function [posterior_mean,posterior_covariance,posterior_mode,posterior_kernel_at_the_mode] = compute_mh_covariance_matrix(bayestopt_,fname,dname,outputFolderName) % function [posterior_mean,posterior_covariance,posterior_mode,posterior_kernel_at_the_mode] = compute_mh_covariance_matrix(bayestopt_,fname,dname,outputFolderName) % Estimation of the posterior covariance matrix, posterior mean, posterior mode and evaluation of the posterior kernel at the % estimated mode, using the draws from a metropolis-hastings. The estimated posterior mode and covariance matrix are saved in % a file _mh_mode.mat. % % INPUTS % o bayestopt_ [struct] characterizing priors % o fname [string] name of model % o dname [string] name of directory with metropolis folder % o outputFolderName [string] name of directory to store results % % OUTPUTS % o posterior_mean [double] (n*1) vector, posterior expectation of the parameters. % o posterior_covariance [double] (n*n) matrix, posterior covariance of the parameters (computed from previous metropolis hastings). % o posterior_mode [double] (n*1) vector, posterior mode of the parameters. % o posterior_kernel_at_the_mode [double] scalar. % % SPECIAL REQUIREMENTS % None. % Copyright © 2006-2023 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 nargin < 4 outputFolderName = 'Output'; end MetropolisFolder = CheckPath('metropolis',dname); BaseName = [MetropolisFolder filesep fname]; record=load_last_mh_history_file(MetropolisFolder, fname); FirstMhFile = record.KeepedDraws.FirstMhFile; FirstLine = record.KeepedDraws.FirstLine; TotalNumberOfMhFiles = sum(record.MhDraws(:,2)); [nblck, n] = size(record.LastParameters); posterior_kernel_at_the_mode = -Inf; posterior_mean = zeros(n,1); posterior_mode = NaN(n,1); posterior_covariance = zeros(n,n); offset = 0; for b=1:nblck first_line = FirstLine; for n = FirstMhFile:TotalNumberOfMhFiles load([ BaseName '_mh' int2str(n) '_blck' int2str(b) '.mat'],'x2','logpo2'); [tmp,idx] = max(logpo2); if tmp>posterior_kernel_at_the_mode posterior_kernel_at_the_mode = tmp; posterior_mode = x2(idx,:); end [posterior_mean,posterior_covariance,offset] = recursive_moments(posterior_mean,posterior_covariance,x2(first_line:end,:),offset); first_line = 1; end end xparam1 = posterior_mode'; hh = inv(posterior_covariance); fval = posterior_kernel_at_the_mode; parameter_names = bayestopt_.name; save([dname filesep outputFolderName filesep fname '_mh_mode.mat'],'xparam1','hh','fval','parameter_names');