diff --git a/matlab/CheckPath.m b/matlab/CheckPath.m
index 0e09700f5..41bd30263 100644
--- a/matlab/CheckPath.m
+++ b/matlab/CheckPath.m
@@ -4,6 +4,6 @@ global M_
 
 DirectoryName = [ M_.dname '/' type ];
 
-if ~isdir(DirectoryName) 
-    mkdir('.',DirectoryName); 
+if ~isdir(DirectoryName)
+    mkdir('.',DirectoryName);
 end
\ No newline at end of file
diff --git a/matlab/McMCDiagnostics.m b/matlab/McMCDiagnostics.m
index 572e4f397..f5f8910f4 100644
--- a/matlab/McMCDiagnostics.m
+++ b/matlab/McMCDiagnostics.m
@@ -3,7 +3,8 @@ function McmcDiagnostic
 
 global options_ estim_params_ M_ 
 
-DirectoryName = CheckPath('Plots/Diagnostics');
+DirectoryName = CheckPath('Output');
+MhDirectoryName = CheckPath('metropolis');
 
 TeX = options_.TeX;
 nblck = options_.mh_nblck;
@@ -18,8 +19,15 @@ npar = npar + estim_params_.ncn;
 npar = npar + estim_params_.np ;
 MAX_nruns = ceil(options_.MaxNumberOfBytes/(npar+2)/8);
 
-load(['./' M_.dname '/metropolis/' M_.fname '_mh_history.mat'])
+load([MhDirectoryName '/'  M_.fname '_mh_history.mat'])
 
+mcfiles = [];
+for blck = 1:nblck
+  mcfiles = cat(3,mcfiles,dir([MhDirectoryName '/' M_.fname '_mh*_blck' int2str(blck) '.mat']));
+end
+NumberOfMcFilesPerBlock = size(mcfiles,1);
+
+  
 PastDraws = sum(record.MhDraws,1);
 LastFileNumber = PastDraws(2);
 LastLineNumber = record.MhDraws(end,3);
@@ -27,233 +35,51 @@ 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. 
+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([M_.dname '\TeX\' 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');
+  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):')
 for j=1:npar
-    fprintf('    Parameter %d...  ',j);
-    for b = 1:nblck
-        startline = 0;
-        for n = 1:LastFileNumber-1
-            eval(['load ' M_.dname '/metropolis/' M_.fname '_mh' int2str(n) '_blck' int2str(b)]);
-            clear logpo2 post2;
-            tmp((b-1)*NumberOfDraws+startline+1:(b-1)*NumberOfDraws+MAX_nruns*n,1) = x2(:,j);
-            clear x2;
-            startline = startline + MAX_nruns;
-        end
-        eval(['load ' M_.dname '/metropolis/' M_.fname '_mh' int2str(LastFileNumber) '_blck' int2str(b)]);
-        clear logpo2 post2;
-        tmp((b-1)*NumberOfDraws+startline+1:(b-1)*NumberOfDraws+MAX_nruns*(LastFileNumber-1)+LastLineNumber,1) = x2(:,j);
-        clear x2;
-        startline = startline + LastLineNumber;
-    end
-    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);
-        UDIAG(ligne,1,j) = temp(CSUP,1)-temp(CINF,1);
-        moyenne = mean(temp(:,1));%% Pooled mean.
-        UDIAG(ligne,3,j) = sum((temp(:,1)-moyenne).^2)/(nblck*n-1);
-        UDIAG(ligne,5,j) = sum(abs(temp(:,1)-moyenne).^3)/(nblck*n-1);
-        for i=1:nblck
-            pmet = temp(find(temp(:,2)==i));
-            UDIAG(ligne,2,j) = UDIAG(ligne,2,j) + pmet(csup,1)-pmet(cinf,1);
-            moyenne = mean(pmet,1); %% Within mean. 
-            UDIAG(ligne,4,j) = UDIAG(ligne,4,j) + sum((pmet(:,1)-moyenne).^2)/(n-1);
-            UDIAG(ligne,6,j) = UDIAG(ligne,6,j) + sum(abs(pmet(:,1)-moyenne).^3)/(n-1);
-        end
-    end
-    fprintf('Done! \n');
-end
-UDIAG(:,[2 4 6],:) = UDIAG(:,[2 4 6],:)/nblck;
-disp(' ')
-clear pmet temp moyenne CSUP CINF csup cinf n linea iter tmp;    
-pages = floor(npar/3);
-k = 0;  
-for i = 1:pages
-    h = figure('Name','MCMC univariate diagnostic (Brooks and Gelman,1998)');
-    boxplot = 1;
-    if TeX
-        NAMES = [];
-        TEXNAMES = [];
-    end
-    for j = 1:3 % Loop over parameters
-        k = k+1;
-        [nam,namtex] = get_the_name(k,TeX);
-        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
-                NAMES = strvcat(NAMES,deblank(namnam));
-                TEXNAMES = strvcat(TEXNAMES,deblank(namtex));
-            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
-    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
-    h = figure('Name','MCMC univariate diagnostic (Brooks and Gelman, 1998)');
-    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([M_.dname '/TeX/' 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
+  fprintf('    Parameter %d...  ',j);
+  for b = 1:nblck
     startline = 0;
-    for n = 1:LastFileNumber-1
-        eval(['load ' M_.dname '/metropolis/' M_.fname '_mh' int2str(n) '_blck' int2str(b)]);
-        clear x2 post2;
-        tmp((b-1)*NumberOfDraws+startline+1:(b-1)*NumberOfDraws+MAX_nruns*n,1) = logpo2;
-        startline = startline+MAX_nruns;
+    for n = 1:NumberOfMcFilesPerBlock-1
+      %eval(['load ' M_.dname '/metropolis/' M_.fname '_mh' int2str(n) '_blck' int2str(b)]);
+      load([MhDirectoryName '/' mcfiles(n,1,b).name],'x2');
+      %clear logpo2 post2;
+      tmp((b-1)*NumberOfDraws+startline+1:(b-1)*NumberOfDraws+MAX_nruns*n,1) = x2(:,j);
+      clear x2;
+      startline = startline + MAX_nruns;
     end
-    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
+    load([MhDirectoryName '/' mcfiles(NumberOfMcFilesPerBlock,1,b).name],'x2');
+    % eval(['load ' M_.dname '/metropolis/' M_.fname '_mh' int2str(LastFileNumber) '_blck' int2str(b)]);
+    % clear logpo2 post2;
+    tmp((b-1)*NumberOfDraws+startline+1:(b-1)*NumberOfDraws+MAX_nruns*(LastFileNumber-1)+LastLineNumber,1) = x2(:,j);
+    clear x2;
+    startline = startline + LastLineNumber;
+  end
+  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;
@@ -262,65 +88,267 @@ for iter  = Origin:StepSize:NumberOfDraws
     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);
+    UDIAG(ligne,1,j) = 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);
+    UDIAG(ligne,3,j) = sum((temp(:,1)-moyenne).^2)/(nblck*n-1);
+    UDIAG(ligne,5,j) = 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);
+      pmet = temp(find(temp(:,2)==i));
+      UDIAG(ligne,2,j) = UDIAG(ligne,2,j) + pmet(csup,1)-pmet(cinf,1);
+      moyenne = mean(pmet,1); %% Within mean. 
+      UDIAG(ligne,4,j) = UDIAG(ligne,4,j) + sum((pmet(:,1)-moyenne).^2)/(n-1);
+      UDIAG(ligne,6,j) = UDIAG(ligne,6,j) + sum(abs(pmet(:,1)-moyenne).^3)/(n-1);
     end
+  end
+  fprintf('Done! \n');
+end
+UDIAG(:,[2 4 6],:) = UDIAG(:,[2 4 6],:)/nblck;
+disp(' ')
+clear pmet temp moyenne CSUP CINF csup cinf n linea iter tmp;    
+pages = floor(npar/3);
+k = 0;  
+for i = 1:pages
+  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;
+  if TeX
+    NAMES = [];
+    TEXNAMES = [];
+  end
+  for j = 1:3 % Loop over parameters
+    k = k+1;
+    [nam,namtex] = get_the_name(k,TeX);
+    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
+        NAMES = strvcat(NAMES,deblank(namnam));
+        TEXNAMES = strvcat(TEXNAMES,deblank(namtex));
+      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
+  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
diff --git a/matlab/metropolis.m b/matlab/metropolis.m
index ac9dd31f0..67004f2d8 100644
--- a/matlab/metropolis.m
+++ b/matlab/metropolis.m
@@ -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' ]);