Fixed bug related to the mh based approximation of the posterior covariance matrix (used

for the jumping distribution).

matlab/PlotPosteriorDistributions.m

@@ -88,7 +88,7 @@ for i=1:npar
         eval(['f1 = oo_.posterior_density.shocks_std.' name '(:,2);'])
         eval(['oo_.prior_density.shocks_std.' name '(:,1) = x2;'])
         eval(['oo_.prior_density.shocks_std.' name '(:,2) = f2;'])
-        if options_.posterior_mode_estimation
+        if ~options_.mh_posterior_mode_estimation
             eval(['pmod = oo_.posterior_mode.shocks_std.' name ';'])
         end
     elseif i <= nvx+nvn
@@ -97,7 +97,7 @@ for i=1:npar
         eval(['f1 = oo_.posterior_density.measurement_errors_std.' name '(:,2);'])    
         eval(['oo_.prior_density.mearsurement_errors_std.' name '(:,1) = x2;'])
         eval(['oo_.prior_density.measurement_errors_std.' name '(:,2) = f2;'])
-        if options_.posterior_mode_estimation
+        if ~options_.mh_posterior_mode_estimation
             eval(['pmod = oo_.posterior_mode.measurement_errors_std.' name ';'])
         end     
     elseif i <= nvx+nvn+ncx
@@ -109,7 +109,7 @@ for i=1:npar
         eval(['f1 = oo_.posterior_density.shocks_corr.' name '(:,2);'])    
         eval(['oo_.prior_density.shocks_corr.' name '(:,1) = x2;'])
         eval(['oo_.prior_density.shocks_corr.' name '(:,2) = f2;'])
-        if options_.posterior_mode_estimation
+        if ~options_.mh_posterior_mode_estimation
             eval(['pmod = oo_.posterior_mode.shocks_corr.' name ';'])  
         end
     elseif i <= nvx+nvn+ncx+ncn
@@ -121,7 +121,7 @@ for i=1:npar
         eval(['f1 = oo_.posterior_density.measurement_errors_corr.' name '(:,2);'])
         eval(['oo_.prior_density.mearsurement_errors_corr.' name '(:,1) = x2;'])
         eval(['oo_.prior_density.measurement_errors_corr.' name '(:,2) = f2;'])
-        if options_.posterior_mode_estimation
+        if ~options_.mh_posterior_mode_estimation
             eval(['pmod = oo_.posterior_mode.measurement_errors_corr.' name ';'])
         end
     else
@@ -131,7 +131,7 @@ for i=1:npar
         eval(['f1 = oo_.posterior_density.parameters.' name '(:,2);'])
         eval(['oo_.prior_density.parameters.' name '(:,1) = x2;'])
         eval(['oo_.prior_density.parameters.' name '(:,2) = f2;'])
-        if options_.posterior_mode_estimation
+        if ~options_.mh_posterior_mode_estimation
             eval(['pmod = oo_.posterior_mode.parameters.' name ';'])
         end
     end
@@ -146,7 +146,7 @@ for i=1:npar
     set(hh,'color',[0.7 0.7 0.7]);
     hold on;
     plot(x1,f1,'-k','linewidth',2);
-    if options_.posterior_mode_estimation
+    if ~options_.mh_posterior_mode_estimation
         plot( [pmod pmod], [0.0 1.1*top0], '--g', 'linewidth', 2);
     end
     box on;

matlab/compute_mh_covariance_matrix.m

 function [posterior_mean,posterior_covariance,posterior_mode,posterior_kernel_at_the_mode] = compute_mh_covariance_matrix()
-
-% function [m0,s0] = compute_mh_covariance_matrix()
-% Estimation of the posterior covariance matrix and expectation. 
+% Estimation of the posterior covariance matrix, posterior mean, posterior mode and evaluation of the posterior kernel at the
+% estimated mode, using the draws from a metropolis-hastings. The estimated posterior mode and covariance matrix are saved in
+% a file <M_.fname>_mh_mode.mat. 
 % 
 % INPUTS 
 %   None.
@@ -10,12 +10,12 @@ function [posterior_mean,posterior_covariance,posterior_mode,posterior_kernel_at
 %   o  posterior_mean                [double]  (n*1) vector, posterior expectation of the parameters.
 %   o  posterior_covariance          [double]  (n*n) matrix, posterior covariance of the parameters (computed from previous metropolis hastings).
 %   o  posterior_mode                [double]  (n*1) vector, posterior mode of the parameters. 
-%   o  posterior_kernel_at_the_mode  [double]  scalar. 
+%   o  posterior_kernel_at_the_mode  [double]  scalar.
 %
 % SPECIAL REQUIREMENTS
 %   None.
 
-% Copyright (C) 2006-2008 Dynare Team
+% Copyright (C) 2006-2008, 2010 Dynare Team
 %
 % This file is part of Dynare.
 %

matlab/global_initialization.m

@@ -176,7 +176,7 @@ options_.moments_varendo = 0;
 options_.nk = 1;
 options_.noconstant = 0;
 options_.nodiagnostic = 0;
-options_.posterior_mode_estimation = 1;
+options_.mh_posterior_mode_estimation = 0;
 options_.prefilter = 0;
 options_.presample = 0;
 options_.prior_trunc = 1e-10;