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Bug corrections and cosmetic changes. 

git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@1897 ac1d8469-bf42-47a9-8791-bf33cf982152
time-shift
adjemian 2008-06-24 17:13:36 +00:00
parent 66c5c66e2f
commit f12c2f4ed6
8 changed files with 151 additions and 138 deletions
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2
matlab/check_name.m Normal file
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@ -0,0 +1,2 @@
function n = check_name(vartan,varname)
n = strmatch(varname,vartan,'exact');

6
matlab/check_posterior_analysis_data.m
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@ -49,7 +49,7 @@ function [info,description] = check_posterior_analysis_data(type,M_)
otherwise
disp('This feature is not yest implemented!')
end
pdfinfo = dir([ M_.dname '/metropolis/' M_.fname '_' generic_post_data_file_name '*'])
pdfinfo = dir([ M_.dname '/metropolis/' M_.fname '_' generic_post_data_file_name '*']);
if isempty(pdfinfo)
info = 4; % posterior draws have to be processed.
if nargout>1
@ -59,9 +59,9 @@ function [info,description] = check_posterior_analysis_data(type,M_)
else
number_of_the_last_post_data_file = length(pdfinfo);
name_of_the_last_post_data_file = ...
[ M_.dname ...
[ './' M_.dname ...
'/metropolis/' ...
M_.dname ...
M_.fname '_' ...
generic_post_data_file_name ...
int2str(number_of_the_last_post_data_file) ...
'.mat' ];

2
matlab/cols.m Normal file
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@ -0,0 +1,2 @@
function c = cols(M)
c = size(M,2);

56
matlab/covariance_posterior_analysis.m Normal file
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@ -0,0 +1,56 @@
function oo_ = covariance_posterior_analysis(NumberOfSimulations,dname,fname,vartan,nvar,var1,var2,mh_conf_sig,oo_)
indx1 = check_name(vartan,var1);
if isempty(indx1)
disp(['posterior_analysis:: ' var1 ' is not a stationary endogenous variable!'])
return
end
if ~isempty(var2)
indx2 = check_name(vartan,var2);
if isempty(indx2)
disp(['posterior_analysis:: ' var2 ' is not a stationary endogenous variable!'])
return
end
else
indx2 = indx1;
var2 = var1;
end
if isfield(oo_,'PosteriorTheoreticalMoments')
if isfield(oo_.PosteriorTheoreticalMoments,'dsge')
if isfield(oo_.PosteriorTheoreticalMoments.dsge,'covariance')
if isfield(oo_.PosteriorTheoreticalMoments.dsge.covariance.mean,var1)
eval(['s1 = oo_.PosteriorTheoreticalMoments.dsge.covariance.mean' '.' var1 ';'])
if isfield(s1,var2)
% Nothing to do.
return
end
else
if isfield(oo_.PosteriorTheoreticalMoments.dsge.covariance.mean,var2)
eval(['s2 = oo_.PosteriorTheoreticalMoments.dsge.covariance.mean' '.' var2 ';'])
if isfield(s1,var1)
% Nothing to do (the covariance matrix is symmetric!).
return
end
end
end
end
end
end
tmp = dir([ dname '/metropolis/' fname '_Posterior2ndOrderMoments*.mat']);
NumberOfFiles= length(tmp);
i1 = 1; tmp = zeros(NumberOfSimulations,1);
for file = 1:NumberOfFiles
load([ dname '/metropolis/' fname '_Posterior2ndOrderMoments' int2str(file) '.mat']);
i2 = i1 + rows(Covariance_matrix) - 1;
tmp(i1:i2) = Covariance_matrix(:,symmetric_matrix_index(indx1,indx2,nvar));
i1 = i2+1;
end
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
posterior_moments(tmp,1,mh_conf_sig);
name = [var1 '.' var2];
eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.mean.' name ' = post_mean;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.median.' name ' = post_median;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.variance.' name ' = post_var;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.hpdinf.' name ' = hpd_interval(1);']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.hpdsup.' name ' = hpd_interval(2);']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.deciles.' name ' = post_deciles;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.density.' name ' = density;']);

15
matlab/dsge_posterior_theoretical_covariance.m
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@ -41,7 +41,7 @@ NumberOfDrawsFiles = length(DrawsFiles);
MaXNumberOfCovarLines = ceil(options_.MaxNumberOfBytes/(nvar*(nvar+1)/2)/8);
if SampleSize<=MaXNumberOfCovarLines
Covariance_matrix = zeros(NumberOfSimulations,nvar*(nvar+1)/2);
Covariance_matrix = zeros(SampleSize,nvar*(nvar+1)/2);
NumberOfCovarFiles = 1;
else
Covariance_matrix = zeros(MaXNumberOfCovarLines,nvar*(nvar+1)/2);
@ -55,7 +55,7 @@ CovarFileNumber = 1;
% Compute 2nd order moments and save them in *_Posterior2ndOrderMoments* files
linea = 0;
for file = 1:NumberOfDrawsFiles
load([MhDirectoryName '/' DrawsFiles(file).name]);
load([M_.dname '/metropolis/' DrawsFiles(file).name]);
NumberOfDraws = rows(pdraws);
isdrsaved = cols(pdraws)-1;
for linee = 1:NumberOfDraws
@ -73,7 +73,7 @@ for file = 1:NumberOfDrawsFiles
end
end
if linea == NumberOfCovarLines
save([fname '_Posterior2ndOrderMoments' int2str(CovarFileNumber)],'Covariance_matrix');
save([ M_.dname '/metropolis/' M_.fname '_Posterior2ndOrderMoments' int2str(CovarFileNumber)],'Covariance_matrix');
CovarFileNumber = CovarFileNumber + 1;
linea = 0;
test = CovarFileNumber-NumberOfCovarFiles;
@ -90,11 +90,4 @@ for file = 1:NumberOfDrawsFiles
end
end
options_.ar = nar;
function r = rows(M)
r = size(M,1);
function c = cols(M)
c = size(M,2);
options_.ar = nar;

32
matlab/dsge_posterior_theoretical_variance_decomposition.m
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@ -42,13 +42,13 @@ NumberOfDrawsFiles = rows(DrawsFiles);
NumberOfSavedElementsPerSimulation = nvar*(nexo+1);
MaXNumberOfDecompLines = ceil(options_.MaxNumberOfBytes/NumberOfSavedElementsPerSimulation/8);
if NumberOfSimulations<=MaXNumberOfDecompLines
Decomposition_array = zeros(NumberOfSimulations,nvar*(nexo+1));
if SampleSize<=MaXNumberOfDecompLines
Decomposition_array = zeros(SampleSize,nvar*nexo);
NumberOfDecompFiles = 1;
else
Decomposition_array = zeros(MaXNumberOfDecompLines,nvar*(nexo+1));
NumberOfLinesInTheLastDecompFile = mod(NumberOfSimulations,MaXNumberOfDecompLines);
NumberOfDecompFiles = ceil(NumberOfSimulations/MaXNumberOfDecompLines);
Decomposition_array = zeros(MaXNumberOfDecompLines,nvar*nexo);
NumberOfLinesInTheLastDecompFile = mod(SampleSize,MaXNumberOfDecompLines);
NumberOfDecompFiles = ceil(SampleSize/MaXNumberOfDecompLines);
end
NumberOfDecompLines = rows(Decomposition_array);
@ -59,7 +59,7 @@ DecompFileNumber = 1;
% implied by each structural shock.
linea = 0;
for file = 1:NumberOfDrawsFiles
load([MhDirectoryName '/' DrawsFiles(file).name]);
load([M_.dname '/metropolis/' DrawsFiles(file).name]);
isdrsaved = cols(pdraws)-1;
NumberOfDraws = rows(pdraws);
for linee = 1:NumberOfDraws
@ -71,26 +71,22 @@ for file = 1:NumberOfDrawsFiles
[dr,info] = resol(oo_.steady_state,0);
end
tmp = th_autocovariances(dr,ivar,M_,options_);
%for i=1:nvar
% Decomposition_array(linea,i) = tmp{1}(i,i);
%end
Decomposition_array(linea,:) = transpose(tmp{1});
for i=1:nvar
for j=1:nexo
Decomposition_array(linea,nvar+(i-1)*nexo+j) = tmp{2}(i,j);
Decomposition_array(linea,(i-1)*nexo+j) = tmp{2}(i,j);
end
end
if linea == NumberOfDecompLines
save([fname '_PosteriorVarianceDecomposition' int2str(DecompFileNumber)],'Decomposition_array');
save([M_.dname '/metropolis/' M_.fname '_PosteriorVarianceDecomposition' int2str(DecompFileNumber)],'Decomposition_array');
DecompFileNumber = DecompFileNumber + 1;
linea = 0;
test = DecompFileNumber-NumberOfDecompFiles;
if ~test% Prepare the last round...
Decomposition_array = zeros(NumberOfLinesInTheLastDecompFile,nvar*(nexo+1));
Decomposition_array = zeros(NumberOfLinesInTheLastDecompFile,nvar*nexo);
NumberOfDecompLines = NumberOfLinesInTheLastDecompFile;
DecompFileNumber = DecompFileNumber - 1;
elseif test<0;
Decomposition_array = zeros(MaXNumberOfDecompLines,nvar*(nexo+1));
Decomposition_array = zeros(MaXNumberOfDecompLines,nvar*nexo);
else
clear('Decomposition_array');
end
@ -98,10 +94,4 @@ for file = 1:NumberOfDrawsFiles
end
end
options_.ar = nar;% Useless because options_ is not a global anymore...
function r = rows(M)
r = size(M,1);
function c = cols(M)
c = size(M,2);
options_.ar = nar;

117
matlab/posterior_analysis.m
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@ -1,15 +1,14 @@
function posterior_analysis(type,arg1,arg2,options_,M_,oo_)
function oo_ = posterior_analysis(type,arg1,arg2,options_,M_,oo_)
% part of DYNARE, copyright Dynare Team (2008)
% Gnu Public License.
info = check_posterior_analysis_data(type,M_);
SampleSize = options_.PosteriorSampleSize;
switch info
case 0
disp('check_posterior_analysis_data:: Can''t find any mcmc file!')
error('Check the options of the estimation command...')
case {1,2}
SampleSize = options_.PosteriorSampleSize;
MaxMegaBytes = options_.MaximumNumberOfMegaBytes;
drsize = size_of_the_reduced_form_model(oo_.dr);
if drsize*SampleSize>MaxMegaBytes
@ -21,117 +20,29 @@ function posterior_analysis(type,arg1,arg2,options_,M_,oo_)
case 'variance'
[nvar,vartan,NumberOfFiles] = ...
dsge_posterior_theoretical_covariance(SampleSize,M_,options_,oo_);
oo_ = covariance_posterior_analysis(SampleSize,M_.dname,M_.fname,...
vartan,nvar,arg1,arg2,options_.mh_conf_sig,oo_);
case 'decomposition'
[nvar,vartan,NumberOfFiles] = ...
dsge_posterior_theoretical_variance_decomposition(SampleSize,M_,options_,oo_);
oo_ = variance_decomposition_posterior_analysis(SampleSize,M_.dname,M_.fname,...
M_.exo_names,arg2,vartan,arg1,options_.mh_conf_sig,oo_);
otherwise
disp('Not yet implemented')
end
case 6
[ivar,vartan] = set_stationary_variables_list;
nvar = length(ivar);
switch type
case 'variance'
covariance_posterior_analysis(NumberOfFiles,SampleSize,M_.dname,M_.fname,...
vartan,nvar,arg1,arg2);
case 'variance'
oo_ = covariance_posterior_analysis(SampleSize,M_.dname,M_.fname,...
vartan,nvar,arg1,arg2,options_.mh_conf_sig,oo_);
case 'decomposition'
variance_decomposition_posterior_analysis(NumberOfFiles,SampleSize,M_.dname,M_.fname,...
M_.exo_names,arg2,vartan,nvar,arg1);
oo_ = variance_decomposition_posterior_analysis(SampleSize,M_.dname,M_.fname,...
M_.exo_names,arg2,vartan,arg1,options_.mh_conf_sig,oo_);
otherwise
disp('Not yet implemented')
end
otherwise
error(['posterior_analysis:: Check_posterior_analysis_data gave a meaningless output!'])
end
function covariance_posterior_analysis(NumberOfFiles,NumberOfSimulations,dname,fname,vartan,nvar,var1,var2)
indx1 = check_name(vartan,var1)
if isempty(indx1)
disp(['posterior_analysis:: ' var1 ' is not a stationary endogenous variable!'])
return
end
if ~isempty(var2)
indx2 = check_name(vartan,var2)
if isempty(indx2)
disp(['posterior_analysis:: ' var2 ' is not a stationary endogenous variable!'])
return
end
else
indx2 = indx1;
var2 = var1;
end
i1 = 1; tmp = zeros(NumberOfSimulations,1);
for file = 1:CovarFileNumber
load([ dname '/metropolis/' fname '_Posterior2ndOrderMoments' int2str(file)]);
i2 = i1 + rows(Covariance_matrix) - 1;
tmp(i1:i2) = Covariance_matrix(:,symmetric_matrix_index(indx1,indx2,nvar));
i1 = i2+1;
end
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
posterior_moments(tmp,1,options_.mh_conf_sig);
if strcmpi(var1,var2)
name = var1;
else
name = [var1 '.' var2];
end
eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.mean.' name ' = post_mean;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.median.' name ' = post_median;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.variance.' name ' = post_var;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.hpdinf.' name ' = hpd_interval(1);']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.hpdsup.' name ' = hpd_interval(2);']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.deciles.' name ' = post_deciles;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.density.' name ' = density;']);
function variance_decomposition_posterior_analysis(NumberOfFiles,NumberOfSimulations,dname,fname, ...
exonames,exo,vartan,nvar,var)
indx1 = check_name(vartan,var)
if isempty(indx)
disp(['posterior_analysis:: ' var ' is not a stationary endogenous variable!'])
return
end
jndx = check_name(exonames,exo);
if isempty(jndx)
disp(['posterior_analysis:: ' exo ' is not a declared exogenous variable!'])
return
end
i1 = 1; tmp = zeros(NumberOfSimulations,1);
for file = 1:NumberOfFiles
load([fname '_PosteriorVarianceDecomposition' int2str(file)]);
i2 = i1 + rows(Decomposition_array) - 1;
tmp(i1:i2) = Decomposition_array(:,nvar+(i-1)*nexo+j);
i1 = i2+1;
end
name = [ var '.' exo ];
t1 = min(tmp); t2 = max(tmp);
t3 = t2-t1;% How to normalize ? t1 and t2 may be zero...
if t3<1.0e-12
if t1<1.0e-12
t1 = 0;
end
if abs(t1-1)<1.0e-12
t1 = 1;
end
post_mean = t1;
post_median = t1;
post_var = 0;
hpd_interval = NaN(2,1);
post_deciles = NaN(9,1);
density = NaN;
else
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
posterior_moments(tmp,1,options_.mh_conf_sig);
end
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.mean.' name ' = post_mean;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.median.' name ' = post_median;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.variance.' name ' = post_var;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.hpdinf.' name ' = hpd_interval(1);']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.hpdsup.' name ' = hpd_interval(2);']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.deciles.' name ' = post_deciles;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.density.' name ' = density;']);
function n = check_name(vartan,varname)
n = strmatch(varname,vartan,'exact')
end

59
matlab/variance_decomposition_posterior_analysis.m Normal file
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@ -0,0 +1,59 @@
function oo_ = variance_decomposition_posterior_analysis(NumberOfSimulations,dname,fname, ...
exonames,exo,vartan,var,mh_conf_sig,oo_)
indx = check_name(vartan,var);
if isempty(indx)
disp(['posterior_analysis:: ' var ' is not a stationary endogenous variable!'])
return
end
jndx = check_name(exonames,exo);
if isempty(jndx)
disp(['posterior_analysis:: ' exo ' is not a declared exogenous variable!'])
return
end
tmp = dir([ dname '/metropolis/' fname '_PosteriorVarianceDecomposition*.mat']);
NumberOfFiles = length(tmp);
i1 = 1; tmp = zeros(NumberOfSimulations,1);
indice = (indx-1)*rows(exonames)+jndx;
for file = 1:NumberOfFiles
load([dname '/metropolis/' fname '_PosteriorVarianceDecomposition' int2str(file) '.mat']);
i2 = i1 + rows(Decomposition_array) - 1;
tmp(i1:i2) = Decomposition_array(:,indice);
i1 = i2+1;
end
name = [ var '.' exo ];
if isfield(oo_,'PosteriorTheoreticalMoments')
if isfield(oo_.PosteriorTheoreticalMoments,'dsge')
if isfield(oo_.PosteriorTheoreticalMoments.dsge,'VarianceDecomposition')
if isfield(oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.mean,name)
% Nothing to do.
return
end
end
end
end
t1 = min(tmp); t2 = max(tmp);
t3 = t2-t1;% How to normalize ? t1 and t2 may be zero...
if t3<1.0e-12
if t1<1.0e-12
t1 = 0;
end
if abs(t1-1)<1.0e-12
t1 = 1;
end
post_mean = t1;
post_median = t1;
post_var = 0;
hpd_interval = NaN(2,1);
post_deciles = NaN(9,1);
density = NaN;
else
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
posterior_moments(tmp,1,mh_conf_sig);
end
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.mean.' name ' = post_mean;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.median.' name ' = post_median;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.variance.' name ' = post_var;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.hpdinf.' name ' = hpd_interval(1);']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.hpdsup.' name ' = hpd_interval(2);']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.deciles.' name ' = post_deciles;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.density.' name ' = density;']);