/usr/share/dynare/matlab/GetPosteriorMeanVariance.m is in dynare-common 4.4.1-1build1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 | function [mean,variance] = GetPosteriorMeanVariance(M,drop)
% Copyright (C) 2012, 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 <http://www.gnu.org/licenses/>.
    
    MetropolisFolder = CheckPath('metropolis',M.dname);
    FileName = M.fname;
    BaseName = [MetropolisFolder filesep FileName];
    load_last_mh_history_file(MetropolisFolder, FileName);
    NbrDraws = sum(record.MhDraws(:,1));
    NbrFiles = sum(record.MhDraws(:,2));
    NbrBlocks = record.Nblck;
    mean = 0;
    variance = 0;
    z = [];
    
    nkept = 0;
    for i=1:NbrBlocks
        n = 0;
        for j=1:NbrFiles
            o = load([BaseName '_mh' int2str(j) '_blck' int2str(i)]);
            m = size(o.x2,1);
            if n + m < drop*NbrDraws
                n = n + m;
                continue
            elseif n < drop*NbrDraws
                k = ceil(drop*NbrDraws - n + 1);
                x2 = o.x2(k:end,:);
            else
                x2 = o.x2;
            end
            z =[z; x2];        
            p = size(x2,1);
            mean = (nkept*mean + sum(x2)')/(nkept+p);
            x = bsxfun(@minus,x2,mean');
            variance = (nkept*variance + x'*x)/(nkept+p);
            n = n + m;
            nkept = nkept + p;
        end
    end
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