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
55
56
57
58
59
60
61
62
63
64
65
66
|
function [mean, covariance, mode, kernel_at_the_mode] = compute_mh_covariance_matrix(names, fname, dname, outputFolderName)
% Estimation of the posterior covariance matrix, posterior mean, posterior mode and evaluation of the posterior kernel at the
% estimated mode, using posterior draws from a metropolis-hastings.
%
% INPUTS
% - names [cell] n×1 cell array of row char arrays, names of the estimated parameters.
% - fname [char] name of the model
% - dname [char] name of subfolder with output files
% - outputFolderName [char] name of directory to store results
%
% OUTPUTS
% - mean [double] n×1 vector, posterior expectation of the parameters.
% - covariance [double] n×n matrix, posterior covariance of the parameters.
% - mode [double] n×1 vector, posterior mode of the parameters.
% - kernel_at_the_mode [double] scalar, value of the posterior kernel at the mode.
% 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 <https://www.gnu.org/licenses/>.
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);
kernel_at_the_mode = -Inf;
mean = zeros(n,1);
mode = NaN(n,1);
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>kernel_at_the_mode
kernel_at_the_mode = tmp;
mode = x2(idx,:);
end
[mean, covariance, offset] = recursive_moments(mean, covariance, x2(first_line:end,:), offset);
first_line = 1;
end
end
mode = transpose(mode);
|
