83 lines
4.2 KiB
Matlab
83 lines
4.2 KiB
Matlab
function oo_ = conditional_variance_decomposition_posterior_analysis(NumberOfSimulations, dname, fname, ...
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Steps, exonames, exo, vartan, var, mh_conf_sig, oo_)
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% Copyright (C) 2009 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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indx = check_name(vartan,var);
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if isempty(indx)
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disp(['posterior_analysis:: ' var ' is not a stationary endogenous variable!'])
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return
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end
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endogenous_variable_index = sum(1:indx);
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exogenous_variable_index = check_name(exonames,exo);
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if isempty(exogenous_variable_index)
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disp(['posterior_analysis:: ' exo ' is not a declared exogenous variable!'])
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return
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end
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tmp = dir([ dname '/metropolis/' fname '_PosteriorConditionalVarianceDecomposition*.mat']);
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NumberOfFiles = length(tmp);
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i1 = 1; tmp = zeros(NumberOfSimulations,length(Steps));
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for file = 1:NumberOfFiles
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load([dname '/metropolis/' fname '_PosteriorConditionalVarianceDecomposition' int2str(file) '.mat']);
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% (endovar,time,exovar,simul)
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i2 = i1 + size(Conditional_decomposition_array,4) - 1;
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tmp(i1:i2,:) = transpose(dynare_squeeze(Conditional_decomposition_array(endogenous_variable_index,:,exogenous_variable_index,:)));
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i1 = i2+1;
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end
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name = [ var '.' exo ];
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if isfield(oo_,'PosteriorTheoreticalMoments')
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if isfield(oo_.PosteriorTheoreticalMoments,'dsge')
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if isfield(oo_.PosteriorTheoreticalMoments.dsge,'ConditionalVarianceDecomposition')
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if isfield(oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.mean,name)
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if sum(Steps-oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.mean.(name)(1,:)) == 0
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% Nothing (new) to do here...
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return
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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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posterior_mean = NaN(2,length(Steps));
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posterior_mean(1,:) = Steps;
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posterior_median = NaN(1,length(Steps));
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posterior_variance = NaN(1,length(Steps));
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posterior_deciles = NaN(9,length(Steps));
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posterior_density = NaN(2^9,2,length(Steps));
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posterior_hpdinf = NaN(1,length(Steps));
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posterior_hpdsup = NaN(1,length(Steps));
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for i=1:length(Steps)
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if ~isconst(tmp(:,i))
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[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
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posterior_moments(tmp(:,i),1,mh_conf_sig);
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posterior_mean(2,i) = post_mean;
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posterior_median(i) = post_median;
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posterior_variance(i) = post_var;
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posterior_deciles(:,i) = post_deciles;
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posterior_hpdinf(i) = hpd_interval(1);
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posterior_hpdinf(i) = hpd_interval(2);
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posterior_density(:,:,i) = density;
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end
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end
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eval(['oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.mean.' name ' = posterior_mean;']);
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eval(['oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.median.' name ' = posterior_median;']);
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eval(['oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.variance.' name ' = posterior_variance;']);
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eval(['oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.hpdinf.' name ' = posterior_hpdinf;']);
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eval(['oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.hpdsup.' name ' = posterior_hpdsup;']);
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eval(['oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.deciles.' name ' = posterior_deciles;']);
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eval(['oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.density.' name ' = posterior_density;']); |