Commit 6a3e0da5 authored by Sébastien Villemot's avatar Sébastien Villemot
Browse files

Merge pull request #559 from rattoma/master

Irf restrictions and identification
parents f525de04 b3c4f942
......@@ -334,6 +334,8 @@ if iload <=0,
disp('----------- ')
skipline()
return
else
parameters = 'Random_prior_params';
end
else
idehess_point.params=params;
......@@ -344,6 +346,7 @@ if iload <=0,
% normJ = max(abs(siJ)')';
% normLRE = max(abs(siLRE)')';
save([IdentifDirectoryName '/' M_.fname '_identif.mat'], 'idehess_point', 'idemoments_point','idemodel_point', 'idelre_point','store_options_ident')
save([IdentifDirectoryName '/' M_.fname '_' parameters '_identif.mat'], 'idehess_point', 'idemoments_point','idemodel_point', 'idelre_point','store_options_ident')
disp_identification(params, idemodel_point, idemoments_point, name, advanced);
if ~options_.nograph,
plot_identification(params,idemoments_point,idehess_point,idemodel_point,idelre_point,advanced,parameters,name,IdentifDirectoryName);
......
......@@ -42,11 +42,11 @@ end
infos=[0 0];
varlist=Model.endo_names(DynareResults.dr.order_var,:);
varlist=varlist(DynareResults.dr.restrict_var_list,:);
T=1;
NT=1;
for j=1:size(endo_prior_restrictions.irf,1),
T=max(T,endo_prior_restrictions.irf{j,3});
NT=max(NT,endo_prior_restrictions.irf{j,3});
end
for t=1:T,
for t=1:NT,
RR = T^(t-1)*R;
for j=1:size(endo_prior_restrictions.irf,1),
if endo_prior_restrictions.irf{j,3}~=t,
......
......@@ -153,9 +153,9 @@ if SampleSize == 1,
dyn_saveas(hh,[ IdentifDirectoryName '/' M_.fname '_ident_collinearity_' tittxt1 '_' int2str(j) ],options_);
end
skipline()
[U,S,V]=svd(idehess.AHess,0);
S=diag(S);
if idehess.flag_score,
[U,S,V]=svd(idehess.AHess,0);
S=diag(S);
if nparam<5,
f1 = dyn_figure(options_,'Name',[tittxt,' - Identification patterns (Information matrix)']);
else
......@@ -163,13 +163,13 @@ if SampleSize == 1,
f2 = dyn_figure(options_,'Name',[tittxt,' - Identification patterns (Information matrix): HIGHEST SV']);
end
else
S = idemoments.S;
V = idemoments.V;
% S = idemoments.S;
% V = idemoments.V;
if nparam<5,
f1 = dyn_figure(options_,'Name',[tittxt,' - Identification patterns (moments)']);
f1 = dyn_figure(options_,'Name',[tittxt,' - Identification patterns (moments Information matrix)']);
else
f1 = dyn_figure(options_,'Name',[tittxt,' - Identification patterns (moments): SMALLEST SV']);
f2 = dyn_figure(options_,'Name',[tittxt,' - Identification patterns (moments): HIGHEST SV']);
f1 = dyn_figure(options_,'Name',[tittxt,' - Identification patterns (moments Information matrix): SMALLEST SV']);
f2 = dyn_figure(options_,'Name',[tittxt,' - Identification patterns (moments Information matrix): HIGHEST SV']);
end
end
for j=1:min(nparam,8),
......
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