function oo_ = ... conditional_variance_decomposition_mc_analysis(NumberOfSimulations, type, dname, fname, Steps, exonames, exo, var_list, endogenous_variable_index, mh_conf_sig, oo_) % This function analyses the (posterior or prior) distribution of the % endogenous conditional variance decomposition. % Copyright (C) 2009-2013 Dynare Team % % This file is part of Dynare. % % Dynare is free software: you can redistribute it and/or modify % it under the terms of the GNU General Public License as published by % the Free Software Foundation, either version 3 of the License, or % (at your option) any later version. % % Dynare is distributed in the hope that it will be useful, % but WITHOUT ANY WARRANTY; without even the implied warranty of % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. % % You should have received a copy of the GNU General Public License % along with Dynare. If not, see . if strcmpi(type,'posterior') TYPE = 'Posterior'; PATH = [dname '/metropolis/']; else TYPE = 'Prior'; PATH = [dname '/prior/moments/']; end % $$$ indx = check_name(vartan,var); % $$$ if isempty(indx) % $$$ disp([ type '_analysis:: ' var ' is not a stationary endogenous variable!']) % $$$ return % $$$ end % $$$ endogenous_variable_index = sum(1:indx); exogenous_variable_index = check_name(exonames,exo); if isempty(exogenous_variable_index) disp([ type '_analysis:: ' exo ' is not a declared exogenous variable!']) return end name = [ var_list(endogenous_variable_index,:) '.' exo ]; if isfield(oo_, [ TYPE 'TheoreticalMoments' ]) eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;']) if isfield(temporary_structure,'dsge') eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;']) if isfield(temporary_structure,'ConditionalVarianceDecomposition') 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... return end end end end end ListOfFiles = dir([ PATH fname '_' TYPE 'ConditionalVarianceDecomposition*.mat']); i1 = 1; tmp = zeros(NumberOfSimulations,length(Steps)); for file = 1:length(ListOfFiles) load([ PATH ListOfFiles(file).name ]); % 4D-array (endovar,time,exovar,simul) i2 = i1 + size(Conditional_decomposition_array,4) - 1; tmp(i1:i2,:) = transpose(dynare_squeeze(Conditional_decomposition_array(endogenous_variable_index,:,exogenous_variable_index,:))); i1 = i2+1; end p_mean = NaN(1,length(Steps)); p_median = NaN(1,length(Steps)); p_variance = NaN(1,length(Steps)); p_deciles = NaN(9,length(Steps)); p_density = NaN(2^9,2,length(Steps)); p_hpdinf = NaN(1,length(Steps)); p_hpdsup = NaN(1,length(Steps)); for i=1:length(Steps) [pp_mean, pp_median, pp_var, hpd_interval, pp_deciles, pp_density] = ... posterior_moments(tmp(:,i),1,mh_conf_sig); p_mean(i) = pp_mean; p_median(i) = pp_median; p_variance(i) = pp_var; p_deciles(:,i) = pp_deciles; p_hpdinf(i) = hpd_interval(1); p_hpdsup(i) = hpd_interval(2); p_density(:,:,i) = pp_density; end eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Steps = Steps;']); eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Mean.' name ' = p_mean;']); eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Median.' name ' = p_median;']); eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Variance.' name ' = p_variance;']); eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.HPDinf.' name ' = p_hpdinf;']); eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.HPDsup.' name ' = p_hpdsup;']); eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.deciles.' name ' = p_deciles;']); eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.density.' name ' = p_density;']);