eval(dir) ==> dir
git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@657 ac1d8469-bf42-47a9-8791-bf33cf982152time-shift
adjemian
parent
58cb6e42b6
commit
3d5b975836
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@ -4,6 +4,6 @@ global M_
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DirectoryName = [ M_.dname '/' type ];
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if ~isdir(DirectoryName)
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mkdir('.',DirectoryName);
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if ~isdir(DirectoryName)
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mkdir('.',DirectoryName);
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end
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@ -3,7 +3,8 @@ function McmcDiagnostic
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global options_ estim_params_ M_
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DirectoryName = CheckPath('Plots/Diagnostics');
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DirectoryName = CheckPath('Output');
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MhDirectoryName = CheckPath('metropolis');
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TeX = options_.TeX;
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nblck = options_.mh_nblck;
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@ -18,8 +19,15 @@ npar = npar + estim_params_.ncn;
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npar = npar + estim_params_.np ;
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MAX_nruns = ceil(options_.MaxNumberOfBytes/(npar+2)/8);
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load(['./' M_.dname '/metropolis/' M_.fname '_mh_history.mat'])
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load([MhDirectoryName '/' M_.fname '_mh_history.mat'])
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mcfiles = [];
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for blck = 1:nblck
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mcfiles = cat(3,mcfiles,dir([MhDirectoryName '/' M_.fname '_mh*_blck' int2str(blck) '.mat']));
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end
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NumberOfMcFilesPerBlock = size(mcfiles,1);
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PastDraws = sum(record.MhDraws,1);
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LastFileNumber = PastDraws(2);
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LastLineNumber = record.MhDraws(end,3);
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@ -27,233 +35,51 @@ NumberOfDraws = PastDraws(1);
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Origin = 1000;
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StepSize = ceil((NumberOfDraws-Origin)/100);% So that the computational time does not
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ALPHA = 0.2; % increase too much with the number of simulations.
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ALPHA = 0.2; % increase too much with the number of simulations.
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time = 1:NumberOfDraws;
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xx = Origin:StepSize:NumberOfDraws;
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NumberOfLines = length(xx);
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tmp = zeros(NumberOfDraws*nblck,3);
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UDIAG = zeros(NumberOfLines,6,npar);
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if NumberOfDraws < Origin
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disp('MCMC Diagnostics :: The number of simulations is to small to compute the MCMC convergence diagnostics.')
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return
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end
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if TeX
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fidTeX = fopen([M_.dname '\TeX\' M_.fname '_UnivariateDiagnostics.TeX'],'w');
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fprintf(fidTeX,'%% TeX eps-loader file generated by McmcDiagnostics.m (Dynare).\n');
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fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
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fprintf(fidTeX,' \n');
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fidTeX = fopen([DirectoryName '/' M_.fname '_UnivariateDiagnostics.TeX'],'w');
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fprintf(fidTeX,'%% TeX eps-loader file generated by McmcDiagnostics.m (Dynare).\n');
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fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
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fprintf(fidTeX,' \n');
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end
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disp('MCMC Diagnostics: Univariate convergence diagnostic, Brooks and Gelman (1998):')
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for j=1:npar
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fprintf(' Parameter %d... ',j);
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for b = 1:nblck
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startline = 0;
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for n = 1:LastFileNumber-1
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eval(['load ' M_.dname '/metropolis/' M_.fname '_mh' int2str(n) '_blck' int2str(b)]);
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clear logpo2 post2;
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tmp((b-1)*NumberOfDraws+startline+1:(b-1)*NumberOfDraws+MAX_nruns*n,1) = x2(:,j);
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clear x2;
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startline = startline + MAX_nruns;
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end
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eval(['load ' M_.dname '/metropolis/' M_.fname '_mh' int2str(LastFileNumber) '_blck' int2str(b)]);
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clear logpo2 post2;
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tmp((b-1)*NumberOfDraws+startline+1:(b-1)*NumberOfDraws+MAX_nruns*(LastFileNumber-1)+LastLineNumber,1) = x2(:,j);
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clear x2;
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startline = startline + LastLineNumber;
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end
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tmp(:,2) = kron(transpose(1:nblck),ones(NumberOfDraws,1));
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tmp(:,3) = kron(ones(nblck,1),time');
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tmp = sortrows(tmp,1);
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ligne = 0;
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for iter = Origin:StepSize:NumberOfDraws
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ligne = ligne+1;
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linea = ceil(0.5*iter);
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n = iter-linea+1;
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cinf = round(n*ALPHA/2);
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csup = round(n*(1-ALPHA/2));
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CINF = round(nblck*n*ALPHA/2);
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CSUP = round(nblck*n*(1-ALPHA/2));
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temp = tmp(find((tmp(:,3)>=linea) & (tmp(:,3)<=iter)),1:2);
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UDIAG(ligne,1,j) = temp(CSUP,1)-temp(CINF,1);
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moyenne = mean(temp(:,1));%% Pooled mean.
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UDIAG(ligne,3,j) = sum((temp(:,1)-moyenne).^2)/(nblck*n-1);
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UDIAG(ligne,5,j) = sum(abs(temp(:,1)-moyenne).^3)/(nblck*n-1);
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for i=1:nblck
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pmet = temp(find(temp(:,2)==i));
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UDIAG(ligne,2,j) = UDIAG(ligne,2,j) + pmet(csup,1)-pmet(cinf,1);
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moyenne = mean(pmet,1); %% Within mean.
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UDIAG(ligne,4,j) = UDIAG(ligne,4,j) + sum((pmet(:,1)-moyenne).^2)/(n-1);
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UDIAG(ligne,6,j) = UDIAG(ligne,6,j) + sum(abs(pmet(:,1)-moyenne).^3)/(n-1);
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end
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end
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fprintf('Done! \n');
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end
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UDIAG(:,[2 4 6],:) = UDIAG(:,[2 4 6],:)/nblck;
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disp(' ')
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clear pmet temp moyenne CSUP CINF csup cinf n linea iter tmp;
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pages = floor(npar/3);
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k = 0;
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for i = 1:pages
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h = figure('Name','MCMC univariate diagnostic (Brooks and Gelman,1998)');
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boxplot = 1;
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if TeX
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NAMES = [];
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TEXNAMES = [];
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end
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for j = 1:3 % Loop over parameters
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k = k+1;
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[nam,namtex] = get_the_name(k,TeX);
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for crit = 1:3% Loop over criteria
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if crit == 1
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plt1 = UDIAG(:,1,k);
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plt2 = UDIAG(:,2,k);
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namnam = [nam , ' (Interval)'];
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elseif crit == 2
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plt1 = UDIAG(:,3,k);
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plt2 = UDIAG(:,4,k);
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namnam = [nam , ' (m2)'];
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elseif crit == 3
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plt1 = UDIAG(:,5,k);
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plt2 = UDIAG(:,6,k);
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namnam = [nam , ' (m3)'];
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end
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if TeX
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NAMES = strvcat(NAMES,deblank(namnam));
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TEXNAMES = strvcat(TEXNAMES,deblank(namtex));
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end
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subplot(3,3,boxplot);
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plot(xx,plt1,'-b'); % Pooled
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hold on;
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plot(xx,plt2,'-r'); % Within (mean)
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hold off;
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xlim([xx(1) xx(NumberOfLines)])
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title(namnam,'Interpreter','none')
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boxplot = boxplot + 1;
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end
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end
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eval(['print -depsc2 ' DirectoryName '/' M_.fname '_udiag' int2str(i)]);
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eval(['print -dpdf ' DirectoryName '/' M_.fname '_udiag' int2str(i)]);
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saveas(h,[DirectoryName '/' M_.fname '_udiag' int2str(i) '.fig']);
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if options_.nograph, close(h), end
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if TeX
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fprintf(fidTeX,'\\begin{figure}[H]\n');
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for jj = 1:size(NAMES,1)
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fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
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end
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fprintf(fidTeX,'\\centering \n');
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fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_udiag%s}\n',M_.fname,int2str(i));
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fprintf(fidTeX,'\\caption{Univariate convergence diagnostics for the Metropolis-Hastings.\n');
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fprintf(fidTeX,'The first, second and third columns are respectively the criteria based on\n');
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fprintf(fidTeX,'the eighty percent interval, the second and third moments.}');
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fprintf(fidTeX,'\\label{Fig:UnivariateDiagnostics:%s}\n',int2str(i));
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fprintf(fidTeX,'\\end{figure}\n');
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fprintf(fidTeX,'\n');
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end
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end
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reste = npar-k;
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if reste
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if reste == 1
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nr = 3;
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nc = 1;
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elseif reste == 2;
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nr = 2;
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nc = 3;
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end
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if TeX
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NAMES = [];
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TEXNAMES = [];
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end
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h = figure('Name','MCMC univariate diagnostic (Brooks and Gelman, 1998)');
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boxplot = 1;
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for j = 1:reste
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k = k+1;
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[nam,namtex] = get_the_name(k,TeX);
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for crit = 1:3
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if crit == 1
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plt1 = UDIAG(:,1,k);
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plt2 = UDIAG(:,2,k);
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namnam = [nam , ' (Interval)'];
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elseif crit == 2
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plt1 = UDIAG(:,3,k);
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plt2 = UDIAG(:,4,k);
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namnam = [nam , ' (m2)'];
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elseif crit == 3
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plt1 = UDIAG(:,5,k);
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plt2 = UDIAG(:,6,k);
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namnam = [nam , ' (m3)'];
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end
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if TeX
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NAMES = strvcat(NAMES,deblank(namnam));
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TEXNAMES = strvcat(TEXNAMES,deblank(namtex));
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end
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subplot(nr,nc,boxplot);
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plot(xx,plt1,'-b'); % Pooled
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hold on;
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plot(xx,plt2,'-r'); % Within (mean)
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hold off;
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xlim([xx(1) xx(NumberOfLines)]);
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title(namnam,'Interpreter','none');
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boxplot = boxplot + 1;
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end
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end
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eval(['print -depsc2 ' DirectoryName '/' M_.fname '_udiag' int2str(pages+1)]);
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eval(['print -dpdf ' DirectoryName '/' M_.fname '_udiag' int2str(pages+1)]);
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saveas(h,[DirectoryName '/' M_.fname '_udiag' int2str(pages+1) '.fig']);
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if options_.nograph, close(h), end
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if TeX
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fprintf(fidTeX,'\\begin{figure}[H]\n');
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for jj = 1:size(NAMES,1);
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fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
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end
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fprintf(fidTeX,'\\centering \n');
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fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_udiag%s}\n',M_.fname,int2str(pages+1));
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if reste == 2
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fprintf(fidTeX,'\\caption{Univariate convergence diagnostics for the Metropolis-Hastings.\n');
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fprintf(fidTeX,'The first, second and third columns are respectively the criteria based on\n');
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fprintf(fidTeX,'the eighty percent interval, the second and third moments.}');
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elseif reste == 1
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fprintf(fidTeX,'\\caption{Univariate convergence diagnostics for the Metropolis-Hastings.\n');
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fprintf(fidTeX,'The first, second and third rows are respectively the criteria based on\n');
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fprintf(fidTeX,'the eighty percent interval, the second and third moments.}');
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end
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fprintf(fidTeX,'\\label{Fig:UnivariateDiagnostics:%s}\n',int2str(pages+1));
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fprintf(fidTeX,'\\end{figure}\n');
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fprintf(fidTeX,'\n');
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fprintf(fidTeX,'% End Of TeX file.');
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fclose(fidTeX);
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end
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end % if reste > 0
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clear UDIAG;
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%%
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%% Multivariate diagnostic.
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%%
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if TeX
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fidTeX = fopen([M_.dname '/TeX/' M_.fname '_MultivariateDiagnostics.TeX'],'w');
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fprintf(fidTeX,'%% TeX eps-loader file generated by McmcDiagnostics.m (Dynare).\n');
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fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
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fprintf(fidTeX,' \n');
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NAMES = [];
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end
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tmp = zeros(NumberOfDraws*nblck,3);
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MDIAG = zeros(NumberOfLines,6);
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for b = 1:nblck
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fprintf(' Parameter %d... ',j);
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for b = 1:nblck
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startline = 0;
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for n = 1:LastFileNumber-1
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eval(['load ' M_.dname '/metropolis/' M_.fname '_mh' int2str(n) '_blck' int2str(b)]);
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clear x2 post2;
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tmp((b-1)*NumberOfDraws+startline+1:(b-1)*NumberOfDraws+MAX_nruns*n,1) = logpo2;
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startline = startline+MAX_nruns;
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for n = 1:NumberOfMcFilesPerBlock-1
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%eval(['load ' M_.dname '/metropolis/' M_.fname '_mh' int2str(n) '_blck' int2str(b)]);
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load([MhDirectoryName '/' mcfiles(n,1,b).name],'x2');
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%clear logpo2 post2;
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tmp((b-1)*NumberOfDraws+startline+1:(b-1)*NumberOfDraws+MAX_nruns*n,1) = x2(:,j);
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clear x2;
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startline = startline + MAX_nruns;
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end
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eval(['load ' M_.dname '/metropolis/' M_.fname '_mh' int2str(LastFileNumber) '_blck' int2str(b)]);
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clear x2 post2;
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tmp((b-1)*NumberOfDraws+startline+1:(b-1)*NumberOfDraws+ MAX_nruns*(LastFileNumber-1)+LastLineNumber,1) = logpo2;
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end
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clear logpo2;
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tmp(:,2) = kron(transpose(1:nblck),ones(NumberOfDraws,1));
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tmp(:,3) = kron(ones(nblck,1),time');
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tmp = sortrows(tmp,1);
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ligne = 0;
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for iter = Origin:StepSize:NumberOfDraws
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load([MhDirectoryName '/' mcfiles(NumberOfMcFilesPerBlock,1,b).name],'x2');
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% eval(['load ' M_.dname '/metropolis/' M_.fname '_mh' int2str(LastFileNumber) '_blck' int2str(b)]);
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% clear logpo2 post2;
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tmp((b-1)*NumberOfDraws+startline+1:(b-1)*NumberOfDraws+MAX_nruns*(LastFileNumber-1)+LastLineNumber,1) = x2(:,j);
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clear x2;
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startline = startline + LastLineNumber;
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end
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tmp(:,2) = kron(transpose(1:nblck),ones(NumberOfDraws,1));
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tmp(:,3) = kron(ones(nblck,1),time');
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tmp = sortrows(tmp,1);
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ligne = 0;
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for iter = Origin:StepSize:NumberOfDraws
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ligne = ligne+1;
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linea = ceil(0.5*iter);
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n = iter-linea+1;
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@ -262,65 +88,267 @@ for iter = Origin:StepSize:NumberOfDraws
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CINF = round(nblck*n*ALPHA/2);
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CSUP = round(nblck*n*(1-ALPHA/2));
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temp = tmp(find((tmp(:,3)>=linea) & (tmp(:,3)<=iter)),1:2);
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MDIAG(ligne,1) = temp(CSUP,1)-temp(CINF,1);
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UDIAG(ligne,1,j) = temp(CSUP,1)-temp(CINF,1);
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moyenne = mean(temp(:,1));%% Pooled mean.
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MDIAG(ligne,3) = sum((temp(:,1)-moyenne).^2)/(nblck*n-1);
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MDIAG(ligne,5) = sum(abs(temp(:,1)-moyenne).^3)/(nblck*n-1);
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UDIAG(ligne,3,j) = sum((temp(:,1)-moyenne).^2)/(nblck*n-1);
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UDIAG(ligne,5,j) = sum(abs(temp(:,1)-moyenne).^3)/(nblck*n-1);
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for i=1:nblck
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pmet = temp(find(temp(:,2)==i));
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MDIAG(ligne,2) = MDIAG(ligne,2) + pmet(csup,1)-pmet(cinf,1);
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moyenne = mean(pmet,1); %% Within mean.
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MDIAG(ligne,4) = MDIAG(ligne,4) + sum((pmet(:,1)-moyenne).^2)/(n-1);
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MDIAG(ligne,6) = MDIAG(ligne,6) + sum(abs(pmet(:,1)-moyenne).^3)/(n-1);
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pmet = temp(find(temp(:,2)==i));
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UDIAG(ligne,2,j) = UDIAG(ligne,2,j) + pmet(csup,1)-pmet(cinf,1);
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moyenne = mean(pmet,1); %% Within mean.
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UDIAG(ligne,4,j) = UDIAG(ligne,4,j) + sum((pmet(:,1)-moyenne).^2)/(n-1);
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UDIAG(ligne,6,j) = UDIAG(ligne,6,j) + sum(abs(pmet(:,1)-moyenne).^3)/(n-1);
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end
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end
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fprintf('Done! \n');
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end
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UDIAG(:,[2 4 6],:) = UDIAG(:,[2 4 6],:)/nblck;
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disp(' ')
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clear pmet temp moyenne CSUP CINF csup cinf n linea iter tmp;
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pages = floor(npar/3);
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k = 0;
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for i = 1:pages
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if options_.nograph
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h = figure('Name','MCMC univariate diagnostic (Brooks and Gelman,1998)','Visible','off');
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else
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h = figure('Name','MCMC univariate diagnostic (Brooks and Gelman,1998)');
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end
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boxplot = 1;
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if TeX
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NAMES = [];
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TEXNAMES = [];
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end
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for j = 1:3 % Loop over parameters
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k = k+1;
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[nam,namtex] = get_the_name(k,TeX);
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for crit = 1:3% Loop over criteria
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if crit == 1
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plt1 = UDIAG(:,1,k);
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plt2 = UDIAG(:,2,k);
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namnam = [nam , ' (Interval)'];
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elseif crit == 2
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plt1 = UDIAG(:,3,k);
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plt2 = UDIAG(:,4,k);
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namnam = [nam , ' (m2)'];
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elseif crit == 3
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plt1 = UDIAG(:,5,k);
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plt2 = UDIAG(:,6,k);
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namnam = [nam , ' (m3)'];
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end
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if TeX
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NAMES = strvcat(NAMES,deblank(namnam));
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TEXNAMES = strvcat(TEXNAMES,deblank(namtex));
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end
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subplot(3,3,boxplot);
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plot(xx,plt1,'-b'); % Pooled
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hold on;
|
||||
plot(xx,plt2,'-r'); % Within (mean)
|
||||
hold off;
|
||||
xlim([xx(1) xx(NumberOfLines)])
|
||||
title(namnam,'Interpreter','none')
|
||||
boxplot = boxplot + 1;
|
||||
end
|
||||
end
|
||||
eval(['print -depsc2 ' DirectoryName '/' M_.fname '_udiag' int2str(i)]);
|
||||
eval(['print -dpdf ' DirectoryName '/' M_.fname '_udiag' int2str(i)]);
|
||||
saveas(h,[DirectoryName '/' M_.fname '_udiag' int2str(i) '.fig']);
|
||||
if options_.nograph, close(h), end
|
||||
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',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
|
||||
if TeX
|
||||
NAMES = [];
|
||||
TEXNAMES = [];
|
||||
end
|
||||
if options_.nograph
|
||||
h = figure('Name','MCMC univariate diagnostic (Brooks and Gelman, 1998)','Visible','off');
|
||||
else
|
||||
h = figure('Name','MCMC univariate diagnostic (Brooks and Gelman, 1998)');
|
||||
end
|
||||
boxplot = 1;
|
||||
for j = 1:reste
|
||||
k = k+1;
|
||||
[nam,namtex] = get_the_name(k,TeX);
|
||||
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
|
||||
NAMES = strvcat(NAMES,deblank(namnam));
|
||||
TEXNAMES = strvcat(TEXNAMES,deblank(namtex));
|
||||
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
|
||||
eval(['print -depsc2 ' DirectoryName '/' M_.fname '_udiag' int2str(pages+1)]);
|
||||
eval(['print -dpdf ' DirectoryName '/' M_.fname '_udiag' int2str(pages+1)]);
|
||||
saveas(h,[DirectoryName '/' M_.fname '_udiag' int2str(pages+1) '.fig']);
|
||||
if options_.nograph, close(h), end
|
||||
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',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');
|
||||
NAMES = [];
|
||||
end
|
||||
tmp = zeros(NumberOfDraws*nblck,3);
|
||||
MDIAG = zeros(NumberOfLines,6);
|
||||
for b = 1:nblck
|
||||
startline = 0;
|
||||
for n = 1:NumberOfMcFilesPerBlock-1
|
||||
% eval(['load ' M_.dname '/metropolis/' M_.fname '_mh' int2str(n) '_blck' int2str(b)]);
|
||||
% clear x2 post2;
|
||||
load([MhDirectoryName '/' mcfiles(n,1,b).name],'logpo2');
|
||||
tmp((b-1)*NumberOfDraws+startline+1:(b-1)*NumberOfDraws+MAX_nruns*n,1) = logpo2;
|
||||
startline = startline+MAX_nruns;
|
||||
end
|
||||
load([MhDirectoryName '/' mcfiles(NumberOfMcFilesPerBlock,1,b).name],'logpo2');
|
||||
% eval(['load ' M_.dname '/metropolis/' M_.fname '_mh' int2str(LastFileNumber) '_blck' int2str(b)]);
|
||||
% clear x2 post2;
|
||||
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(0.5*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 = figure('Name','Multivatiate diagnostic');
|
||||
if options_.nograph
|
||||
h = figure('Name','Multivatiate diagnostic','Visible','off');
|
||||
else
|
||||
h = figure('Name','Multivatiate diagnostic');
|
||||
end
|
||||
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
|
||||
NAMES = strvcat(NAMES,namnam);
|
||||
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;
|
||||
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
|
||||
NAMES = strvcat(NAMES,namnam);
|
||||
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
|
||||
eval(['print -depsc2 ' DirectoryName '/' M_.fname '_mdiag']);
|
||||
eval(['print -dpdf ' DirectoryName '/' M_.fname '_mdiag']);
|
||||
saveas(h,[DirectoryName '/' M_.fname '_mdiag.fig']);
|
||||
if options_.nograph, close(h), end
|
||||
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',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);
|
||||
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',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
|
||||
|
|
|
|||
|
|
@ -99,7 +99,7 @@ if options_.load_mh_file == 0
|
|||
record.LastLogLiK = zeros(nblck,1);
|
||||
record.LastFileNumber = AnticipatedNumberOfFiles+1;
|
||||
record.LastLineNumber = AnticipatedNumberOfLinesInTheLastFile;
|
||||
save([DirectoryName '/' M_.fname '_mh_history'],'record');
|
||||
save([MhDirectoryName '/' M_.fname '_mh_history'],'record');
|
||||
elseif options_.load_mh_file == 1% Here we consider previous mh files (previous mh did not crash).
|
||||
disp('MH: I''m loading past metropolis-hastings simulations...')
|
||||
file = dir([ MhDirectoryName '/' M_.fname '_mh_history.mat' ]);
|
||||
|
|
|
|||
Loading…
Reference in New Issue