From 7ebbc41d8af472342f813b9891c1a5c992e96c44 Mon Sep 17 00:00:00 2001
From: Johannes Pfeifer <jpfeifer@gmx.de>
Date: Mon, 12 Oct 2015 15:20:15 +0200
Subject: [PATCH] Get rid of eval statements by using indirect indexing of
 structures

---
 matlab/GetPosteriorParametersStatistics.m     |  2 +-
 matlab/PosteriorIRF.m                         | 24 ++++-----
 ...ional_variance_decomposition_mc_analysis.m | 22 ++++----
 matlab/correlation_mc_analysis.m              | 42 +++++++--------
 matlab/covariance_mc_analysis.m               | 54 +++++++++----------
 matlab/variance_decomposition_mc_analysis.m   | 20 +++----
 6 files changed, 81 insertions(+), 83 deletions(-)

diff --git a/matlab/GetPosteriorParametersStatistics.m b/matlab/GetPosteriorParametersStatistics.m
index f9bfedbd0..c51e0a2ba 100644
--- a/matlab/GetPosteriorParametersStatistics.m
+++ b/matlab/GetPosteriorParametersStatistics.m
@@ -389,6 +389,6 @@ oo.posterior_density.(type).(name) = density;
 function [post_mean,hpd_interval,post_var] = Extractoo(oo,name,type)
 hpd_interval = zeros(2,1);
 post_mean = oo.posterior_mean.(type).(name);
-hpd_interval(1) = oo.posterior_hpdinf.(type).(name); 
+hpd_interval(1) = oo.posterior_hpdinf.(type).(name);
 hpd_interval(2) = oo.posterior_hpdsup.(type).(name);
 post_var = oo.posterior_variance.(type).(name);
\ No newline at end of file
diff --git a/matlab/PosteriorIRF.m b/matlab/PosteriorIRF.m
index 8c094a24f..be4246100 100644
--- a/matlab/PosteriorIRF.m
+++ b/matlab/PosteriorIRF.m
@@ -304,12 +304,12 @@ clear STOCK_IRF_DSGE;
 for i = irf_shocks_indx
     for j = 1:nvar
         name = [deblank(M_.endo_names(IndxVariables(j),:)) '_' deblank(tit(i,:))];
-        eval(['oo_.PosteriorIRF.dsge.Mean.' name ' = MeanIRF(:,j,i);']);
-        eval(['oo_.PosteriorIRF.dsge.Median.' name ' = MedianIRF(:,j,i);']);
-        eval(['oo_.PosteriorIRF.dsge.Var.' name ' = VarIRF(:,j,i);']);
-        eval(['oo_.PosteriorIRF.dsge.deciles.' name ' = DistribIRF(:,:,j,i);']);
-        eval(['oo_.PosteriorIRF.dsge.HPDinf.' name ' = HPDIRF(:,1,j,i);']);
-        eval(['oo_.PosteriorIRF.dsge.HPDsup.' name ' = HPDIRF(:,2,j,i);']);
+        oo_.PosteriorIRF.dsge.Mean.(name) = MeanIRF(:,j,i);
+        oo_.PosteriorIRF.dsge.Median.(name) = MedianIRF(:,j,i);
+        oo_.PosteriorIRF.dsge.Var.(name) = VarIRF(:,j,i);
+        oo_.PosteriorIRF.dsge.deciles.(name) = DistribIRF(:,:,j,i);
+        oo_.PosteriorIRF.dsge.HPDinf.(name) = HPDIRF(:,1,j,i);
+        oo_.PosteriorIRF.dsge.HPDsup.(name) = HPDIRF(:,2,j,i);
     end
 end
 
@@ -341,12 +341,12 @@ if MAX_nirfs_dsgevar
     for i = irf_shocks_indx
         for j = 1:nvar
             name = [deblank(M_.endo_names(IndxVariables(j),:)) '_' deblank(tit(i,:))];
-            eval(['oo_.PosteriorIRF.bvardsge.Mean.' name ' = MeanIRFdsgevar(:,j,i);']);
-            eval(['oo_.PosteriorIRF.bvardsge.Median.' name ' = MedianIRFdsgevar(:,j,i);']);
-            eval(['oo_.PosteriorIRF.bvardsge.Var.' name ' = VarIRFdsgevar(:,j,i);']);
-            eval(['oo_.PosteriorIRF.bvardsge.deciles.' name ' = DistribIRFdsgevar(:,:,j,i);']);
-            eval(['oo_.PosteriorIRF.bvardsge.HPDinf.' name ' = HPDIRFdsgevar(:,1,j,i);']);
-            eval(['oo_.PosteriorIRF.bvardsge.HPDsup.' name ' = HPDIRFdsgevar(:,2,j,i);']);
+            oo_.PosteriorIRF.bvardsge.Mean.(name) = MeanIRFdsgevar(:,j,i);
+            oo_.PosteriorIRF.bvardsge.Median.(name) = MedianIRFdsgevar(:,j,i);
+            oo_.PosteriorIRF.bvardsge.Var.(name) = VarIRFdsgevar(:,j,i);
+            oo_.PosteriorIRF.bvardsge.deciles.(name) = DistribIRFdsgevar(:,:,j,i);
+            oo_.PosteriorIRF.bvardsge.HPDinf.(name) = HPDIRFdsgevar(:,1,j,i);
+            oo_.PosteriorIRF.bvardsge.HPDsup.(name) = HPDIRFdsgevar(:,2,j,i);
         end
     end
 end
diff --git a/matlab/conditional_variance_decomposition_mc_analysis.m b/matlab/conditional_variance_decomposition_mc_analysis.m
index 2c724083a..c165a62be 100644
--- a/matlab/conditional_variance_decomposition_mc_analysis.m
+++ b/matlab/conditional_variance_decomposition_mc_analysis.m
@@ -62,11 +62,11 @@ end
 
 name = [ var_list(endogenous_variable_index,:) '.' exo ];
 if isfield(oo_, [ TYPE 'TheoreticalMoments' ])
-    eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])
+    temporary_structure = oo_.([TYPE 'TheoreticalMoments']);
     if isfield(temporary_structure,'dsge')
-        eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
+        temporary_structure = oo_.([TYPE 'TheoreticalMoments']).dsge;
         if isfield(temporary_structure,'ConditionalVarianceDecomposition')
-            eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Mean;'])
+            temporary_structure = oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.Mean;
             if isfield(temporary_structure,name)
                 if sum(Steps-temporary_structure.(name)(1,:)) == 0
                     % Nothing (new) to do here...
@@ -112,13 +112,13 @@ for i=1:length(Steps)
     p_hpdinf(i) = hpd_interval(1);
     p_hpdsup(i) = hpd_interval(2);
 end
-eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Steps = Steps;']);
-eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Mean.' name ' = p_mean;']);
-eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Median.' name ' = p_median;']);
-eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Variance.' name ' = p_variance;']);
-eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.HPDinf.' name ' = p_hpdinf;']);
-eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.HPDsup.' name ' = p_hpdsup;']);
-eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.deciles.' name ' = p_deciles;']);
+oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.Steps = Steps;
+oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.Mean.(name) = p_mean;
+oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.Median.(name) = p_median;
+oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.Variance.(name) = p_variance;
+oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.HPDinf.(name) = p_hpdinf;
+oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.HPDsup.(name)  = p_hpdsup;
+oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.deciles.(name)  = p_deciles;
 if options_.estimation.moments_posterior_density.indicator
-    eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.density.' name ' = p_density;']);
+    oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.density.(name) = p_density;
 end
\ No newline at end of file
diff --git a/matlab/correlation_mc_analysis.m b/matlab/correlation_mc_analysis.m
index 28a5c1af7..def6c94a9 100644
--- a/matlab/correlation_mc_analysis.m
+++ b/matlab/correlation_mc_analysis.m
@@ -44,15 +44,15 @@ else
 end
 
 if isfield(oo_,[TYPE 'TheoreticalMoments'])
-    eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])
+    temporary_structure = oo_.([TYPE, 'TheoreticalMoments']);
     if isfield(temporary_structure,'dsge')
-        eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
+        temporary_structure = oo_.([TYPE, 'TheoreticalMoments']).dsge;
         if isfield(temporary_structure,'correlation')
-            eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.correlation.Mean;'])
+            temporary_structure = oo_.([TYPE, 'TheoreticalMoments']).dsge.correlation.Mean;
             if isfield(temporary_structure,deblank(var1))
-                eval(['temporary_structure_1 = oo_.' TYPE 'TheoreticalMoments.dsge.correlation.Mean.' var1 ';']) 
+                temporary_structure_1 = oo_.([TYPE, 'TheoreticalMoments']).dsge.correlation.Mean.(var1);
                 if isfield(temporary_structure_1,deblank(var2))
-                    eval(['temporary_structure_2 = temporary_structure_1.' var2 ';'])
+                    temporary_structure_2 = temporary_structure_1.(var2);
                     l1 = length(temporary_structure_2);
                     if l1<nar
                         % INITIALIZATION:
@@ -99,9 +99,9 @@ if ~isconst(tmp)
             posterior_moments(tmp,0,mh_conf_sig);
     end
     if isfield(oo_,[ TYPE 'TheoreticalMoments'])
-        eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])
+        temporary_structure = oo_.([TYPE, 'TheoreticalMoments']);
         if isfield(temporary_structure,'dsge')
-            eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
+            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);
@@ -117,9 +117,9 @@ if ~isconst(tmp)
     end
 else
     if isfield(oo_,'PosteriorTheoreticalMoments')
-        eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])
+        temporary_structure = oo_.([TYPE, 'TheoreticalMoments']);
         if isfield(temporary_structure,'dsge')
-            eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
+            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);
@@ -136,30 +136,28 @@ else
 end
 
 function oo_ = initialize_output_structure(var1,var2,nar,type,oo_,options_)
-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 'TheoreticalMoments.dsge.correlation.Variance.' name ' = NaN(' int2str(nar) ',1);']);
-eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.HPDinf.' name ' = NaN(' int2str(nar) ',1);']);
-eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.HPDsup.' name ' = NaN(' int2str(nar) ',1);']);
-eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.deciles.' name ' = cell(' int2str(nar) ',1);']);
+oo_.([type, 'TheoreticalMoments']).dsge.correlation.Mean.(var1).(var2) = NaN(nar,1);
+oo_.([type, 'TheoreticalMoments']).dsge.correlation.Median.(var1).(var2) = NaN(nar,1);
+oo_.([type, 'TheoreticalMoments']).dsge.correlation.Variance.(var1).(var2) = NaN(nar,1);
+oo_.([type, 'TheoreticalMoments']).dsge.correlation.HPDinf.(var1).(var2) = NaN(nar,1);
+oo_.([type, 'TheoreticalMoments']).dsge.correlation.HPDsup.(var1).(var2) = NaN(nar,1);
+oo_.([type, 'TheoreticalMoments']).dsge.correlation.deciles.(var1).(var2) = cell(nar,1);
 if options_.estimation.moments_posterior_density.indicator
-    eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.density.' name ' = cell(' int2str(nar) ',1);']);
+    oo_.([type, 'TheoreticalMoments']).dsge.correlation.density.(var1).(var2) = cell(nar,1);
 end
 for i=1:nar
     if options_.estimation.moments_posterior_density.indicator
-        eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.density.' name '(' int2str(i) ',1) = {NaN};']);
+        oo_.([type, 'TheoreticalMoments']).dsge.correlation.density.(var1).(var2)(i,1) = {NaN};
     end
-    eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.deciles.' name '(' int2str(i) ',1) = {NaN};']);
+    oo_.([type, 'TheoreticalMoments']).dsge.correlation.deciles.(var1).(var2)(i,1) = {NaN};
 end
 
 function oo_ = fill_output_structure(var1,var2,type,oo_,moment,lag,result)
-name = [ var1 '.' var2 ];
 switch moment
   case {'Mean','Median','Variance','HPDinf','HPDsup'} 
-    eval(['oo_.' type  'TheoreticalMoments.dsge.correlation.' moment '.' name '(' int2str(lag) ',1) = result;']);
+    oo_.([type,  'TheoreticalMoments']).dsge.correlation.(moment).(var1).(var2)(lag,1) = result;
   case {'deciles','density'}
-    eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.' moment '.' name '(' int2str(lag) ',1) = {result};']);
+    oo_.([type, 'TheoreticalMoments']).dsge.correlation.(moment).(var1).(var2)(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
index 991c9f1ac..a5bda07ba 100644
--- a/matlab/covariance_mc_analysis.m
+++ b/matlab/covariance_mc_analysis.m
@@ -61,20 +61,20 @@ else
 end
 
 if isfield(oo_,[ TYPE 'TheoreticalMoments'])
-    eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])   
+    temporary_structure = oo_.([TYPE, 'TheoreticalMoments']); 
     if isfield(temporary_structure,'dsge')
-        eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
+        temporary_structure = oo_.([TYPE, 'TheoreticalMoments']).dsge;
         if isfield(temporary_structure,'covariance')
-            eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.covariance.Mean;'])
+            temporary_structure = oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Mean;
             if isfield(temporary_structure,var1)
-                eval(['temporary_structure_1 = oo_.' TYPE 'TheoreticalMoments.dsge.covariance.Mean.' var1 ';'])
+                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 ';'])
+                    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
@@ -104,31 +104,31 @@ for file = 1:length(ListOfFiles)
     end    
     i1 = i2+1;
 end
-name = [var1 '.' var2];
+
 if ~isconst(tmp)
     if options_.estimation.moments_posterior_density.indicator
         [p_mean, p_median, p_var, hpd_interval, p_deciles, density] = ...
                 posterior_moments(tmp,1,mh_conf_sig);
-        eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.density.' name ' = density;']);
+        oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.density.(var1).(var2) = density;
     else
         [p_mean, p_median, p_var, hpd_interval, p_deciles] = ...
                         posterior_moments(tmp,0,mh_conf_sig);
     end
-    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;']);
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Mean.(var1).(var2) = p_mean;
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Median.(var1).(var2) = p_median;
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Variance.(var1).(var2) = p_var;
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.HPDinf.(var1).(var2) = hpd_interval(1);
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.HPDsup.(var1).(var2) = hpd_interval(2);
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.deciles.(var1).(var2) = p_deciles;
 else
-    eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.Mean.' name ' = NaN;']);
-    eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.Median.' name ' = NaN;']);
-    eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.Variance.' name ' = NaN;']);
-    eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.HPDinf.' name ' = NaN;']);
-    eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.HPDsup.' name ' = NaN;']);
-    eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.deciles.' name ' = NaN;']);
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Mean.(var1).(var2) = NaN;
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Median.(var1).(var2) = NaN;
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Variance.(var1).(var2) = NaN;
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.HPDinf.(var1).(var2) = NaN;
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.HPDsup.(var1).(var2) = NaN;
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.deciles.(var1).(var2) = NaN;
     if options_.estimation.moments_posterior_density.indicator
-        eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.density.' name ' = NaN;']);
+        oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.density.(var1).(var2) = NaN;
     end
 end
 
@@ -136,15 +136,15 @@ if options_.contemporaneous_correlation
     if options_.estimation.moments_posterior_density.indicator
         [p_mean, p_median, p_var, hpd_interval, p_deciles, density] = ...
             posterior_moments(tmp_corr_mat,1,mh_conf_sig);
-        eval(['oo_.' TYPE 'TheoreticalMoments.dsge.contemporeaneous_correlation.density.' name ' = density;']);
+        oo_.([TYPE, 'TheoreticalMoments']).dsge.contemporeaneous_correlation.density.(var1).(var2) = density;
     else
         [p_mean, p_median, p_var, hpd_interval, p_deciles] = ...
             posterior_moments(tmp_corr_mat,0,mh_conf_sig);
     end
-    eval(['oo_.' TYPE 'TheoreticalMoments.dsge.contemporeaneous_correlation.Mean.' name ' = p_mean;']);
-    eval(['oo_.' TYPE 'TheoreticalMoments.dsge.contemporeaneous_correlation.Median.' name ' = p_median;']);
-    eval(['oo_.' TYPE 'TheoreticalMoments.dsge.contemporeaneous_correlation.Variance.' name ' = p_var;']);
-    eval(['oo_.' TYPE 'TheoreticalMoments.dsge.contemporeaneous_correlation.HPDinf.' name ' = hpd_interval(1);']);
-    eval(['oo_.' TYPE 'TheoreticalMoments.dsge.contemporeaneous_correlation.HPDsup.' name ' = hpd_interval(2);']);
-    eval(['oo_.' TYPE 'TheoreticalMoments.dsge.contemporeaneous_correlation.deciles.' name ' = p_deciles;']);
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.contemporeaneous_correlation.Mean.(var1).(var2) = p_mean;
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.contemporeaneous_correlation.Median.(var1).(var2) = p_median;
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.contemporeaneous_correlation.Variance.(var1).(var2) = p_var;
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.contemporeaneous_correlation.HPDinf.(var1).(var2) = hpd_interval(1);
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.contemporeaneous_correlation.HPDsup.(var1).(var2) = hpd_interval(2);
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.contemporeaneous_correlation.deciles.(var1).(var2) = p_deciles;
 end
diff --git a/matlab/variance_decomposition_mc_analysis.m b/matlab/variance_decomposition_mc_analysis.m
index 7d426bd40..b9e2a114b 100644
--- a/matlab/variance_decomposition_mc_analysis.m
+++ b/matlab/variance_decomposition_mc_analysis.m
@@ -63,11 +63,11 @@ end
 
 name = [ var '.' exo ];
 if isfield(oo_, [ TYPE 'TheoreticalMoments'])
-    eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])
+    temporary_structure = oo_.([TYPE, 'TheoreticalMoments']);
     if isfield(temporary_structure,'dsge')
-        eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
+        temporary_structure = oo_.([TYPE, 'TheoreticalMoments']).dsge;
         if isfield(temporary_structure,'VarianceDecomposition')
-            eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.Mean;'])
+            temporary_structure = oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.Mean;
             if isfield(temporary_structure,name)
                 % Nothing to do.
                 return
@@ -110,12 +110,12 @@ else
             posterior_moments(tmp,0,mh_conf_sig);        
     end
 end
-eval(['oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.Mean.' name ' = p_mean;']);
-eval(['oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.Median.' name ' = p_median;']);
-eval(['oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.Variance.' name ' = p_var;']);
-eval(['oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.HPDinf.' name ' = hpd_interval(1);']);
-eval(['oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.HPDsup.' name ' = hpd_interval(2);']);
-eval(['oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.deciles.' name ' = p_deciles;']);
+oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.Mean.(var).(exo) = p_mean;
+oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.Median.(var).(exo) = p_median;
+oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.Variance.(var).(exo) = p_var;
+oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.HPDinf.(var).(exo) = hpd_interval(1);
+oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.HPDsup.(var).(exo) = hpd_interval(2);
+oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.deciles.(var).(exo) = p_deciles;
 if options_.estimation.moments_posterior_density.indicator
-    eval(['oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.density.' name ' = density;']);
+    oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.density.(var).(exo) = density;
 end
\ No newline at end of file