95 lines
4.1 KiB
Matlab
95 lines
4.1 KiB
Matlab
function oo_ = ...
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conditional_variance_decomposition_mc_analysis(NumberOfSimulations, type, dname, fname, Steps, exonames, exo, var_list, endogenous_variable_index, mh_conf_sig, oo_)
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% This function analyses the (posterior or prior) distribution of the
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% endogenous conditional variance decomposition.
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% Copyright (C) 2009-2013 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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if strcmpi(type,'posterior')
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TYPE = 'Posterior';
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PATH = [dname '/metropolis/'];
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else
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TYPE = 'Prior';
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PATH = [dname '/prior/moments/'];
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end
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% $$$ indx = check_name(vartan,var);
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% $$$ if isempty(indx)
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% $$$ disp([ type '_analysis:: ' var ' is not a stationary endogenous variable!'])
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% $$$ 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([ type '_analysis:: ' exo ' is not a declared exogenous variable!'])
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return
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end
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name = [ var_list(endogenous_variable_index,:) '.' exo ];
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if isfield(oo_, [ TYPE 'TheoreticalMoments' ])
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eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])
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if isfield(temporary_structure,'dsge')
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eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
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if isfield(temporary_structure,'ConditionalVarianceDecomposition')
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eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Mean;'])
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if isfield(temporary_structure,name)
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if sum(Steps-temporary_structure.(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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ListOfFiles = dir([ PATH fname '_' TYPE 'ConditionalVarianceDecomposition*.mat']);
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i1 = 1; tmp = zeros(NumberOfSimulations,length(Steps));
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for file = 1:length(ListOfFiles)
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load([ PATH ListOfFiles(file).name ]);
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% 4D-array (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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p_mean = NaN(1,length(Steps));
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p_median = NaN(1,length(Steps));
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p_variance = NaN(1,length(Steps));
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p_deciles = NaN(9,length(Steps));
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p_density = NaN(2^9,2,length(Steps));
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p_hpdinf = NaN(1,length(Steps));
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p_hpdsup = NaN(1,length(Steps));
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for i=1:length(Steps)
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[pp_mean, pp_median, pp_var, hpd_interval, pp_deciles, pp_density] = ...
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posterior_moments(tmp(:,i),1,mh_conf_sig);
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p_mean(i) = pp_mean;
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p_median(i) = pp_median;
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p_variance(i) = pp_var;
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p_deciles(:,i) = pp_deciles;
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p_hpdinf(i) = hpd_interval(1);
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p_hpdsup(i) = hpd_interval(2);
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p_density(:,:,i) = pp_density;
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end
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eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Steps = Steps;']);
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eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Mean.' name ' = p_mean;']);
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eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Median.' name ' = p_median;']);
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eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Variance.' name ' = p_variance;']);
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eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.HPDinf.' name ' = p_hpdinf;']);
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eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.HPDsup.' name ' = p_hpdsup;']);
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eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.deciles.' name ' = p_deciles;']);
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eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.density.' name ' = p_density;']); |