428 lines
17 KiB
Matlab
428 lines
17 KiB
Matlab
function oo_ = McMCDiagnostics(options_, estim_params_, M_, oo_)
|
|
% function McMCDiagnostics
|
|
% Computes convergence tests
|
|
%
|
|
% INPUTS
|
|
% options_ [structure]
|
|
% estim_params_ [structure]
|
|
% M_ [structure]
|
|
%
|
|
% OUTPUTS
|
|
% oo_ [structure]
|
|
%
|
|
% SPECIAL REQUIREMENTS
|
|
% none
|
|
%
|
|
% PARALLEL CONTEXT
|
|
% See the comment in random_walk_metropolis_hastings.m funtion.
|
|
|
|
% Copyright (C) 2005-2013 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/>.
|
|
|
|
DirectoryName = CheckPath('Output',M_.dname);
|
|
MhDirectoryName = CheckPath('metropolis',M_.dname);
|
|
|
|
TeX = options_.TeX;
|
|
nblck = options_.mh_nblck;
|
|
npar = estim_params_.nvx;
|
|
npar = npar + estim_params_.nvn;
|
|
npar = npar + estim_params_.ncx;
|
|
npar = npar + estim_params_.ncn;
|
|
npar = npar + estim_params_.np ;
|
|
MAX_nruns = ceil(options_.MaxNumberOfBytes/(npar+2)/8);
|
|
|
|
load([MhDirectoryName '/' M_.fname '_mh_history.mat'])
|
|
|
|
NumberOfMcFilesPerBlock = size(dir([MhDirectoryName ,filesep, M_.fname '_mh*_blck1.mat']),1);
|
|
|
|
% check if all previous files are there for block 1
|
|
check_presence_consecutive_MC_files(MhDirectoryName,M_.fname,1)
|
|
|
|
if nblck == 1 % Brooks and Gelman tests need more than one block
|
|
convergence_diagnostics_geweke=zeros(npar,4+2*length(options_.convergence.geweke.taper_steps));
|
|
if any(options_.convergence.geweke.geweke_interval<0) || any(options_.convergence.geweke.geweke_interval>1) || length(any(options_.convergence.geweke.geweke_interval<0))~=2 ...
|
|
|| (options_.convergence.geweke.geweke_interval(2)-options_.convergence.geweke.geweke_interval(1)<0)
|
|
fprintf('\nCONVERGENCE DIAGNOSTICS: Invalid option for geweke_interval. Using the default of [0.2 0.5].\n')
|
|
options_.convergence.geweke.geweke_interval=[0.2 0.5];
|
|
end
|
|
first_obs_begin_sample = max(1,ceil(options_.mh_drop*options_.mh_replic));
|
|
last_obs_begin_sample = first_obs_begin_sample+round(options_.convergence.geweke.geweke_interval(1)*options_.mh_replic*options_.mh_drop);
|
|
first_obs_end_sample = first_obs_begin_sample+round(options_.convergence.geweke.geweke_interval(2)*options_.mh_replic*options_.mh_drop);
|
|
param_name=[];
|
|
for jj=1:npar
|
|
param_name = strvcat(param_name,get_the_name(jj,options_.TeX,M_,estim_params_,options_));
|
|
end
|
|
fprintf('\nGeweke (1992) Convergence Tests, based on means of draws %d to %d vs %d to %d.\n',first_obs_begin_sample,last_obs_begin_sample,first_obs_end_sample,options_.mh_replic);
|
|
fprintf('p-values are for Chi2-test for equality of means.\n');
|
|
Geweke_header={'Parameter', 'Post. Mean', 'Post. Std', 'p-val No Taper'};
|
|
print_string=['%',num2str(size(param_name,2)+3),'s \t %12.3f \t %12.3f \t %12.3f'];
|
|
print_string_header=['%',num2str(size(param_name,2)+3),'s \t %12s \t %12s \t %12s'];
|
|
for ii=1:length(options_.convergence.geweke.taper_steps)
|
|
Geweke_header=[Geweke_header, ['p-val ' num2str(options_.convergence.geweke.taper_steps(ii)),'% Taper']];
|
|
print_string=[print_string,'\t %12.3f'];
|
|
print_string_header=[print_string_header,'\t %12s'];
|
|
end
|
|
print_string=[print_string,'\n'];
|
|
print_string_header=[print_string_header,'\n'];
|
|
fprintf(print_string_header,Geweke_header{1,:});
|
|
for jj=1:npar
|
|
startline=0;
|
|
for n = 1:NumberOfMcFilesPerBlock
|
|
load([MhDirectoryName '/' M_.fname '_mh',int2str(n),'_blck1.mat'],'x2');
|
|
nx2 = size(x2,1);
|
|
param_draws(startline+(1:nx2),1) = x2(:,jj);
|
|
startline = startline + nx2;
|
|
end
|
|
[results_vec, results_struct] = geweke_moments(param_draws,options_);
|
|
convergence_diagnostics_geweke(jj,:)=results_vec;
|
|
|
|
param_draws1 = param_draws(first_obs_begin_sample:last_obs_begin_sample,:);
|
|
param_draws2 = param_draws(first_obs_end_sample:end,:);
|
|
[results_vec1] = geweke_moments(param_draws1,options_);
|
|
[results_vec2] = geweke_moments(param_draws2,options_);
|
|
|
|
results_struct = geweke_chi2_test(results_vec1,results_vec2,results_struct,options_);
|
|
eval(['oo_.convergence.geweke.',param_name(jj,:),'=results_struct;'])
|
|
fprintf(print_string,param_name(jj,:),results_struct.posteriormean,results_struct.posteriorstd,results_struct.prob_chi2_test)
|
|
end
|
|
skipline(2);
|
|
return;
|
|
end
|
|
|
|
for blck = 2:nblck
|
|
tmp = size(dir([MhDirectoryName ,filesep, M_.fname '_mh*_blck' int2str(blck) '.mat']),1);
|
|
if tmp~=NumberOfMcFilesPerBlock
|
|
disp(['McMCDiagnostics:: The number of mh files in chain ' int2str(blck) ' is ' int2str(tmp) ' while'])
|
|
disp([' the number of mh files in chain 1 is ' int2str(mcfiles) '!'])
|
|
error('The number of mh files has to be constant across chains!')
|
|
end
|
|
% check if all previous files are there for block blck
|
|
check_presence_consecutive_MC_files(MhDirectoryName,M_.fname,blck)
|
|
end
|
|
|
|
PastDraws = sum(record.MhDraws,1);
|
|
LastFileNumber = PastDraws(2);
|
|
LastLineNumber = record.MhDraws(end,3);
|
|
NumberOfDraws = PastDraws(1);
|
|
|
|
Origin = 1000;
|
|
StepSize = ceil((NumberOfDraws-Origin)/100);% So that the computational time does not
|
|
ALPHA = 0.2; % increase too much with the number of simulations.
|
|
time = 1:NumberOfDraws;
|
|
xx = Origin:StepSize:NumberOfDraws;
|
|
NumberOfLines = length(xx);
|
|
tmp = zeros(NumberOfDraws*nblck,3);
|
|
UDIAG = zeros(NumberOfLines,6,npar);
|
|
|
|
if NumberOfDraws < Origin
|
|
disp('MCMC Diagnostics :: The number of simulations is to small to compute the MCMC convergence diagnostics.')
|
|
return
|
|
end
|
|
|
|
if TeX
|
|
fidTeX = fopen([DirectoryName '/' M_.fname '_UnivariateDiagnostics.TeX'],'w');
|
|
fprintf(fidTeX,'%% TeX eps-loader file generated by McmcDiagnostics.m (Dynare).\n');
|
|
fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
|
|
fprintf(fidTeX,' \n');
|
|
end
|
|
|
|
disp('MCMC Diagnostics: Univariate convergence diagnostic, Brooks and Gelman (1998):')
|
|
|
|
% The mandatory variables for local/remote parallel
|
|
% computing are stored in localVars struct.
|
|
|
|
localVars.MhDirectoryName = MhDirectoryName;
|
|
localVars.nblck = nblck;
|
|
localVars.NumberOfMcFilesPerBlock = NumberOfMcFilesPerBlock;
|
|
localVars.Origin = Origin;
|
|
localVars.StepSize = StepSize;
|
|
localVars.mh_drop = options_.mh_drop;
|
|
localVars.NumberOfDraws = NumberOfDraws;
|
|
localVars.NumberOfLines = NumberOfLines;
|
|
localVars.time = time;
|
|
localVars.M_ = M_;
|
|
|
|
|
|
% Like sequential execution!
|
|
if isnumeric(options_.parallel),
|
|
fout = McMCDiagnostics_core(localVars,1,npar,0);
|
|
UDIAG = fout.UDIAG;
|
|
clear fout
|
|
% Parallel execution!
|
|
else
|
|
ModelName = M_.fname;
|
|
if ~isempty(M_.bvar)
|
|
ModelName = [M_.fname '_bvar'];
|
|
end
|
|
NamFileInput={[M_.dname '/metropolis/'],[ModelName '_mh*_blck*.mat']};
|
|
|
|
[fout, nBlockPerCPU, totCPU] = masterParallel(options_.parallel, 1, npar,NamFileInput,'McMCDiagnostics_core', localVars, [], options_.parallel_info);
|
|
UDIAG = fout(1).UDIAG;
|
|
for j=2:totCPU,
|
|
UDIAG = cat(3,UDIAG ,fout(j).UDIAG);
|
|
end
|
|
end
|
|
|
|
UDIAG(:,[2 4 6],:) = UDIAG(:,[2 4 6],:)/nblck;
|
|
skipline()
|
|
clear pmet temp moyenne CSUP CINF csup cinf n linea iter tmp;
|
|
pages = floor(npar/3);
|
|
k = 0;
|
|
for i = 1:pages
|
|
h=dyn_figure(options_,'Name','MCMC univariate convergence diagnostic (Brooks and Gelman,1998)');
|
|
boxplot = 1;
|
|
for j = 1:3 % Loop over parameters
|
|
k = k+1;
|
|
[nam,namtex] = get_the_name(k,TeX,M_,estim_params_,options_);
|
|
for crit = 1:3% Loop over criteria
|
|
if crit == 1
|
|
plt1 = UDIAG(:,1,k);
|
|
plt2 = UDIAG(:,2,k);
|
|
namnam = [nam , ' (Interval)'];
|
|
elseif crit == 2
|
|
plt1 = UDIAG(:,3,k);
|
|
plt2 = UDIAG(:,4,k);
|
|
namnam = [nam , ' (m2)'];
|
|
elseif crit == 3
|
|
plt1 = UDIAG(:,5,k);
|
|
plt2 = UDIAG(:,6,k);
|
|
namnam = [nam , ' (m3)'];
|
|
end
|
|
if TeX
|
|
if j==1
|
|
NAMES = deblank(namnam);
|
|
TEXNAMES = deblank(namtex);
|
|
else
|
|
NAMES = char(NAMES,deblank(namnam));
|
|
TEXNAMES = char(TEXNAMES,deblank(namtex));
|
|
end
|
|
end
|
|
subplot(3,3,boxplot);
|
|
plot(xx,plt1,'-b'); % Pooled
|
|
hold on;
|
|
plot(xx,plt2,'-r'); % Within (mean)
|
|
hold off;
|
|
xlim([xx(1) xx(NumberOfLines)])
|
|
title(namnam,'Interpreter','none')
|
|
boxplot = boxplot + 1;
|
|
end
|
|
end
|
|
dyn_saveas(h,[DirectoryName '/' M_.fname '_udiag' int2str(i)],options_);
|
|
if TeX
|
|
fprintf(fidTeX,'\\begin{figure}[H]\n');
|
|
for jj = 1:size(NAMES,1)
|
|
fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
|
|
end
|
|
fprintf(fidTeX,'\\centering \n');
|
|
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_udiag%s}\n',[DirectoryName '/' M_.fname],int2str(i));
|
|
fprintf(fidTeX,'\\caption{Univariate convergence diagnostics for the Metropolis-Hastings.\n');
|
|
fprintf(fidTeX,'The first, second and third columns are respectively the criteria based on\n');
|
|
fprintf(fidTeX,'the eighty percent interval, the second and third moments.}');
|
|
fprintf(fidTeX,'\\label{Fig:UnivariateDiagnostics:%s}\n',int2str(i));
|
|
fprintf(fidTeX,'\\end{figure}\n');
|
|
fprintf(fidTeX,'\n');
|
|
end
|
|
end
|
|
reste = npar-k;
|
|
if reste
|
|
if reste == 1
|
|
nr = 3;
|
|
nc = 1;
|
|
elseif reste == 2;
|
|
nr = 2;
|
|
nc = 3;
|
|
end
|
|
h = dyn_figure(options_,'Name','MCMC univariate convergence diagnostic (Brooks and Gelman, 1998)');
|
|
boxplot = 1;
|
|
for j = 1:reste
|
|
k = k+1;
|
|
[nam,namtex] = get_the_name(k,TeX,M_,estim_params_,options_);
|
|
for crit = 1:3
|
|
if crit == 1
|
|
plt1 = UDIAG(:,1,k);
|
|
plt2 = UDIAG(:,2,k);
|
|
namnam = [nam , ' (Interval)'];
|
|
elseif crit == 2
|
|
plt1 = UDIAG(:,3,k);
|
|
plt2 = UDIAG(:,4,k);
|
|
namnam = [nam , ' (m2)'];
|
|
elseif crit == 3
|
|
plt1 = UDIAG(:,5,k);
|
|
plt2 = UDIAG(:,6,k);
|
|
namnam = [nam , ' (m3)'];
|
|
end
|
|
if TeX
|
|
if j==1
|
|
NAMES = deblank(namnam);
|
|
TEXNAMES = deblank(namtex);
|
|
else
|
|
NAMES = char(NAMES,deblank(namnam));
|
|
TEXNAMES = char(TEXNAMES,deblank(namtex));
|
|
end
|
|
end
|
|
subplot(nr,nc,boxplot);
|
|
plot(xx,plt1,'-b'); % Pooled
|
|
hold on;
|
|
plot(xx,plt2,'-r'); % Within (mean)
|
|
hold off;
|
|
xlim([xx(1) xx(NumberOfLines)]);
|
|
title(namnam,'Interpreter','none');
|
|
boxplot = boxplot + 1;
|
|
end
|
|
end
|
|
dyn_saveas(h,[ DirectoryName '/' M_.fname '_udiag' int2str(pages+1)],options_);
|
|
if TeX
|
|
fprintf(fidTeX,'\\begin{figure}[H]\n');
|
|
for jj = 1:size(NAMES,1);
|
|
fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
|
|
end
|
|
fprintf(fidTeX,'\\centering \n');
|
|
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_udiag%s}\n',[DirectoryName '/' M_.fname],int2str(pages+1));
|
|
if reste == 2
|
|
fprintf(fidTeX,'\\caption{Univariate convergence diagnostics for the Metropolis-Hastings.\n');
|
|
fprintf(fidTeX,'The first, second and third columns are respectively the criteria based on\n');
|
|
fprintf(fidTeX,'the eighty percent interval, the second and third moments.}');
|
|
elseif reste == 1
|
|
fprintf(fidTeX,'\\caption{Univariate convergence diagnostics for the Metropolis-Hastings.\n');
|
|
fprintf(fidTeX,'The first, second and third rows are respectively the criteria based on\n');
|
|
fprintf(fidTeX,'the eighty percent interval, the second and third moments.}');
|
|
end
|
|
fprintf(fidTeX,'\\label{Fig:UnivariateDiagnostics:%s}\n',int2str(pages+1));
|
|
fprintf(fidTeX,'\\end{figure}\n');
|
|
fprintf(fidTeX,'\n');
|
|
fprintf(fidTeX,'% End Of TeX file.');
|
|
fclose(fidTeX);
|
|
end
|
|
end % if reste > 0
|
|
clear UDIAG;
|
|
%%
|
|
%% Multivariate diagnostic.
|
|
%%
|
|
if TeX
|
|
fidTeX = fopen([DirectoryName '/' M_.fname '_MultivariateDiagnostics.TeX'],'w');
|
|
fprintf(fidTeX,'%% TeX eps-loader file generated by McmcDiagnostics.m (Dynare).\n');
|
|
fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
|
|
fprintf(fidTeX,' \n');
|
|
end
|
|
tmp = zeros(NumberOfDraws*nblck,3);
|
|
MDIAG = zeros(NumberOfLines,6);
|
|
for b = 1:nblck
|
|
startline = 0;
|
|
for n = 1:NumberOfMcFilesPerBlock
|
|
%load([MhDirectoryName '/' mcfiles(n,1,b).name],'logpo2');
|
|
load([MhDirectoryName '/' M_.fname '_mh',int2str(n),'_blck' int2str(b) '.mat'],'logpo2');
|
|
nlogpo2 = size(logpo2,1);
|
|
tmp((b-1)*NumberOfDraws+startline+(1:nlogpo2),1) = logpo2;
|
|
startline = startline+nlogpo2;
|
|
end
|
|
% $$$ %load([MhDirectoryName '/' mcfiles(NumberOfMcFilesPerBlock,1,b).name],'logpo2');
|
|
% $$$ load([MhDirectoryName '/' M_.fname '_mh',int2str(NumberOfMcFilesPerBlock),'_blck' int2str(b) '.mat'],'logpo2');
|
|
% $$$ tmp((b-1)*NumberOfDraws+startline+1:(b-1)*NumberOfDraws+ MAX_nruns*(LastFileNumber-1)+LastLineNumber,1) = logpo2;
|
|
end
|
|
clear logpo2;
|
|
tmp(:,2) = kron(transpose(1:nblck),ones(NumberOfDraws,1));
|
|
tmp(:,3) = kron(ones(nblck,1),time');
|
|
tmp = sortrows(tmp,1);
|
|
ligne = 0;
|
|
for iter = Origin:StepSize:NumberOfDraws
|
|
ligne = ligne+1;
|
|
linea = ceil(options_.mh_drop*iter);
|
|
n = iter-linea+1;
|
|
cinf = round(n*ALPHA/2);
|
|
csup = round(n*(1-ALPHA/2));
|
|
CINF = round(nblck*n*ALPHA/2);
|
|
CSUP = round(nblck*n*(1-ALPHA/2));
|
|
temp = tmp(find((tmp(:,3)>=linea) & (tmp(:,3)<=iter)),1:2);
|
|
MDIAG(ligne,1) = temp(CSUP,1)-temp(CINF,1);
|
|
moyenne = mean(temp(:,1));%% Pooled mean.
|
|
MDIAG(ligne,3) = sum((temp(:,1)-moyenne).^2)/(nblck*n-1);
|
|
MDIAG(ligne,5) = sum(abs(temp(:,1)-moyenne).^3)/(nblck*n-1);
|
|
for i=1:nblck
|
|
pmet = temp(find(temp(:,2)==i));
|
|
MDIAG(ligne,2) = MDIAG(ligne,2) + pmet(csup,1)-pmet(cinf,1);
|
|
moyenne = mean(pmet,1); %% Within mean.
|
|
MDIAG(ligne,4) = MDIAG(ligne,4) + sum((pmet(:,1)-moyenne).^2)/(n-1);
|
|
MDIAG(ligne,6) = MDIAG(ligne,6) + sum(abs(pmet(:,1)-moyenne).^3)/(n-1);
|
|
end
|
|
end
|
|
MDIAG(:,[2 4 6],:) = MDIAG(:,[2 4 6],:)/nblck;
|
|
|
|
h = dyn_figure(options_,'Name','Multivariate convergence diagnostic');
|
|
boxplot = 1;
|
|
for crit = 1:3
|
|
if crit == 1
|
|
plt1 = MDIAG(:,1);
|
|
plt2 = MDIAG(:,2);
|
|
namnam = 'Interval';
|
|
elseif crit == 2
|
|
plt1 = MDIAG(:,3);
|
|
plt2 = MDIAG(:,4);
|
|
namnam = 'm2';
|
|
elseif crit == 3
|
|
plt1 = MDIAG(:,5);
|
|
plt2 = MDIAG(:,6);
|
|
namnam = 'm3';
|
|
end
|
|
if TeX
|
|
if crit == 1
|
|
NAMES = deblank(namnam);
|
|
else
|
|
NAMES = char(NAMES,deblank(namnam));
|
|
end
|
|
end
|
|
subplot(3,1,boxplot);
|
|
plot(xx,plt1,'-b'); % Pooled
|
|
hold on
|
|
plot(xx,plt2,'-r'); % Within (mean)
|
|
hold off
|
|
xlim([xx(1) xx(NumberOfLines)])
|
|
title(namnam,'Interpreter','none');
|
|
boxplot = boxplot + 1;
|
|
end
|
|
dyn_saveas(h,[ DirectoryName '/' M_.fname '_mdiag'],options_);
|
|
|
|
if TeX
|
|
fprintf(fidTeX,'\\begin{figure}[H]\n');
|
|
for jj = 1:3
|
|
fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(jj,:)),' ');
|
|
end
|
|
fprintf(fidTeX,'\\centering \n');
|
|
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_mdiag}\n',[DirectoryName '/' M_.fname]);
|
|
fprintf(fidTeX,'\\caption{Multivariate convergence diagnostics for the Metropolis-Hastings.\n');
|
|
fprintf(fidTeX,'The first, second and third rows are respectively the criteria based on\n');
|
|
fprintf(fidTeX,'the eighty percent interval, the second and third moments. The different \n');
|
|
fprintf(fidTeX,'parameters are aggregated using the posterior kernel.}');
|
|
fprintf(fidTeX,'\\label{Fig:MultivariateDiagnostics}\n');
|
|
fprintf(fidTeX,'\\end{figure}\n');
|
|
fprintf(fidTeX,'\n');
|
|
fprintf(fidTeX,'% End Of TeX file.');
|
|
fclose(fidTeX);
|
|
end
|
|
|
|
function check_presence_consecutive_MC_files(MhDirectoryName,fname,blck)
|
|
% check if all previous files are there
|
|
files=ls([MhDirectoryName ,filesep, fname '_mh*_blck' int2str(blck) '.mat']); %list files
|
|
right_string=files(:,length([fname '_mh'])+1:end); %cut off left part of filename
|
|
k = cell2mat(strfind(cellstr(right_string),['_blck' int2str(blck) '.mat'])); %find index of position after number
|
|
file_numbers=str2num(right_string(:,1:k-1)); %get file number
|
|
if ~isempty(file_numbers) && ...
|
|
sum(sort(file_numbers)-(min(file_numbers):max(file_numbers))')~=0
|
|
error(['There are MH draw files missing within chain ', int2str(blck)])
|
|
end
|
|
|
|
|