Fixed bug in the initialization of the metropolis when mode_compute=6 was previously used (so that we have an optimal mh scale factor)

and option load_mh_file is used. After the (stochastic) optimization, the optimal value of the scale parameter is saved in a mat file.

matlab/dynare_estimation_1.m

@@ -389,6 +389,12 @@ if options_.mode_compute == 0 && length(options_.mode_file) == 0 && options_.mh_
     return;
 end
 
+if options_.mode_compute>0 || options_.mode_compute==6
+    % Erase previously computed optimal mh scale parameter.
+    delete([M_.fname '_optimal_mh_scale_parameter.mat'])
+end
+
+
 %% Estimation of the posterior mode or likelihood mode
 if options_.mode_compute > 0 && ~options_.mh_posterior_mode_estimation
     if ~options_.dsge_var
@@ -550,6 +556,7 @@ if options_.mode_compute > 0 && ~options_.mh_posterior_mode_estimation
             end
             hh = inv(PostVar);
             save([M_.fname '_mode.mat'],'xparam1','hh');
+            save([M_.fname '_optimal_mh_scale_parameter.mat'],'Scale');
             bayestopt_.jscale = ones(length(xparam1),1)*Scale;%??!
         end    
       case 7

matlab/independent_metropolis_hastings.m

@@ -94,6 +94,9 @@ else
     if (options_.load_mh_file~=0)  & any(fline>1) ,
         NamFileInput(length(NamFileInput)+1,:)={[M_.dname '/metropolis/'],[ModelName '_mh' int2str(NewFile(1)) '_blck*.mat']};
     end
+    if exist([ModelName '_optimal_mh_scale_parameter.mat'])
+        NamFileInput(length(NamFileInput)+1,:)={'',[ModelName '_optimal_mh_scale_parameter.mat']};
+    end
     
     % from where to get back results
     %     NamFileOutput(1,:) = {[M_.dname,'/metropolis/'],'*.*'};

matlab/independent_metropolis_hastings_core.m

@@ -88,7 +88,16 @@ end
 %%%% NOW i run the (nblck-fblck+1) metropolis-hastings chains
 %%%%
 
-proposal_covariance = d * diag(bayestopt_.jscale);
+if any(isnan(bayestopt_.jscale))
+    if exist([ModelName '_optimal_mh_scale_parameter.mat'])% This file is created by mode_compute=6.
+        load([ModelName '_optimal_mh_scale_parameter'])
+        proposal_covariance = d*Scale;
+    else
+        error('mh:: Something is wrong. I can''t figure out the value of the scale parameter.')
+    end
+else
+    proposal_covariance = d*diag(bayestopt_.jscale);
+end
 
 jloop=0;
 

matlab/random_walk_metropolis_hastings.m

@@ -113,6 +113,9 @@ else
     if (options_.load_mh_file~=0)  & any(fline>1) ,
         NamFileInput(length(NamFileInput)+1,:)={[M_.dname '/metropolis/'],[ModelName '_mh' int2str(NewFile(1)) '_blck*.mat']};
     end
+    if exist([ModelName '_optimal_mh_scale_parameter.mat'])
+        NamFileInput(length(NamFileInput)+1,:)={'',[ModelName '_optimal_mh_scale_parameter.mat']};
+    end
     
     % from where to get back results
     %     NamFileOutput(1,:) = {[M_.dname,'/metropolis/'],'*.*'};

matlab/random_walk_metropolis_hastings_core.m

@@ -119,7 +119,18 @@ end
 %%%% NOW i run the (nblck-fblck+1) metropolis-hastings chains
 %%%%
 
-proposal_covariance = d*diag(bayestopt_.jscale);
+
+if any(isnan(bayestopt_.jscale))
+    if exist([ModelName '_optimal_mh_scale_parameter.mat'])% This file is created by mode_compute=6.
+        load([ModelName '_optimal_mh_scale_parameter'])
+        proposal_covariance = d*Scale;
+    else
+        error('mh:: Something is wrong. I can''t figure out the value of the scale parameter.')
+    end
+else
+    proposal_covariance = d*diag(bayestopt_.jscale);
+end
+
 
 jloop=0;