trend_coeff') || max(max(abs(Mean(:,:))))<=10^(-6) || all(all(isnan(Mean)))
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fprintf(['Estimation::mcmc: ' tit1 ', done!\n']);
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return %not do plots
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end
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%%
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%% Finally I build the plots.
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@ -93,6 +93,9 @@ end
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MAX_nruns = min(B,ceil(MaxNumberOfBytes/(npar+2)/8));
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MAX_nsmoo = min(B,ceil(MaxNumberOfBytes/((endo_nbr)*gend)/8));
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MAX_n_smoothed_constant = min(B,ceil(MaxNumberOfBytes/((endo_nbr)*gend)/8));
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MAX_n_smoothed_trend = min(B,ceil(MaxNumberOfBytes/((endo_nbr)*gend)/8));
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MAX_n_trend_coeff = min(B,ceil(MaxNumberOfBytes/endo_nbr/8));
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MAX_ninno = min(B,ceil(MaxNumberOfBytes/(exo_nbr*gend)/8));
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MAX_nerro = min(B,ceil(MaxNumberOfBytes/(size(options_.varobs,1)*gend)/8));
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@ -123,7 +126,7 @@ for i=1:nvar
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end
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end
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n_variables_to_fill=8;
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n_variables_to_fill=11;
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irun = ones(n_variables_to_fill,1);
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ifil = zeros(n_variables_to_fill,1);
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@ -172,6 +175,9 @@ end
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if options_.filter_covariance
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localVars.MAX_filter_covariance = MAX_filter_covariance;
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end
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localVars.MAX_n_smoothed_constant=MAX_n_smoothed_constant;
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localVars.MAX_n_smoothed_trend=MAX_n_smoothed_trend;
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localVars.MAX_n_trend_coeff=MAX_n_trend_coeff;
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localVars.MAX_nruns=MAX_nruns;
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localVars.MAX_momentsno = MAX_momentsno;
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localVars.ifil=ifil;
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@ -223,6 +229,14 @@ else
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nfiles = ceil(nBlockPerCPU(j)/MAX_filter_covariance);
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ifil(8,j+1) =ifil(8,j)+nfiles;
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end
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if run_smoother
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nfiles = ceil(nBlockPerCPU(j)/MAX_n_trend_coeff);
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ifil(9,j+1) =ifil(9,j)+nfiles;
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nfiles = ceil(nBlockPerCPU(j)/MAX_n_smoothed_constant);
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ifil(10,j+1) =ifil(10,j)+nfiles;
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nfiles = ceil(nBlockPerCPU(j)/MAX_n_smoothed_trend);
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ifil(11,j+1) =ifil(11,j)+nfiles;
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end
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end
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localVars.ifil = ifil;
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globalVars = struct('M_',M_, ...
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@ -264,6 +278,16 @@ if options_.smoother
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pm3(exo_nbr,gend,ifil(2),B,'Smoothed shocks',...
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'',M_.exo_names,M_.exo_names_tex,M_.exo_names,...
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M_.exo_names,'SmoothedShocks',DirectoryName,'_inno');
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pm3(endo_nbr,1,ifil(9),B,'Trend_coefficients',...
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'',M_.endo_names(1:M_.orig_endo_nbr,:),M_.endo_names_tex,M_.endo_names,...
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varlist,'TrendCoeff',DirectoryName,'_trend_coeff');
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pm3(endo_nbr,gend,ifil(10),B,'Smoothed constant',...
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'',M_.endo_names(1:M_.orig_endo_nbr, :),M_.endo_names_tex,M_.endo_names,...
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varlist,'Constant',DirectoryName,'_smoothed_constant');
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pm3(endo_nbr,gend,ifil(11),B,'Smoothed trend',...
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'',M_.endo_names(1:M_.orig_endo_nbr, :),M_.endo_names_tex,M_.endo_names,...
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varlist,'Trend',DirectoryName,'_smoothed_trend');
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if nvn
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for obs_iter=1:length(options_.varobs)
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meas_error_names{obs_iter,1}=['SE_EOBS_' M_.endo_names(strmatch(options_.varobs{obs_iter},M_.endo_names,'exact'),:)];
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@ -15,7 +15,11 @@ function myoutput=prior_posterior_statistics_core(myinputs,fpar,B,whoiam, ThisMa
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% _filter_step_ahead;
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% _param;
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% _forc_mean;
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% _forc_point
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% _forc_point;
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% _filter_covar;
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% _trend_coeff;
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% _smoothed_trend;
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% _smoothed_constant;
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%
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% ALGORITHM
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% Portion of prior_posterior.m function.
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@ -77,11 +81,13 @@ end
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if filter_covariance
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MAX_filter_covariance=myinputs.MAX_filter_covariance;
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end
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exo_nbr=myinputs.exo_nbr;
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maxlag=myinputs.maxlag;
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MAX_nsmoo=myinputs.MAX_nsmoo;
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MAX_ninno=myinputs.MAX_ninno;
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MAX_n_smoothed_constant=myinputs.MAX_n_smoothed_constant;
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MAX_n_smoothed_trend=myinputs.MAX_n_smoothed_trend;
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MAX_n_trend_coeff=myinputs.MAX_n_trend_coeff;
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MAX_nerro = myinputs.MAX_nerro;
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MAX_nruns=myinputs.MAX_nruns;
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MAX_momentsno = myinputs.MAX_momentsno;
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@ -132,6 +138,9 @@ if RemoteFlag==1,
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OutputFileName_forc_mean = {};
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OutputFileName_forc_point = {};
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OutputFileName_filter_covar ={};
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OutputFileName_trend_coeff = {};
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OutputFileName_smoothed_trend = {};
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OutputFileName_smoothed_constant = {};
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% OutputFileName_moments = {};
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end
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@ -140,6 +149,9 @@ if run_smoother
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stock_smooth=NaN(endo_nbr,gend,MAX_nsmoo);
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stock_update=NaN(endo_nbr,gend,MAX_nsmoo);
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stock_innov=NaN(M_.exo_nbr,gend,MAX_ninno);
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stock_smoothed_constant=NaN(endo_nbr,gend,MAX_n_smoothed_constant);
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stock_smoothed_trend=NaN(endo_nbr,gend,MAX_n_smoothed_trend);
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stock_trend_coeff = zeros(endo_nbr,MAX_n_trend_coeff);
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if horizon
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stock_forcst_mean= NaN(endo_nbr,horizon,MAX_nforc1);
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stock_forcst_point = NaN(endo_nbr,horizon,MAX_nforc2);
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@ -177,18 +189,23 @@ for b=fpar:B
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[dr,info,M_,options_,oo_] = resol(0,M_,options_,oo_);
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[alphahat,etahat,epsilonhat,alphatilde,SteadyState,trend_coeff,aK,junk1,junk2,P,junk4,junk5,trend_addition] = ...
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DsgeSmoother(deep,gend,Y,data_index,missing_value);
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stock_trend_coeff(options_.varobs_id,irun(9))=trend_coeff;
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stock_smoothed_trend(IdObs,:,irun(11))=trend_addition;
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if options_.loglinear %reads values from smoother results, which are in dr-order and put them into declaration order
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||||
constant_part=repmat(log(SteadyState(dr.order_var)),1,gend);
|
||||
stock_smooth(dr.order_var,:,irun(1)) = alphahat(1:endo_nbr,:)+ ...
|
||||
repmat(log(SteadyState(dr.order_var)),1,gend);
|
||||
constant_part;
|
||||
stock_update(dr.order_var,:,irun(1)) = alphatilde(1:endo_nbr,:)+ ...
|
||||
repmat(log(SteadyState(dr.order_var)),1,gend);
|
||||
constant_part;
|
||||
else
|
||||
constant_part=repmat(SteadyState(dr.order_var),1,gend);
|
||||
stock_smooth(dr.order_var,:,irun(1)) = alphahat(1:endo_nbr,:)+ ...
|
||||
repmat(SteadyState(dr.order_var),1,gend);
|
||||
constant_part;
|
||||
stock_update(dr.order_var,:,irun(1)) = alphatilde(1:endo_nbr,:)+ ...
|
||||
repmat(SteadyState(dr.order_var),1,gend);
|
||||
end
|
||||
constant_part;
|
||||
end
|
||||
stock_smoothed_constant(dr.order_var,:,irun(10))=constant_part;
|
||||
%% Compute constant for observables
|
||||
if options_.prefilter == 1 %as mean is taken after log transformation, no distinction is needed here
|
||||
constant_part=repmat(mean_varobs',1,gend);
|
||||
|
|
@ -205,6 +222,7 @@ for b=fpar:B
|
|||
else
|
||||
mean_correction=-repmat(SteadyState(IdObs),1,gend)+constant_part;
|
||||
end
|
||||
stock_smoothed_constant(IdObs,:,irun(10))=stock_smoothed_constant(IdObs,:,irun(10))+mean_correction;
|
||||
%smoothed variables are E_T(y_t) so no trend shift is required
|
||||
stock_smooth(IdObs,:,irun(1))=stock_smooth(IdObs,:,irun(1))+trend_addition+mean_correction;
|
||||
%updated variables are E_t(y_t) so no trend shift is required
|
||||
|
|
@ -282,7 +300,7 @@ for b=fpar:B
|
|||
stock_ys(irun(5),:) = SteadyState';
|
||||
|
||||
|
||||
irun = irun + ones(8,1);
|
||||
irun = irun + ones(11,1);
|
||||
|
||||
|
||||
if run_smoother && (irun(1) > MAX_nsmoo || b == B),
|
||||
|
|
@ -370,6 +388,39 @@ for b=fpar:B
|
|||
end
|
||||
irun(8) = 1;
|
||||
end
|
||||
|
||||
irun_index=9;
|
||||
if run_smoother && (irun(irun_index) > MAX_n_trend_coeff || b == B)
|
||||
stock = stock_trend_coeff(:,1:irun(irun_index)-1);
|
||||
ifil(irun_index) = ifil(irun_index) + 1;
|
||||
save([DirectoryName '/' M_.fname '_trend_coeff' int2str(ifil(irun_index)) '.mat'],'stock');
|
||||
if RemoteFlag==1,
|
||||
OutputFileName_trend_coeff = [OutputFileName_trend_coeff; {[DirectoryName filesep], [M_.fname '_trend_coeff' int2str(ifil(irun_index)) '.mat']}];
|
||||
end
|
||||
irun(irun_index) = 1;
|
||||
end
|
||||
|
||||
irun_index=10;
|
||||
if run_smoother && (irun(irun_index) > MAX_n_smoothed_constant || b == B)
|
||||
stock = stock_smoothed_constant(:,:,1:irun(irun_index)-1);
|
||||
ifil(irun_index) = ifil(irun_index) + 1;
|
||||
save([DirectoryName '/' M_.fname '_smoothed_constant' int2str(ifil(irun_index)) '.mat'],'stock');
|
||||
if RemoteFlag==1,
|
||||
OutputFileName_smoothed_constant = [OutputFileName_smoothed_constant; {[DirectoryName filesep], [M_.fname '_smoothed_constant' int2str(ifil(irun_index)) '.mat']}];
|
||||
end
|
||||
irun(irun_index) = 1;
|
||||
end
|
||||
|
||||
irun_index=11;
|
||||
if run_smoother && (irun(irun_index) > MAX_n_smoothed_trend || b == B)
|
||||
stock = stock_smoothed_trend(:,:,1:irun(irun_index)-1);
|
||||
ifil(irun_index) = ifil(irun_index) + 1;
|
||||
save([DirectoryName '/' M_.fname '_smoothed_trend' int2str(ifil(irun_index)) '.mat'],'stock');
|
||||
if RemoteFlag==1,
|
||||
OutputFileName_smoothed_trend = [OutputFileName_smoothed_trend; {[DirectoryName filesep], [M_.fname '_smoothed_trend' int2str(ifil(irun_index)) '.mat']}];
|
||||
end
|
||||
irun(irun_index) = 1;
|
||||
end
|
||||
|
||||
dyn_waitbar((b-fpar+1)/(B-fpar+1),h);
|
||||
end
|
||||
|
|
@ -384,7 +435,10 @@ if RemoteFlag==1,
|
|||
OutputFileName_param;
|
||||
OutputFileName_forc_mean;
|
||||
OutputFileName_forc_point
|
||||
OutputFileName_filter_covar];
|
||||
OutputFileName_filter_covar
|
||||
OutputFileName_trend_coeff
|
||||
OutputFileName_smoothed_trend
|
||||
OutputFileName_smoothed_constant];
|
||||
end
|
||||
|
||||
dyn_waitbar_close(h);
|
||||
|
|
|
|||
Loading…
Reference in New Issue