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  • compute_mh_covariance_matrix.m 2.81 KiB
    function [posterior_mean,posterior_covariance,posterior_mode,posterior_kernel_at_the_mode] = compute_mh_covariance_matrix()
    % 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 <M_.fname>_mh_mode.mat. 
    % 
    % INPUTS 
    %   None.
    %  
    % 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 (C) 2006-2010 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 <http://www.gnu.org/licenses/>.
    
    global M_ options_ estim_params_
    
    
    n = estim_params_.np + ...
        estim_params_.nvn+ ...
        estim_params_.ncx+ ...
        estim_params_.ncn+ ...
        estim_params_.nvx;
    nblck = options_.mh_nblck;
    
    MhDirectoryName = CheckPath('metropolis',M_.dname);
    load([ MhDirectoryName '/'  M_.fname '_mh_history.mat'])
    
    FirstMhFile = record.KeepedDraws.FirstMhFile;
    FirstLine   = record.KeepedDraws.FirstLine;
    TotalNumberOfMhFiles = sum(record.MhDraws(:,2));
    
    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
            %for b = 1:nblck
            load([ MhDirectoryName '/' M_.fname '_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;
    
    save([M_.fname '_mh_mode.mat'],'xparam1','hh','fval');