From b82ce1baf1e9531b5ddcc55d56abeeefdfb3787d Mon Sep 17 00:00:00 2001
From: michel <michel@ac1d8469-bf42-47a9-8791-bf33cf982152>
Date: Fri, 16 Dec 2005 14:57:55 +0000
Subject: [PATCH] v3 metropolis: corrected bugs when not in dsge_var mode
git-svn-id: https://www.dynare.org/svn/dynare/dynare_v3@555 ac1d8469-bf42-47a9-8791-bf33cf982152
---
matlab/metropolis.m | 86 ++++++++++++++++++++++++---------------------
1 file changed, 45 insertions(+), 41 deletions(-)
diff --git a/matlab/metropolis.m b/matlab/metropolis.m
index 4c970fa268..1c412edc72 100644
--- a/matlab/metropolis.m
+++ b/matlab/metropolis.m
@@ -34,7 +34,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
MAX_nfilt = ceil(MaxNumberOfBytes/((endo_nbr)*gend)/8);
if options_.bayesian_irf
MAX_nirfs_dsge = ceil(MaxNumberOfBytes/(options_.irf*length(ys_)*exo_nbr)/8);
- if exist('dsge_prior_weight')
+ if ~isempty(dsge_prior_weight)
MAX_nirfs_dsgevar = ceil(MaxNumberOfBytes/(options_.irf*nvobs*exo_nbr)/8)
end
end
@@ -2267,7 +2267,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
%% %%
if options_.forecast
tmp = zeros(B,1);
- tmp_big = zeros(2*B,1);
+ tmp_big = zeros(B,1);
fprintf('MH: Out of sample forecasts...\n');
MeanForecast = zeros(options_.forecast,nvar);
MedianForecast = zeros(options_.forecast,nvar);
@@ -2309,11 +2309,11 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
end
HPD(step,i,1) = tmp(tmp2(1));
HPD(step,i,2) = tmp(tmp2(2));
- t = floor(options_.mh_conf_sig*B*2);
+ t = floor(options_.mh_conf_sig*B);
a = 1;
b = t;
tmp2_big = [1;t;tmp_big(t)-tmp_big(1)];
- while b <= 2*B
+ while b <= B
tmp1_big = [a;b;tmp_big(b)-tmp_big(a)];
a = a + 1;
b = b + 1;
@@ -2463,7 +2463,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
deep = MU;
subindx = subset();
nirfs = options_.irf;
- if exist('dsge_prior_weight')
+ if ~isempty(dsge_prior_weight)
files = eval(['dir(''' fname_ '_irf_dsgevar*.mat'');']);
if length(files)
delete([fname_ '_irf_dsgevar*.mat']);
@@ -2486,7 +2486,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
elseif nvn & B > MAX_nirfs
stock_irf_dsge = zeros(nirfs,size(lgy_,1),exo_nbr,MAX_nirfs_dsge);
end
- if exist('dsge_prior_weight')
+ if ~isempty(dsge_prior_weight)
if B <= MAX_nirfs_dsgevar
stock_irf_dsgevar = zeros(nirfs,nvobs,exo_nbr,B);
else
@@ -2507,7 +2507,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
for b = 1:B;
irun_irf_dsge = irun_irf_dsge+1;
tmp_dsge = zeros(nirfs,size(lgy_,1),exo_nbr);
- if exist('dsge_prior_weight')
+ if ~isempty(dsge_prior_weight)
irun_irf_dsgevar = irun_irf_dsgevar+1;
tmp_dsgevar = zeros(nirfs,nvobs*exo_nbr);
end
@@ -2554,7 +2554,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
stock_irf_dsge = zeros(nirfs,size(lgy_,1),exo_nbr,MAX_nirfs_dsge);
end
% bvar-dsge
- if exist('dsge_prior_weight')
+ if ~isempty(dsge_prior_weight)
DsgeVarLikelihood(deep',gend);
GYY = evalin('base','GYY');
GXX = evalin('base','GXX');
@@ -2624,7 +2624,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
eval(['save ' instr]);
end
clear stock_irf_dsge;
- if exist('dsge_prior_weight')
+ if ~isempty(dsge_prior_weight)
if irun_irf_dsgevar
stock_irf_dsgevar = stock_irf_dsgevar(:,:,:,1:irun_irf_dsgevar);
sfil_irf_dsgevar = sfil_irf_dsgevar + 1;
@@ -2636,7 +2636,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
else
sfil_irf_dsge = 0;
irun_irf_dsge = 0;
- if exist('dsge_prior_weight')
+ if ~isempty(dsge_prior_weight)
sfil_irf_dsgevar = 0;
irun_irf_dsgevar = 0;
end
@@ -2646,7 +2646,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
for b = 1:B;
irun_irf_dsge = irun_irf_dsge+1;
tmp_dsge = zeros(nirfs,size(lgy_,1),exo_nbr);
- if exist('dsge_prior_weight')
+ if ~isempty(dsge_prior_weight)
irun_irf_dsgevar = irun_irf_dsgevar+1;
tmp_dsgevar = zeros(nirfs,nvobs*exo_nbr);
end
@@ -2683,7 +2683,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
stock_irf_dsge = zeros(nirfs,size(lgy_,1),exo_nbr,MAX_nirfs_dsge);
end
% bvar-dsge
- if exist('dsge_prior_weight')
+ if ~isempty(dsge_prior_weight)
DsgeVarLikelihood(deep',gend);
GYY = evalin('base','GYY');
GXX = evalin('base','GXX');
@@ -2752,7 +2752,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
eval(['save ' instr]);
end
clear stock_irf_dsge;
- if exist('dsge_prior_weight')
+ if ~isempty(dsge_prior_weight)
if irun_irf_dsgevar
stock_irf_dsgevar = stock_irf_dsgevar(:,:,:,1:irun_irf_dsgevar);
sfil_irf_dsgevar = sfil_irf_dsgevar + 1;
@@ -2773,7 +2773,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
StdIRF_dsge = zeros(nirfs,nvar,exo_nbr);
DistribIRF_dsge = zeros(nirfs,nvar,exo_nbr,9);
HPDIRF_dsge = zeros(nirfs,nvar,exo_nbr,2);
- if exist('dsge_prior_weight')
+ if ~isempty(dsge_prior_weight)
SelecVariables = bayestopt_.mfys;
nvar = length(SelecVariables);
end
@@ -2830,7 +2830,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
deblank(lgy_(SelecVariables(j),:)) '_' deblank(tit(i,:)) ' = squeeze(HPDIRF_dsge(:,j,i,2));']);
end
end
- if exist('dsge_prior_weight')% BVAR-DSGE:
+ if ~isempty(dsge_prior_weight)% BVAR-DSGE:
tmp = zeros(B,1);
MeanIRF_dsgevar = zeros(nirfs,nvar,exo_nbr);
MedianIRF_dsgevar = zeros(nirfs,nvar,exo_nbr);
@@ -2906,9 +2906,9 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
for i=1:exo_nbr
number_of_plots_to_draw = 0;
index = [];
- if ~exist('dsge_prior_weight')
+ if ~~isempty(dsge_prior_weight)
for j=1:nvar
- if MeanIRF(1,j,i)
+ if MeanIRF_dsge(1,j,i)
number_of_plots_to_draw = number_of_plots_to_draw + 1;
index = cat(1,index,j);
end
@@ -2933,12 +2933,16 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
hold on
for k = 1:9
plot(1:nirfs,DistribIRF_dsge(:,index(j),i,k),'-k','linewidth',0.5,'Color',[0 0 0])
- if exist('dsge_prior_weight')
+ if ~isempty(dsge_prior_weight)
plot(1:nirfs,DistribIRF_dsgevar(:,j,i,k),'-k','linewidth',0.5,'Color',[0.80 0.80 0.80])
end
end
- plot(1:nirfs,MeanIRF_dsge(:,index(j),i),'-k','linewidth',3,'Color',[0 0 0])
- plot(1:nirfs,MeanIRF_dsgevar(:,j,i),'-k','linewidth',3,'Color',[0.80 0.80 0.80])
+ plot(1:nirfs,MeanIRF_dsge(:,index(j),i),'-k','linewidth',3,'Color',[0 ...
+ 0 0])
+ if ~isempty(dsge_prior_weight)
+ plot(1:nirfs,MeanIRF_dsgevar(:,j,i),'-k','linewidth',3,'Color',[0.80 ...
+ 0.80 0.80])
+ end
xlim([1 nirfs]);
hold off
name = deblank(lgy_(SelecVariables(index(j)),:));
@@ -2949,7 +2953,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
end
title(name,'Interpreter','none')
end
- if ~exist('dsge_prior_weight')
+ if isempty(dsge_prior_weight)
eval(['print -depsc2 ' fname_ '_Bayesian_IRFdsge_' deblank(tit(i,:))]);
eval(['print -dpdf ' fname_ '_Bayesian_IRFdsge_' deblank(tit(i,:))]);
saveas(hh,[fname_ '_Bayesian_IRFdsge_' deblank(tit(i,:)) '.fig']);
@@ -2965,7 +2969,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
fprintf(fidTeX,['\\psfrag{%s}[1][][0.5][0]{%s}\n'],deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
end
fprintf(fidTeX,'\\centering \n');
- if ~exist('dsge_prior_weight')
+ if ~~isempty(dsge_prior_weight)
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_Bayesian_IRFdsge_%s}\n',fname_,deblank(tit(i,:)));
else
fprintf(fidTeX,['\\includegraphics[scale=0.5]{%s_Bayesian_IRFbvardsge_%s}\n',fname_,deblank(tit(i,:))]);
@@ -2973,13 +2977,13 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
if options_.relative_irf
fprintf(fidTeX,['\\caption{Bayesian relative IRF.}']);
else
- if ~exist('dsge_prior_weight')
+ if ~~isempty(dsge_prior_weight)
fprintf(fidTeX,'\\caption{Bayesian IRF (DSGE model).}');
else
fprintf(fidTeX,'\\caption{Bayesian IRF (BVAR-DSGE model).}');
end
end
- if ~exist('dsge_prior_weight')
+ if ~~isempty(dsge_prior_weight)
fprintf(fidTeX,'\\label{Fig:BayesianIRFdsge:%s}\n',deblank(tit(i,:)));
else
fprintf(fidTeX,'\\label{Fig:BayesianIRFbvardsge:%s}\n',deblank(tit(i,:)));
@@ -3005,12 +3009,12 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
hold on
for k = 1:9
plot(1:options_.irf,DistribIRF_dsge(:,index(jj),i,k),'-k','linewidth',0.5,'Color',[0 0 0])
- if exist('dsge_prior_weight')
+ if ~isempty(dsge_prior_weight)
plot(1:nirfs,DistribIRF_dsgevar(:,jj,i,k),'-k','linewidth',0.5,'Color',[0.80 0.80 0.80])
end
end
plot(1:nirfs,MeanIRF_dsge(:,index(jj),i),'-k','linewidth',3,'Color',[0 0 0])
- if exist('dsge_prior_weight')
+ if ~isempty(dsge_prior_weight)
plot(1:nirfs,MeanIRF_dsgevar(:,jj,i),'-k','linewidth',3,'Color',[0.80 0.80 0.80])
end
xlim([1 nirfs]);
@@ -3023,7 +3027,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
end
title(name,'Interpreter','none')
end
- if ~exist('dsge_prior_weight')
+ if ~~isempty(dsge_prior_weight)
eval(['print -depsc2 ' fname_ '_Bayesian_IRFdsge_' deblank(tit(i,:)) int2str(fig)]);
eval(['print -dpdf ' fname_ '_Bayesian_IRFdsge_' deblank(tit(i,:)) int2str(fig)]);
saveas(hh,[fname_ '_Bayesian_IRFdsge_' deblank(tit(i,:)) int2str(fig) '.fig']);
@@ -3039,7 +3043,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
fprintf(fidTeX,['\\psfrag{%s}[1][][0.5][0]{%s}\n'],deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
end
fprintf(fidTeX,'\\centering \n');
- if ~exist('dsge_prior_weight')
+ if ~~isempty(dsge_prior_weight)
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_Bayesian_IRFdsge_%s%s}\n',fname_,deblank(tit(i,:)),int2str(fig));
else
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_Bayesian_IRFbvardsge_%s%s}\n',fname_,deblank(tit(i,:)),int2str(fig));
@@ -3047,13 +3051,13 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
if options_.relative_irf == 1
fprintf(fidTeX,['\\caption{Bayesian relative IRF.}']);
else
- if ~exist('dsge_prior_weight')
+ if ~~isempty(dsge_prior_weight)
fprintf(fidTeX,'\\caption{Bayesian IRF (DSGE model).}');
else
fprintf(fidTeX,['\\caption{Bayesian IRF (BVAR-DSGE model).}']);
end
end
- if ~exist('dsge_prior_weight')
+ if ~~isempty(dsge_prior_weight)
fprintf(fidTeX,'\\label{Fig:BayesianIRFdsge:%s:%s}\n',deblank(tit(i,:)), int2str(fig));
else
fprintf(fidTeX,'\\label{Fig:BayesianIRFbvardsge:%s:%s}\n',deblank(tit(i,:)), int2str(fig));
@@ -3072,13 +3076,13 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
hold on
for k = 1:9
plot(1:options_.irf,DistribIRF_dsge(:,index(jj),i,k),'-k','linewidth',0.5,'Color',[0 0 0])
- if exist('dsge_prior_weight')
+ if ~isempty(dsge_prior_weight)
plot(1:nirfs,DistribIRF_dsgevar(:,jj,i,k),'-k','linewidth',0.5,'Color',[0.80 0.80 0.80])
end
end
- plot(1:nirfs,MeanIRF(:,index(jj),i),'-k','linewidth',3,'Color',[0 0 0])
- if exist('dsge_prior_weight')
- plot(1:nirfs,MeanIRF(:,jj,i),'-k','linewidth',3,'Color',[0.80 0.80 0.80])
+ plot(1:nirfs,MeanIRF_dsge(:,index(jj),i),'-k','linewidth',3,'Color',[0 0 0])
+ if ~isempty(dsge_prior_weight)
+ plot(1:nirfs,MeanIRF_dsgevar(:,jj,i),'-k','linewidth',3,'Color',[0.80 0.80 0.80])
end
xlim([1 nirfs]);
hold off
@@ -3090,7 +3094,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
end
title(name,'Interpreter','none')
end
- if ~exist('dsge_prior_weight')
+ if ~~isempty(dsge_prior_weight)
eval(['print -depsc2 ' fname_ '_Bayesian_IRFdsge_' deblank(tit(i,:)) int2str(nbplt)]);
eval(['print -dpdf ' fname_ '_Bayesian_IRFdsge_' deblank(tit(i,:)) int2str(nbplt)]);
saveas(hh,[fname_ '_Bayesian_IRFdsge_' deblank(tit(i,:)) int2str(nbplt) '.fig']);
@@ -3106,7 +3110,7 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
fprintf(fidTeX,['\\psfrag{%s}[1][][0.5][0]{%s}\n'],deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
end
fprintf(fidTeX,'\\centering \n');
- if ~exist('dsge_prior_weight')
+ if ~~isempty(dsge_prior_weight)
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_Bayesian_IRFdsge_%s%s}\n',fname_,deblank(tit(i,:)),int2str(nbplt));
fprintf(fidTeX,'\\caption{Bayesian IRF (DSGE model).}');
fprintf(fidTeX,'\\label{Fig:BayesianIRFdsge:%s:%s}\n',deblank(tit(i,:)), int2str(nbplt));
@@ -3756,11 +3760,11 @@ function metropolis(xparam1,vv,gend,data,rawdata,mh_bounds)
StdDecomp(i,j),...
HPDDecomp(i,j,1),...
HPDDecomp(i,j,2)));
- eval(['oo_.PosteriorTheoreticalMoment.Decomp.Mean.' deblank(lgy_(ivar(i),:)) '_' deblank(lgx1_(j,:)) ' = MeanDecomp(i,j);']);
- eval(['oo_.PosteriorTheoreticalMoment.Decomp.Median.' deblank(lgy_(ivar(i),:)) '_' deblank(lgx1_(j,:)) ' = MedianDecomp(i,j);']);
- eval(['oo_.PosteriorTheoreticalMoment.Decomp.Std.' deblank(lgy_(ivar(i),:)) '_' deblank(lgx1_(j,:)) ' = StdDecomp(i,j);']);
- eval(['oo_.PosteriorTheoreticalMoment.Decomp.HPDinf.' deblank(lgy_(ivar(i),:)) '_' deblank(lgx1_(j,:)) ' = HPDDecomp(i,j,1);']);
- eval(['oo_.PosteriorTheoreticalMoment.Decomp.HPDsup.' deblank(lgy_(ivar(i),:)) '_' deblank(lgx1_(j,:)) ' = HPDDecomp(i,j,2);']);
+ eval(['oo_.PosteriorTheoreticalMoment.Decomp.Mean.' deblank(lgy_(ivar(i),:)) '_' deblank(lgx1(j,:)) ' = MeanDecomp(i,j);']);
+ eval(['oo_.PosteriorTheoreticalMoment.Decomp.Median.' deblank(lgy_(ivar(i),:)) '_' deblank(lgx1(j,:)) ' = MedianDecomp(i,j);']);
+ eval(['oo_.PosteriorTheoreticalMoment.Decomp.Std.' deblank(lgy_(ivar(i),:)) '_' deblank(lgx1(j,:)) ' = StdDecomp(i,j);']);
+ eval(['oo_.PosteriorTheoreticalMoment.Decomp.HPDinf.' deblank(lgy_(ivar(i),:)) '_' deblank(lgx1(j,:)) ' = HPDDecomp(i,j,1);']);
+ eval(['oo_.PosteriorTheoreticalMoment.Decomp.HPDsup.' deblank(lgy_(ivar(i),:)) '_' deblank(lgx1(j,:)) ' = HPDDecomp(i,j,2);']);
end
end
if TeX
--
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