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+ Bug fixes related to the computation of prior (and posterior) moments. 

+ Cosmetic changes.


git-svn-id: https://www.dynare.org/svn/dynare/trunk@2791 ac1d8469-bf42-47a9-8791-bf33cf982152
time-shift
stepan 2009-06-26 10:21:30 +00:00
parent 53b0cf6306
commit d6fe54dc18
7 changed files with 53 additions and 47 deletions
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2
matlab/conditional_variance_decomposition.m
View File

@ -35,6 +35,7 @@ function PackedConditionalVarianceDecomposition = conditional_variance_decomposi
ConditionalVariance = zeros(StateSpaceModel.number_of_state_equations,StateSpaceModel.number_of_state_equations);
ConditionalVariance = repmat(ConditionalVariance,[1 1 length(Steps) StateSpaceModel.number_of_state_innovations]);
BB = StateSpaceModel.impulse_matrix*transpose(StateSpaceModel.impulse_matrix);
for h = 1:length(Steps)
for t = 0:Steps(h)
for i=1:StateSpaceModel.number_of_state_innovations
@ -44,6 +45,7 @@ function PackedConditionalVarianceDecomposition = conditional_variance_decomposi
end
end
end
ConditionalVariance = ConditionalVariance(SubsetOfVariables,SubsetOfVariables,:,:);
NumberOfVariables = length(SubsetOfVariables);
PackedConditionalVarianceDecomposition = zeros(NumberOfVariables*(NumberOfVariables+1)/2,length(Steps),StateSpaceModel.number_of_state_innovations);

2
matlab/conditional_variance_decomposition_mc_analysis.m
View File

@ -45,7 +45,7 @@ function oo_ = conditional_variance_decomposition_mc_analysis(NumberOfSimulation
if isfield(temporary_structure,'dsge')
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
if isfield(temporary_structure,'ConditionalVarianceDecomposition')
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.mean;'])
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.mean;'])
if isfield(temporary_structure,name)
if sum(Steps-temporary_structure.(name)(1,:)) == 0
% Nothing (new) to do here...

49
matlab/dsge_simulated_theoretical_conditional_variance_decomposition.m
View File

@ -40,6 +40,7 @@ if strcmpi(type,'posterior')
posterior = 1;
elseif strcmpi(type,'prior')
DrawsFiles = dir([M_.dname '/prior/draws/' type '_draws*' ]);
CheckPath('prior/moments');
posterior = 0;
else
disp('dsge_simulated_theoretical_conditional_variance_decomposition:: Unknown type!')
@ -53,7 +54,7 @@ if ~posterior
end
options_.varlist = options_.prior_analysis_endo_var_list;
end
[ivar,vartan, options_] = set_stationary_variables_list(options_, M_);
[ivar,vartan ] = set_stationary_variables_list(options_, M_);
if ~posterior
if exist('temp','var')
options_.varlist = temp;
@ -65,9 +66,6 @@ nvar = length(ivar);
nar = options_.ar;
options_.ar = 0;
NumberOfDrawsFiles = length(DrawsFiles);
NumberOfDrawsFiles = rows(DrawsFiles);
NumberOfSavedElementsPerSimulation = nvar*(nvar+1)/2*M_.exo_nbr*length(Steps);
MaXNumberOfConditionalDecompLines = ceil(options_.MaxNumberOfBytes/NumberOfSavedElementsPerSimulation/8);
@ -81,21 +79,13 @@ else
NumberOfConditionalDecompFiles = ceil(SampleSize/MaXNumberOfConditionalDecompLines);
end
NumberOfConditionalDecompLines = rows(Conditional_decomposition_array);
ConditionalDecompFileNumber = 1;
NumberOfConditionalDecompLines = size(Conditional_decomposition_array,4);
ConditionalDecompFileNumber = 0;
StateSpaceModel.number_of_state_equations = M_.endo_nbr;
StateSpaceModel.number_of_state_innovations = M_.exo_nbr;
endo_nbr = M_.endo_nbr;
nstatic = oo_.dr.nstatic;
npred = oo_.dr.npred;
iv = (1:endo_nbr)';
ic = [ nstatic+(1:npred) endo_nbr+(1:size(oo_.dr.ghx,2)-npred) ]';
aux = oo_.dr.transition_auxiliary_variables;
k = find(aux(:,2) > npred);
aux(:,2) = aux(:,2) + nstatic;
aux(k,2) = aux(k,2) + oo_.dr.nfwrd;
first_call = 1;
linea = 0;
for file = 1:NumberOfDrawsFiles
@ -115,11 +105,28 @@ for file = 1:NumberOfDrawsFiles
set_parameters(pdraws{linee,1});
[dr,info] = resol(oo_.steady_state,0);
end
if first_call
endo_nbr = M_.endo_nbr;
nstatic = dr.nstatic;
npred = dr.npred;
iv = (1:endo_nbr)';
ic = [ nstatic+(1:npred) endo_nbr+(1:size(dr.ghx,2)-npred) ]';
aux = dr.transition_auxiliary_variables;
k = find(aux(:,2) > npred);
aux(:,2) = aux(:,2) + nstatic;
aux(k,2) = aux(k,2) + dr.nfwrd;
StateSpaceModel.number_of_state_equations = M_.endo_nbr+rows(aux);
StateSpaceModel.number_of_state_innovations = M_.exo_nbr;
first_call = 0;
clear('endo_nbr','nstatic','npred','k');
end
[StateSpaceModel.transition_matrix,StateSpaceModel.impulse_matrix] = kalman_transition_matrix(dr,iv,ic,aux,M_.exo_nbr);
StateSpaceModel.state_innovations_covariance_matrix = M_.Sigma_e;
clear('dr');
Conditional_decomposition_array(:,:,:,linea) = conditional_variance_decomposition(StateSpaceModel, Steps, ivar);
Conditional_decomposition_array(:,:,:,linea) = conditional_variance_decomposition(StateSpaceModel, Steps, ivar);
if linea == NumberOfConditionalDecompLines
ConditionalDecompFileNumber = ConditionalDecompFileNumber + 1;
linea = 0;
if posterior
save([M_.dname '/metropolis/' M_.fname '_PosteriorConditionalVarianceDecomposition' int2str(ConditionalDecompFileNumber) '.mat' ], ...
'Conditional_decomposition_array');
@ -127,14 +134,10 @@ for file = 1:NumberOfDrawsFiles
save([M_.dname '/prior/moments/' M_.fname '_PriorConditionalVarianceDecomposition' int2str(ConditionalDecompFileNumber) '.mat' ], ...
'Conditional_decomposition_array');
end
ConditionalDecompFileNumber = ConditionalDecompFileNumber + 1;
linea = 0;
test = ConditionalDecompFileNumber-NumberOfConditionalDecompFiles;
if ~test% Prepare the last round...
Conditional_decomposition_array = zeros(nvar*(nvar+1)/2,length(Steps),M_.exo_nbr,NumberOfLinesInTheLastConditionalDecompFile);
if (ConditionalDecompFileNumber==NumberOfConditionalDecompFiles-1)% Prepare last round.
Conditional_decomposition_array = zeros(nvar*(nvar+1)/2, length(Steps),M_.exo_nbr,NumberOfLinesInTheLastConditionalDecompFile) ;
NumberOfConditionalDecompLines = NumberOfLinesInTheLastConditionalDecompFile;
ConditionalDecompFileNumber = ConditionalDecompFileNumber - 1;
elseif test<0;
elseif ConditionalDecompFileNumber<NumberOfConditionalDecompFiles-1
Conditional_decomposition_array = zeros(nvar*(nvar+1)/2,length(Steps),M_.exo_nbr,MaXNumberOfConditionalDecompLines);
else
clear('Conditional_decomposition_array');

1
matlab/dsge_simulated_theoretical_correlation.m
View File

@ -40,6 +40,7 @@ if strcmpi(type,'posterior')
posterior = 1;
elseif strcmpi(type,'prior')
DrawsFiles = dir([M_.dname '/prior/draws/' type '_draws*' ]);
CheckPath('prior/moments');
posterior = 0;
else
disp('dsge_simulated_theoretical_correlation:: Unknown type!');

1
matlab/dsge_simulated_theoretical_covariance.m
View File

@ -40,6 +40,7 @@ if strcmpi(type,'posterior')
posterior = 1;
elseif strcmpi(type,'prior')
DrawsFiles = dir([M_.dname '/prior/draws/' type '_draws*' ]);
CheckPath('prior/moments');
posterior = 0;
else
disp('dsge_simulated_theoretical_covariance:: Unknown type!')

1
matlab/dsge_simulated_theoretical_variance_decomposition.m
View File

@ -41,6 +41,7 @@ if strcmpi(type,'posterior')
posterior = 1;
elseif strcmpi(type,'prior')
DrawsFiles = dir([M_.dname '/prior/draws/' type '_draws*' ]);
CheckPath('prior/moments');
posterior = 0;
else
disp('dsge_simulated_theoretical_variance_decomposition:: Unknown type!')

44
matlab/prior_sampler.m
View File

@ -34,7 +34,7 @@ function results = prior_sampler(drsave,M_,bayestopt_,options_,oo_)
prior_draw(1,bayestopt_);
PriorDirectoryName = CheckPath('prior/draws');
work = ~drsave;
iteration = 1;
iteration = 0;
loop_indx = 0;
file_indx = [];
count_bk_indeterminacy = 0;
@ -55,48 +55,39 @@ function results = prior_sampler(drsave,M_,bayestopt_,options_,oo_)
if NumberOfSimulations <= NumberOfElementsPerFile
TableOfInformations = [ 1 , NumberOfSimulations , 1] ;
else
NumberOfFiles = fix(NumberOfSimulations/NumberOfElementsPerFile) ;
NumberOfFiles = ceil(NumberOfSimulations/NumberOfElementsPerFile) ;
NumberOfElementsInTheLastFile = NumberOfSimulations - NumberOfElementsPerFile*(NumberOfFiles-1) ;
if ~isint(NumberOfSimulations/NumberOfElementsPerFile)
NumberOfFiles = NumberOfFiles + 1 ;
end
TableOfInformations = NaN(NumberOfFiles,3);
TableOfInformations = NaN(NumberOfFiles,3) ;
TableOfInformations(:,1) = transpose(1:NumberOfFiles) ;
TableOfInformations(1:NumberOfFiles-1,2) = NumberOfElementsPerFile*ones(NumberOfFiles-1,1) ;
TableOfInformations(NumberOfFiles,2) = NumberOfElementsInTheLastFile ;
TableOfInformations(1,3) = 1;
TableOfInformations(2:end,3) = cumsum(TableOfInformations(2:end,2))+1;
TableOfInformations(2:end,3) = cumsum(TableOfInformations(1:end-1,2))+1;
end
pdraws = cell(TableOfInformations(1,2),drsave+1) ;
sampled_prior_expectation = zeros(NumberOfParameters,1);
sampled_prior_covariance = zeros(NumberOfParameters,NumberOfParameters);
file_line_number = 1;
file_indx_number = 1;
file_line_number = 0;
file_indx_number = 0;
% Simulations.
while iteration <= NumberOfSimulations
while iteration < NumberOfSimulations
loop_indx = loop_indx+1;
if ( (file_line_number-1)==TableOfInformations(file_indx_number,2))
save([ PriorDirectoryName '/prior_draws' int2str(file_indx_number) '.mat' ],'pdraws');
file_line_number = 1;
file_indx_number = file_indx_number + 1;
pdraws = cell(TableOfInformations(file_indx_number,2),drsave+1) ;
end
params = prior_draw();
set_all_parameters(params);
[dr,INFO] = resol(oo_.steady_state,work);
switch INFO(1)
switch INFO(1)
case 0
file_line_number = file_line_number + 1 ;
iteration = iteration + 1;
pdraws(file_line_number,1) = {params};
if drsave
pdraws(file_line_number,2) = {dr};
end
iteration = iteration+1;
file_line_number = file_line_number+1;
[sampled_prior_expectation,sampled_prior_covariance] = ...
recursive_prior_moments(sampled_prior_expectation,sampled_prior_covariance,params,iteration) ;
recursive_prior_moments(sampled_prior_expectation,sampled_prior_covariance,params,iteration);
case 1
count_static_undefined = count_static_undefined + 1;
case 2
@ -118,6 +109,14 @@ function results = prior_sampler(drsave,M_,bayestopt_,options_,oo_)
otherwise
count_unknown_problem = count_unknown_problem + 1 ;
end
if ( file_line_number==TableOfInformations(file_indx_number+1,2) )
file_indx_number = file_indx_number + 1;
save([ PriorDirectoryName '/prior_draws' int2str(file_indx_number) '.mat' ],'pdraws');
if file_indx_number<NumberOfFiles
pdraws = cell(TableOfInformations(file_indx_number+1,2),drsave+1);
end
file_line_number = 0;
end
end
% Get informations about BK conditions and other things...
@ -141,8 +140,7 @@ function results = prior_sampler(drsave,M_,bayestopt_,options_,oo_)
results.prior.mean = sampled_prior_expectation;
results.prior.variance = sampled_prior_covariance;
results.prior.mass = 1-results.garbage_share;
function [mu,sigma] = recursive_prior_moments(m0,s0,newobs,iter)
% Recursive estimation of order one and two moments (expectation and
% covariance matrix). newobs should be a row vector. I do not use the