Account for PAC components in evaluate routine.

The print_expectations routine was previously only considering the
aggregate expectation (for the target). Now it updates the
database (dseries) with each component of the PAC model. The growth
neutrality correction is included in the aggregate expectation but not
in the expectations of the components.

matlab/print_expectations.m

@@ -217,7 +217,10 @@ end
 % Third print a routine for evaluating VAR_EXPECTATION/PAC_EXPECTATION term (returns a dseries object).
 %
 kind = [expectationmodelkind '_expectations'];
-mkdir(sprintf('+%s/+%s/+%s', M_.fname, kind, expectationmodelname));
+ndir = sprintf('+%s/+%s/+%s', M_.fname, kind, expectationmodelname);
+if ~exist(ndir, 'dir')
+    mkdir(sprintf('+%s/+%s/+%s', M_.fname, kind, expectationmodelname));
+end
 filename = sprintf('+%s/+%s/+%s/evaluate.m', M_.fname, kind, expectationmodelname);
 fid = fopen(filename, 'w');
 
@@ -237,6 +240,12 @@ fprintf(fid, 'ds = dseries();\n\n');
 
 id = 0;
 
+if isfield(expectationmodel, 'h_param_indices')
+    decompose = false;
+else
+    decompose = true;
+end
+
 clear('expression');
 
 % Get coefficient values in the target (if any)
@@ -266,12 +275,20 @@ if isequal(expectationmodelkind, 'pac') && isequal(expectationmodel.auxiliary_mo
     if isfield(expectationmodel, 'h_param_indices')
         constant = M_.params(expectationmodel.h_param_indices(id));
     else
+        if decompose
+            expressions = cell(length(expectationmodel.components), 1);
+            for j=1:length(expectationmodel.components)
+                expressions{j} = sprintf('%1.16f', M_.params(expectationmodel.components(j).h_param_indices(id)));
+            end
+        end
         constant = 0;
         for j=1:length(expectationmodel.components)
             constant = constant + targetcoefficients(j)*M_.params(expectationmodel.components(j).h_param_indices(id));
         end
     end
-    expression = sprintf('%1.16f', constant);
+    if isfield(expectationmodel, 'h_param_indices')
+        expression = sprintf('%1.16f', constant);
+    end
 end
 
 for i=1:maxlag
@@ -338,6 +355,16 @@ for i=1:maxlag
                 expression = sprintf('-%1.16f*%s', -parameter, variable);
             end
         end
+        if decompose
+            for k=1:length(expectationmodel.components)
+                parameter = M_.params(expectationmodel.components(k).h_param_indices(id));
+                if parameter>=0
+                    expressions{k} = sprintf('%s+%1.16f*%s', expressions{k}, parameter, variable);;
+                else
+                    expressions{k} = sprintf('%s-%1.16f*%s', expressions{k}, -parameter, variable);
+                end
+            end
+        end
     end
 end
 
@@ -382,7 +409,7 @@ if isequal(expectationmodelkind, 'pac') && growth_correction
     else
         first = true;
         for i=1:length(expectationmodel.components)
-            if ~isequal(expectationmodel.components(i).kind, 'll') && isfield(expectationmodel.components(i), 'growth_neutrality_param_index') && isfield(expectationmodel.components(i), 'growth_linear_comb') && ~isempty(expectationmodel.components(i).growth_linear_comb) 
+            if ~isequal(expectationmodel.components(i).kind, 'll') && isfield(expectationmodel.components(i), 'growth_neutrality_param_index') && isfield(expectationmodel.components(i), 'growth_linear_comb') && ~isempty(expectationmodel.components(i).growth_linear_comb)
                 pgrowth = targetcoefficients(i)*M_.params(expectationmodel.components(i).growth_neutrality_param_index);
                 for iter = 1:numel(expectationmodel.components(i).growth_linear_comb)
                     vgrowth='';
@@ -435,11 +462,16 @@ if isequal(expectationmodelkind, 'pac') && growth_correction
     expression = sprintf('%s+%s', expression, growthcorrection);
 end % growth_correction
 
-fprintf(fid, 'ds.%s = %s;', expectationmodelname, expression);
+fprintf(fid, 'ds.%s = %s;\n', expectationmodelname, expression);
+if exist('expressions', 'var')
+    for i=1:length(expressions)
+        fprintf(fid, 'ds.%s = %s;\n', M_.lhs{expectationmodel.components(i).aux_id}, expressions{i});
+    end
+end
 fclose(fid);
 
 fprintf('Expectation dseries expression is saved in %s.\n', filename);
 
 skipline();
 
-rehash
+rehash

matlab/write_expectations.m

@@ -220,7 +220,7 @@ for i=1:maxlag
 end
 
 if aggregate
-    growthneutralitycorrection = ''
+    growthneutralitycorrection = '';
 else
     growthneutralitycorrection = {};
 end
@@ -295,4 +295,4 @@ end
 
 if nargout==1 && ~isempty(growthneutralitycorrection)
     expression = sprintf('%s + %s', expression, growthneutralitycorrection);
-end
+end