Make field names consistent with different analysis steps and manual

still related to #316 (https://github.com/DynareTeam/dynare/pull/316)

matlab/conditional_variance_decomposition_mc_analysis.m

@@ -46,7 +46,7 @@ if isfield(oo_, [ TYPE 'TheoreticalMoments' ])
     if isfield(temporary_structure,'dsge')
         eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
         if isfield(temporary_structure,'ConditionalVarianceDecomposition')
-            eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.mean;'])
+            eval(['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...
@@ -85,11 +85,11 @@ for i=1:length(Steps)
     p_hpdsup(i) = hpd_interval(2);
     p_density(:,:,i) = pp_density;
 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.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;']);
 eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.density.' name ' = p_density;']);
\ No newline at end of file

matlab/correlation_mc_analysis.m

@@ -48,9 +48,9 @@ if isfield(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.correlation.mean;'])
+            eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.correlation.Mean;'])
             if isfield(temporary_structure,var1)
-                eval(['temporary_structure_1 = oo_.' TYPE 'TheoreticalMoments.dsge.correlation.mean.' var1 ';']) 
+                eval(['temporary_structure_1 = oo_.' TYPE 'TheoreticalMoments.dsge.correlation.Mean.' var1 ';']) 
                 if isfield(temporary_structure_1,var2)
                     eval(['temporary_structure_2 = temporary_structure_1.' var2 ';'])
                     l1 = length(temporary_structure_2);
@@ -98,11 +98,11 @@ if ~isconst(tmp)
         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_,'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
@@ -114,11 +114,11 @@ else
         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_,'Mean',nar,NaN);
+                oo_ = fill_output_structure(var1,var2,TYPE,oo_,'Median',nar,NaN);
+                oo_ = fill_output_structure(var1,var2,TYPE,oo_,'Nariance',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
@@ -128,11 +128,11 @@ 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 '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.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);']);
 eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.density.' name ' = cell(' int2str(nar) ',1);']);
 for i=1:nar
@@ -143,7 +143,7 @@ end
 function oo_ = fill_output_structure(var1,var2,type,oo_,moment,lag,result)
 name = [ var1 '.' var2 ];
 switch moment
-  case {'mean','median','variance','hpdinf','hpdsup'} 
+  case {'Mean','Median','Variance','HPDinf','HPDsup'} 
     eval(['oo_.' type  'TheoreticalMoments.dsge.correlation.' moment '.' name '(' int2str(lag) ',1) = result;']);
   case {'deciles','density'}
     eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.' moment '.' name '(' int2str(lag) ',1) = {result};']);

matlab/covariance_mc_analysis.m

@@ -48,16 +48,16 @@ if isfield(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;'])
+            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 ';'])
+                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 ';'])
+                    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
@@ -80,19 +80,19 @@ 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.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_.' 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.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;']);
     eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.density.' name ' = NaN;']);
 end
\ No newline at end of file

matlab/evaluate_smoother.m

@@ -131,7 +131,7 @@ clear('priordens')
 oo.Smoother.SteadyState = ys;
 oo.Smoother.TrendCoeffs = trend_coeff;
 if options_.filter_covariance
-    oo.Smoother.variance = P;
+    oo.Smoother.Variance = P;
 end
 i_endo = bayestopt_.smoother_saved_var_list;
 if options_.nk ~= 0

matlab/forcst_unc.m

@@ -146,7 +146,7 @@ dynare_graph_close;
 
 
 % saving results
-save_results(yf_mean,'oo_.forecast.mean.',var_list);
+save_results(yf_mean,'oo_.forecast.Mean.',var_list);
 save_results(yf1(:,:,k1(1)),'oo_.forecast.HPDinf.',var_list);
 save_results(yf1(:,:,k1(2)),'oo_.forecast.HPDsup.',var_list);
 save_results(yf2(:,:,k2(1)),'oo_.forecast.HPDTotalinf.',var_list);

matlab/imcforecast.m

@@ -203,7 +203,7 @@ forecasts.controled_variables = constrained_vars;
 forecasts.instruments = options_cond_fcst.controlled_varexo;
 
 for i = 1:EndoSize
-    eval(['forecasts.cond.mean.' deblank(M_.endo_names(oo_.dr.order_var(i),:)) ' = mFORCS1(i,:)'';']);
+    eval(['forecasts.cond.Mean.' deblank(M_.endo_names(oo_.dr.order_var(i),:)) ' = mFORCS1(i,:)'';']);
     tmp = sort(squeeze(FORCS1(i,:,:))');
     eval(['forecasts.cond.ci.' deblank(M_.endo_names(oo_.dr.order_var(i),:)) ...
           ' = [tmp(t1,:)'' ,tmp(t2,:)'' ]'';']);
@@ -227,7 +227,7 @@ end
 mFORCS2 = mean(FORCS2,3);
 
 for i = 1:EndoSize
-    eval(['forecasts.uncond.mean.' deblank(M_.endo_names(oo_.dr.order_var(i),:)) ' = mFORCS2(i,:)'';']);
+    eval(['forecasts.uncond.Mean.' deblank(M_.endo_names(oo_.dr.order_var(i),:)) ' = mFORCS2(i,:)'';']);
     tmp = sort(squeeze(FORCS2(i,:,:))');
     eval(['forecasts.uncond.ci.' deblank(M_.endo_names(oo_.dr.order_var(i),:)) ...
           ' = [tmp(t1,:)'' ,tmp(t2,:)'' ]'';']);

matlab/plot_icforecast.m

@@ -35,14 +35,14 @@ end
 load conditional_forecasts;
 
 if nargin==1 || isempty(periods) % Set default number of periods.
-    eval(['periods = length(forecasts.cond.mean.' Variables(1,:) ');']);
+    eval(['periods = length(forecasts.cond.Mean.' Variables(1,:) ');']);
 end
 
 for i=1:size(Variables,1)
     eval(['ci1 = forecasts.cond.ci.' Variables(i,:) ';'])
-    eval(['m1 = forecasts.cond.mean.' Variables(i,:) ';'])
+    eval(['m1 = forecasts.cond.Mean.' Variables(i,:) ';'])
     eval(['ci2 = forecasts.uncond.ci.' Variables(i,:) ';'])
-    eval(['m2 = forecasts.uncond.mean.' Variables(i,:) ';'])
+    eval(['m2 = forecasts.uncond.Mean.' Variables(i,:) ';'])
     build_figure(Variables(i,:),ci1(:,1:periods),ci2(:,1:periods),m1(1:periods),m2(1:periods),options_);
 end
 

matlab/variance_decomposition_mc_analysis.m

@@ -44,7 +44,7 @@ if isfield(oo_, [ TYPE 'TheoreticalMoments'])
     if isfield(temporary_structure,'dsge')
         eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
         if isfield(temporary_structure,'VarianceDecomposition')
-            eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.mean;'])
+            eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.Mean;'])
             if isfield(temporary_structure,name)
                 % Nothing to do.
                 return
@@ -82,10 +82,10 @@ else
     [p_mean, p_median, p_var, hpd_interval, p_deciles, density] = ...
         posterior_moments(tmp,1,mh_conf_sig);
 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.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;']);
 eval(['oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.density.' name ' = density;']);
\ No newline at end of file