diff --git a/matlab/correlation_mc_analysis.m b/matlab/correlation_mc_analysis.m
new file mode 100644
index 000000000..578304b93
--- /dev/null
+++ b/matlab/correlation_mc_analysis.m
@@ -0,0 +1,152 @@
+function oo_ = correlation_mc_analysis(SampleSize,type,dname,fname,vartan,nvar,var1,var2,nar,mh_conf_sig,oo_,M_,options_)
+% This function analyses the (posterior or prior) distribution of the
+% endogenous variables correlation function.
+
+% Copyright (C) 2008-2009 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/>.
+
+    if strcmpi(type,'posterior')
+        TYPE = 'Posterior';
+        PATH = [dname '/metropolis/']
+    else
+        TYPE = 'Prior';
+        PATH = [dname '/prior/moments/']
+    end
+
+    indx1 = check_name(vartan,var1);
+    if isempty(indx1)
+        disp([ type '_analysis:: ' var1 ' is not a stationary endogenous variable!'])
+        return
+    end
+    if ~isempty(var2)
+        indx2 = check_name(vartan,var2);
+        if isempty(indx2)
+            disp([ type '_analysis:: ' var2 ' is not a stationary endogenous variable!'])
+            return
+        end
+    else
+        indx2 = indx1;
+        var2 = var1;
+    end
+`
+    if isfield(oo_,[TYPE 'TheoreticalMoments'])
+        eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])
+        if isfield(temporary_structure,'dsge')
+            eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
+            if isfield(temporary_structure,'correlation')
+                eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.mean;'])
+                if isfield(temporary_structure,var1)
+                    eval(['temporary_structure_1 = oo_.' TYPE 'TheoreticalMoments.dsge.mean.' var1 ';']) 
+                    if isfield(temporary_structure_1,var2)
+                        eval(['temporary_structure_2 = temporary_structure_1.' var2 ';'])
+                        l1 = length(temporary_structure_2);
+                        if l1<nar
+                            % INITIALIZATION:
+                            oo_ = initialize_output_structure(var1,var2,nar,type,oo_);
+                            delete([PATH fname '_' TYPE 'Correlations*'])
+                            [nvar,vartan,NumberOfFiles] = ...
+                                dsge_simulated_theoretical_correlation(SampleSize,nar,M_,options_,oo_,type);
+                        else
+                            if ~isnan(temporary_structure_2(nar))
+                                %Nothing to do.
+                                return
+                            end
+                        end
+                    else
+                        oo_ = initialize_output_structure(var1,var2,nar,TYPE,oo_);
+                    end
+                else
+                    oo_ = initialize_output_structure(var1,var2,nar,TYPE,oo_);
+                end
+            else
+                oo_ = initialize_output_structure(var1,var2,nar,TYPE,oo_);
+            end
+        else
+            oo_ = initialize_output_structure(var1,var2,nar,TYPE,oo_);
+        end
+    else
+        oo_ = initialize_output_structure(var1,var2,nar,TYPE,oo_);
+    end
+    ListOfFiles = dir([ PATH  fname '_' TYPE 'Correlations*.mat']);
+    i1 = 1; tmp = zeros(SampleSize,1);
+    for file = 1:length(ListOfFiles)
+        load([ PATH  fname '_' TYPE 'PosteriorCorrelations' int2str(file) '.mat']);
+        i2 = i1 + rows(Correlation_array) - 1;
+        tmp(i1:i2) = Correlation_array(:,indx1,indx2,nar);
+        i1 = i2+1;
+    end
+    name = [ var1 '.' var2 ];
+    if ~isconst(tmp)
+        [p_mean, p_median, p_var, hpd_interval, p_deciles, density] = ...
+            posterior_moments(tmp,1,mh_conf_sig);
+        if isfield(oo_,'PosteriorTheoreticalMoments')
+            eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])
+            if isfield(temporary_structure,'dsge')
+                eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
+                if isfield(temporary_structure,'correlation')
+                    oo_ = fill_output_structure(var1,var2,TYPE,oo_,'mean',nar,p_mean);
+                    oo_ = fill_output_structure(var1,var2,TYPE,oo_,'median',nar,p_median);
+                    oo_ = fill_output_structure(var1,var2,TYPE,oo_,'variance',nar,p_var);
+                    oo_ = fill_output_structure(var1,var2,TYPE,oo_,'hpdinf',nar,hpd_interval(1));
+                    oo_ = fill_output_structure(var1,var2,TYPE,oo_,'hpdsup',nar,hpd_interval(2));
+                    oo_ = fill_output_structure(var1,var2,TYPE,oo_,'deciles',nar,p_deciles);
+                    oo_ = fill_output_structure(var1,var2,TYPE,oo_,'density',nar,density);
+                end
+            end
+        end
+    else
+        if isfield(oo_,'PosteriorTheoreticalMoments')
+            eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])
+            if isfield(temporary_structure,'dsge')
+                eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
+                if isfield(temporary_structure,'correlation')
+                    oo_ = fill_output_structure(var1,var2,TYPE,oo_,'mean',nar,NaN);
+                    oo_ = fill_output_structure(var1,var2,TYPE,oo_,'median',nar,NaN);
+                    oo_ = fill_output_structure(var1,var2,TYPE,oo_,'variance',nar,NaN);
+                    oo_ = fill_output_structure(var1,var2,TYPE,oo_,'hpdinf',nar,NaN);
+                    oo_ = fill_output_structure(var1,var2,TYPE,oo_,'hpdsup',nar,NaN);
+                    oo_ = fill_output_structure(var1,var2,TYPE,oo_,'deciles',nar,NaN);
+                    oo_ = fill_output_structure(var1,var2,TYPE,oo_,'density',nar,NaN);
+                end
+            end
+        end
+    end
+    
+function oo_ = initialize_output_structure(var1,var2,nar,type,oo_)
+    name = [ var1 '.' var2 ];
+    eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.mean.' name ' = NaN(' int2str(nar) ',1);']);
+    eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.median.' name ' = NaN(' int2str(nar) ',1);']);
+    eval(['oo_.' type 'PosteriorTheoreticalMoments.dsge.correlation.variance.' name ' = NaN(' int2str(nar) ',1);']);
+    eval(['oo_.' type 'PosteriorTheoreticalMoments.dsge.correlation.hpdinf.' name ' = NaN(' int2str(nar) ',1);']);
+    eval(['oo_.' type 'PosteriorTheoreticalMoments.dsge.correlation.hpdsup.' name ' = NaN(' int2str(nar) ',1);']);
+    eval(['oo_.' type 'PosteriorTheoreticalMoments.dsge.correlation.deciles.' name ' = cell(' int2str(nar) ',1);']);
+    eval(['oo_.' type 'PosteriorTheoreticalMoments.dsge.correlation.density.' name ' = cell(' int2str(nar) ',1);']);
+    for i=1:nar
+        eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.density.' name '(' int2str(i) ',1) = {NaN};']);
+        eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.deciles.' name '(' int2str(i) ',1) = {NaN};']);
+    end
+    
+function oo_ = fill_output_structure(var1,var2,type,oo_,lag,result)
+    name = [ var1 '.' var2 ];
+    switch type
+      case {'mean','median','variance','hpdinf','hpdsup'} 
+        eval(['oo_.' type  'TheoreticalMoments.dsge.correlation.' type '.' name '(' int2str(lag) ',1) = result;']);
+      case {'deciles','density'}
+        eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.' type '.' name '(' int2str(lag) ',1) = {result};']);
+      otherwise
+        disp('fill_output_structure:: Unknown field!')
+    end
\ No newline at end of file
diff --git a/matlab/correlation_posterior_analysis.m b/matlab/correlation_posterior_analysis.m
deleted file mode 100644
index f7cefec01..000000000
--- a/matlab/correlation_posterior_analysis.m
+++ /dev/null
@@ -1,135 +0,0 @@
-function oo_ = correlation_posterior_analysis(SampleSize,dname,fname,vartan,nvar,var1,var2,nar,mh_conf_sig,oo_,M_,options_)
-
-% Copyright (C) 2008 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/>.
-
-    indx1 = check_name(vartan,var1);
-    if isempty(indx1)
-        disp(['posterior_analysis:: ' var1 ' is not a stationary endogenous variable!'])
-        return
-    end
-    if ~isempty(var2)
-        indx2 = check_name(vartan,var2);
-        if isempty(indx2)
-            disp(['posterior_analysis:: ' var2 ' is not a stationary endogenous variable!'])
-            return
-        end
-    else
-        indx2 = indx1;
-        var2 = var1;
-    end
-    if isfield(oo_,'PosteriorTheoreticalMoments')
-        if isfield(oo_.PosteriorTheoreticalMoments,'dsge')
-            if isfield(oo_.PosteriorTheoreticalMoments.dsge,'correlation')
-                if isfield(oo_.PosteriorTheoreticalMoments.dsge.correlation.mean,var1)
-                    eval(['s1 = oo_.PosteriorTheoreticalMoments.dsge.correlation.mean' '.' var1 ';'])  
-                    if isfield(s1,var2)
-                        eval(['s2 = s1' '.' var2 ';'])
-                        l1 = length(s2);
-                        if l1<nar
-                            % INITIALIZATION:
-                            oo_ = initialize_output_structure(var1,var2,nar,oo_);
-                            system(['rm ' M_.dname '/metropolis/' M_.fname '_PosteriorCorrelations*']);
-                            [nvar,vartan,NumberOfFiles] = ...
-                                dsge_posterior_theoretical_correlation(SampleSize,nar,M_,options_,oo_);
-                        else
-                            if ~isnan(s2(nar))
-                                %Nothing to do.
-                                return
-                            end
-                        end
-                    else
-                        oo_ = initialize_output_structure(var1,var2,nar,oo_);
-                    end
-                else
-                    oo_ = initialize_output_structure(var1,var2,nar,oo_);
-                end
-            else
-                oo_ = initialize_output_structure(var1,var2,nar,oo_);
-            end
-        else
-            oo_ = initialize_output_structure(var1,var2,nar,oo_);
-        end
-    else
-        oo_ = initialize_output_structure(var1,var2,nar,oo_);
-    end
-    tmp = dir([ dname '/metropolis/'  fname '_PosteriorCorrelations*.mat']);
-    NumberOfFiles = length(tmp);
-    i1 = 1; tmp = zeros(SampleSize,1);
-    for file = 1:NumberOfFiles
-        load([ dname '/metropolis/'  fname '_PosteriorCorrelations' int2str(file) '.mat']);
-        i2 = i1 + rows(Correlation_array) - 1;
-        tmp(i1:i2) = Correlation_array(:,indx1,indx2,nar);
-        i1 = i2+1;
-    end
-    name = [ var1 '.' var2 ];
-    if ~isconst(tmp)
-        [post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
-            posterior_moments(tmp,1,mh_conf_sig);
-        if isfield(oo_,'PosteriorTheoreticalMoments')
-            if isfield(oo_.PosteriorTheoreticalMoments,'dsge')
-                if isfield(oo_.PosteriorTheoreticalMoments.dsge,'correlation')
-                    oo_ = fill_output_structure(var1,var2,oo_,'mean',nar,post_mean);
-                    oo_ = fill_output_structure(var1,var2,oo_,'median',nar,post_median);
-                    oo_ = fill_output_structure(var1,var2,oo_,'variance',nar,post_var);
-                    oo_ = fill_output_structure(var1,var2,oo_,'hpdinf',nar,hpd_interval(1));
-                    oo_ = fill_output_structure(var1,var2,oo_,'hpdsup',nar,hpd_interval(2));
-                    oo_ = fill_output_structure(var1,var2,oo_,'deciles',nar,post_deciles);
-                    oo_ = fill_output_structure(var1,var2,oo_,'density',nar,density);
-                end
-            end
-        end
-    else
-        if isfield(oo_,'PosteriorTheoreticalMoments')
-            if isfield(oo_.PosteriorTheoreticalMoments,'dsge')
-                if isfield(oo_.PosteriorTheoreticalMoments.dsge,'correlation')
-                    oo_ = fill_output_structure(var1,var2,oo_,'mean',nar,NaN);
-                    oo_ = fill_output_structure(var1,var2,oo_,'median',nar,NaN);
-                    oo_ = fill_output_structure(var1,var2,oo_,'variance',nar,NaN);
-                    oo_ = fill_output_structure(var1,var2,oo_,'hpdinf',nar,NaN);
-                    oo_ = fill_output_structure(var1,var2,oo_,'hpdsup',nar,NaN);
-                    oo_ = fill_output_structure(var1,var2,oo_,'deciles',nar,NaN);
-                    oo_ = fill_output_structure(var1,var2,oo_,'density',nar,NaN);
-                end
-            end
-        end
-    end
-    
-function oo_ = initialize_output_structure(var1,var2,nar,oo_)
-    name = [ var1 '.' var2 ];
-    eval(['oo_.PosteriorTheoreticalMoments.dsge.correlation.mean.' name ' = NaN(' int2str(nar) ',1);']);
-    eval(['oo_.PosteriorTheoreticalMoments.dsge.correlation.median.' name ' = NaN(' int2str(nar) ',1);']);
-    eval(['oo_.PosteriorTheoreticalMoments.dsge.correlation.variance.' name ' = NaN(' int2str(nar) ',1);']);
-    eval(['oo_.PosteriorTheoreticalMoments.dsge.correlation.hpdinf.' name ' = NaN(' int2str(nar) ',1);']);
-    eval(['oo_.PosteriorTheoreticalMoments.dsge.correlation.hpdsup.' name ' = NaN(' int2str(nar) ',1);']);
-    eval(['oo_.PosteriorTheoreticalMoments.dsge.correlation.deciles.' name ' = cell(' int2str(nar) ',1);']);
-    eval(['oo_.PosteriorTheoreticalMoments.dsge.correlation.density.' name ' = cell(' int2str(nar) ',1);']);
-    for i=1:nar
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.correlation.density.' name '(' int2str(i) ',1) = {NaN};']);
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.correlation.deciles.' name '(' int2str(i) ',1) = {NaN};']);
-    end
-    
-function oo_ = fill_output_structure(var1,var2,oo_,type,lag,result)
-    name = [ var1 '.' var2 ];
-    switch type
-      case {'mean','median','variance','hpdinf','hpdsup'} 
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.correlation.' type '.' name '(' int2str(lag) ',1) = result;']);
-      case {'deciles','density'}
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.correlation.' type '.' name '(' int2str(lag) ',1) = {result};']);
-      otherwise
-        disp('fill_output_structure:: Unknown field!')
-    end
\ No newline at end of file
diff --git a/matlab/covariance_mc_analysis.m b/matlab/covariance_mc_analysis.m
new file mode 100644
index 000000000..f907c0be7
--- /dev/null
+++ b/matlab/covariance_mc_analysis.m
@@ -0,0 +1,100 @@
+function oo_ = covariance_mc_analysis(NumberOfSimulations,type,dname,fname,vartan,nvar,var1,var2,mh_conf_sig,oo_)
+% This function analyses the (posterior or prior) distribution of the
+% endogenous variables covariance matrix.
+
+% Copyright (C) 2008-2009 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/>.
+
+    if strcmpi(type,'posterior')
+        TYPE = 'Posterior';
+        PATH = [dname '/metropolis/']
+        posterior = 1;
+    else
+        TYPE = 'Prior';
+        PATH = [dname '/prior/moments/']
+        posterior = 0;
+    end
+
+    indx1 = check_name(vartan,var1);
+    if isempty(indx1)
+        disp([ type '_analysis:: ' var1 ' is not a stationary endogenous variable!'])
+        return
+    end
+    if ~isempty(var2)
+        indx2 = check_name(vartan,var2);
+        if isempty(indx2)
+            disp([ prior '_analysis:: ' var2 ' is not a stationary endogenous variable!'])
+            return
+        end
+    else
+        indx2 = indx1;
+        var2 = var1;
+    end
+
+    if isfield(oo_,[ TYPE 'TheoreticalMoments'])
+        eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])   
+        if isfield(temporary_structure,'dsge')
+            eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
+            if isfield(temporary_structure,'covariance')
+                eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.covariance.mean;'])
+                if isfield(temporary_structure,var1)
+                    eval(['temporary_structure_1 = oo_.' TYPE 'TheoreticalMoments.dsge.covariance.mean.' var1 ';'])
+                    if isfield(temporary_structure_1,var2)
+                        % Nothing to do (the covariance matrix is symmetric!).
+                        return
+                    end
+                else
+                    if isfield(temporary_structure,var2)
+                        eval(['temporary_structure_2 = oo_.' TYPE 'TheoreticalMoments.dsge.covariance.mean.' var2 ';'])
+                        if isfield(temporary_structure_2,var1)
+                            % Nothing to do (the covariance matrix is symmetric!).
+                            return
+                        end
+                    end
+                end
+            end
+        end
+    end
+
+    ListOfFiles = dir([ PATH  fname '_' TYPE '2ndOrderMoments*.mat']);
+    i1 = 1; tmp = zeros(NumberOfSimulations,1);
+    for file = 1:length(ListOfFiles)
+        load([ PATH ListOfFiles(file).name ]);
+        i2 = i1 + rows(Covariance_matrix) - 1;
+        tmp(i1:i2) = Covariance_matrix(:,symmetric_matrix_index(indx1,indx2,nvar));
+        i1 = i2+1;
+    end
+    name = [var1 '.' var2];
+    if ~isconst(tmp)
+        [p_mean, p_median, p_var, hpd_interval, p_deciles, density] = ...
+            posterior_moments(tmp,1,mh_conf_sig);
+        eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.mean.' name ' = p_mean;']);
+        eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.median.' name ' = p_median;']);
+        eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.variance.' name ' = p_var;']);
+        eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.hpdinf.' name ' = hpd_interval(1);']);
+        eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.hpdsup.' name ' = hpd_interval(2);']);
+        eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.deciles.' name ' = p_deciles;']);
+        eval(['oo_.' TYPE 'Theoreticalmoments.dsge.covariance.density.' name ' = density;']);
+    else
+        eval(['oo_.' NAME 'TheoreticalMoments.dsge.covariance.mean.' name ' = NaN;']);
+        eval(['oo_.' NAME 'TheoreticalMoments.dsge.covariance.median.' name ' = NaN;']);
+        eval(['oo_.' NAME 'TheoreticalMoments.dsge.covariance.variance.' name ' = NaN;']);
+        eval(['oo_.' NAME 'TheoreticalMoments.dsge.covariance.hpdinf.' name ' = NaN;']);
+        eval(['oo_.' NAME 'TheoreticalMoments.dsge.covariance.hpdsup.' name ' = NaN;']);
+        eval(['oo_.' NAME 'TheoreticalMoments.dsge.covariance.deciles.' name ' = NaN;']);
+        eval(['oo_.' NAME 'TheoreticalMoments.dsge.covariance.density.' name ' = NaN;']);
+    end
\ No newline at end of file
diff --git a/matlab/covariance_posterior_analysis.m b/matlab/covariance_posterior_analysis.m
deleted file mode 100644
index b879c5731..000000000
--- a/matlab/covariance_posterior_analysis.m
+++ /dev/null
@@ -1,84 +0,0 @@
-function oo_ = covariance_posterior_analysis(NumberOfSimulations,dname,fname,vartan,nvar,var1,var2,mh_conf_sig,oo_)
-
-% Copyright (C) 2008 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/>.
-
-    indx1 = check_name(vartan,var1);
-    if isempty(indx1)
-        disp(['posterior_analysis:: ' var1 ' is not a stationary endogenous variable!'])
-        return
-    end
-    if ~isempty(var2)
-        indx2 = check_name(vartan,var2);
-        if isempty(indx2)
-            disp(['posterior_analysis:: ' var2 ' is not a stationary endogenous variable!'])
-            return
-        end
-    else
-        indx2 = indx1;
-        var2 = var1;
-    end
-    if isfield(oo_,'PosteriorTheoreticalMoments')
-        if isfield(oo_.PosteriorTheoreticalMoments,'dsge')
-            if isfield(oo_.PosteriorTheoreticalMoments.dsge,'covariance')
-                if isfield(oo_.PosteriorTheoreticalMoments.dsge.covariance.mean,var1)
-                    eval(['s1 = oo_.PosteriorTheoreticalMoments.dsge.covariance.mean' '.' var1 ';'])  
-                    if isfield(s1,var2)
-                        % Nothing to do.
-                        return
-                    end
-                else
-                    if isfield(oo_.PosteriorTheoreticalMoments.dsge.covariance.mean,var2)
-                        eval(['s2 = oo_.PosteriorTheoreticalMoments.dsge.covariance.mean' '.' var2 ';'])
-                        if isfield(s1,var1)
-                            % Nothing to do (the covariance matrix is symmetric!).
-                            return
-                        end
-                    end
-                end
-            end
-        end
-    end
-    tmp = dir([ dname '/metropolis/'  fname '_Posterior2ndOrderMoments*.mat']);
-    NumberOfFiles = length(tmp);
-    i1 = 1; tmp = zeros(NumberOfSimulations,1);
-    for file = 1:NumberOfFiles
-        load([ dname '/metropolis/'  fname '_Posterior2ndOrderMoments' int2str(file) '.mat']);
-        i2 = i1 + rows(Covariance_matrix) - 1;
-        tmp(i1:i2) = Covariance_matrix(:,symmetric_matrix_index(indx1,indx2,nvar));
-        i1 = i2+1;
-    end
-    name = [var1 '.' var2];
-    if ~isconst(tmp)
-        [post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
-            posterior_moments(tmp,1,mh_conf_sig);
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.mean.' name ' = post_mean;']);
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.median.' name ' = post_median;']);
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.variance.' name ' = post_var;']);
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.hpdinf.' name ' = hpd_interval(1);']);
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.hpdsup.' name ' = hpd_interval(2);']);
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.deciles.' name ' = post_deciles;']);
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.density.' name ' = density;']);
-    else
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.mean.' name ' = NaN;']);
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.median.' name ' = NaN;']);
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.variance.' name ' = NaN;']);
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.hpdinf.' name ' = NaN;']);
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.hpdsup.' name ' = NaN;']);
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.deciles.' name ' = NaN;']);
-        eval(['oo_.PosteriorTheoreticalMoments.dsge.covariance.density.' name ' = NaN;']);
-    end
\ No newline at end of file
diff --git a/matlab/get_prior_info.m b/matlab/get_prior_info.m
index 2008cab03..070efd2c2 100644
--- a/matlab/get_prior_info.m
+++ b/matlab/get_prior_info.m
@@ -115,7 +115,7 @@ function get_prior_info(info)
         look_for_admissible_initial_condition = 1;
         scale = 1.0;
         iter  = 0;
-        while look_for_admissible_initial_condition
+        While look_for_admissible_initial_condition
             xinit = xparam1+scale*randn(size(xparam1));
             if all(xinit>bayestopt_.p3) && all(xinit<bayestopt_.p4)
                 look_for_admissible_initial_condition = 0;
@@ -151,7 +151,7 @@ function get_prior_info(info)
        end
     end
     
-    if info==3% Prior simulations (BK+moments).
+    if info==3% Prior simulations (BK + 2nd order moments).
        results = prior_sampler(1,M_,bayestopt_,options_,oo_);
        % Display prior mass info.
        disp(['Prior mass = ' num2str(results.prior.mass)])
@@ -188,17 +188,16 @@ function get_prior_info(info)
            load([ M_.dname '/prior/draws/prior_draws' int2str(f) '.mat']);
            number_of_simulations = length(pdraws);
            total_number_of_simulations = total_number_of_simulations + number_of_simulations;
-           covariance_cell = cell(number_of_simulations);
-           correlation_cell = cell(number_of_simulations);
-           decomposition_cell = cell(number_of_simulations);
+           covariance_cell = cell(number_of_simulations,1);
+           correlation_cell = cell(number_of_simulations,1);
+           decomposition_cell = cell(number_of_simulations,1);
            for s=1:number_of_simulations
-               dr = pdraws{s,2};
-               [gamma_y,ivar] = th_autocovariances(dr,ivar,M_,options_);
+               [gamma_y,ivar] = th_autocovariances(pdraws{s,2},ivar,M_,options_);
                covariance_cell(s) = {vech(gamma_y{1})};
-               tmp = zeros(ivar,options_.ar);
+               tmp = zeros(length(ivar),options_.ar);
                for i=1:length(ivar)
                    for lag=1:options_.ar
-                       tmp(i,lag) = gamma_y{lag+1}(i,i); 
+                       tmp(i,lag) = gamma_y{i,lag+1}; 
                    end
                end
                correlation_cell(s) = {tmp};
@@ -207,7 +206,21 @@ function get_prior_info(info)
            save([ PriorMomentsDirectoryName '/prior_moments_draws' int2str(f) '.mat' ],'covariance_cell','correlation_cell','decomposition_cell');
        end
        clear('covariance_cell','correlation_cell','decomposition_cell')
-    end
+       prior_moments_info = dir([ M_.dname '/prior/moments/prior_moments*.mat']);
+       number_of_prior_moments_files = length(prior_moments_info);
+       % Covariance analysis
+       disp(' ')
+       disp('-------------------------')
+       disp('Prior variance analysis')
+       disp('-------------------------')
+       disp(' ')
+       for i=1:length(ivar)
+           for file = 1:number_of_prior_moments_file
+               load()
+           end
+       end
+       
+    end 
     
 function format_string = build_format_string(bayestopt,i)
     format_string = ['%s & %s & %6.4f &'];
diff --git a/matlab/posterior_analysis.m b/matlab/posterior_analysis.m
index 2c6ff9d68..520262e71 100644
--- a/matlab/posterior_analysis.m
+++ b/matlab/posterior_analysis.m
@@ -54,7 +54,7 @@ function oo_ = job(type,SampleSize,arg1,arg2,arg3,options_,M_,oo_,nvar,vartan)
             [nvar,vartan,NumberOfFiles] = ...
                 dsge_simulated_theoretical_covariance(SampleSize,M_,options_,oo_,'posterior');
         end
-        oo_ = covariance_posterior_analysis(SampleSize,M_.dname,M_.fname,...
+        oo_ = covariance_mc_analysis(SampleSize,'posterior',M_.dname,M_.fname,...
                                             vartan,nvar,arg1,arg2,options_.mh_conf_sig,oo_);          
       case 'decomposition'
         if nargin==narg1
@@ -63,12 +63,12 @@ function oo_ = job(type,SampleSize,arg1,arg2,arg3,options_,M_,oo_,nvar,vartan)
         end
         oo_ = variance_decomposition_posterior_analysis(SampleSize,M_.dname,M_.fname,...
                                                         M_.exo_names,arg2,vartan,arg1,options_.mh_conf_sig,oo_);
-      case 'correlation'
+      case OB'correlation'
         if nargin==narg1
             [nvar,vartan,NumberOfFiles] = ...
                 dsge_simulated_theoretical_correlation(SampleSize,arg3,M_,options_,oo_,'posterior');
         end
-        oo_ = correlation_posterior_analysis(SampleSize,M_.dname,M_.fname,...
+        oo_ = correlation_mc_analysis(SampleSize,'posterior',M_.dname,M_.fname,...
                                              vartan,nvar,arg1,arg2,arg3,options_.mh_conf_sig,oo_,M_,options_);
       case 'conditional decomposition'
         if nargin==narg1
diff --git a/matlab/prior_sampler.m b/matlab/prior_sampler.m
index 4125da55e..3f8c98141 100644
--- a/matlab/prior_sampler.m
+++ b/matlab/prior_sampler.m
@@ -119,10 +119,7 @@ function results = prior_sampler(drsave,M_,bayestopt_,options_,oo_)
             count_unknown_problem = count_unknown_problem + 1 ;
         end
     end
-    
-    % Save last prior_draw*.mat file
-    % save([ PriorDirectoryName '/prior_draws' int2str(TableOfInformations(end,1)) '.mat' ],'pdraws');
-    
+  
     % Get informations about BK conditions and other things...
     results.bk.indeterminacy_share = count_bk_indeterminacy/loop_indx;
     results.bk.unstability_share = count_bk_unstability/loop_indx;