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1) fix of boxplots when two nparams =2; 

2) default useautocorr = 0;
3) new option prior_range;
4) normalized Jacobian for weak identification;
5) more complete options load_ident_files.
time-shift
Marco Ratto 2010-03-08 16:12:01 +01:00
parent 2166d36cc1
commit 52e9e9aef7
1 changed files with 67 additions and 10 deletions
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77
matlab/dynare_identification.m
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@ -28,9 +28,10 @@ else
end
options_ident = set_default_option(options_ident,'load_ident_files',0);
options_ident = set_default_option(options_ident,'useautocorr',1);
options_ident = set_default_option(options_ident,'useautocorr',0);
options_ident = set_default_option(options_ident,'ar',3);
options_ident = set_default_option(options_ident,'prior_mc',2000);
options_ident = set_default_option(options_ident,'prior_range',0);
if nargin==2,
options_ident.prior_mc=size(pdraws0,1);
end
@ -54,7 +55,13 @@ SampleSize = options_ident.prior_mc;
% results = prior_sampler(0,M_,bayestopt_,options_,oo_);
prior_draw(1,bayestopt_);
bbb=bayestopt_;
if options_ident.prior_range
bbb.pshape = ones(size(bbb.pshape))*5;
bbb.p3=bbb.lb;
bbb.p4=bbb.ub;
end
prior_draw(1,bbb);
if ~(exist('sylvester3mr','file')==2),
dynareroot = strrep(which('dynare'),'dynare.m','');
@ -193,13 +200,19 @@ if iload <=0,
derLREmean = (siLRE)./SampleSize+derLREmean;
end
pdraws(iteration,:) = params;
normH = max(abs(stoH(:,:,run_index))')';
normJ = max(abs(stoJJ(:,:,run_index))')';
normLRE = max(abs(stoLRE(:,:,run_index))')';
% normH = TAU(:,iteration);
% normJ = GAM(:,iteration);
% normLRE = LRE(:,iteration);
[idemodel.Mco(:,iteration), idemoments.Mco(:,iteration), idelre.Mco(:,iteration), ...
idemodel.Pco(:,:,iteration), idemoments.Pco(:,:,iteration), idelre.Pco(:,:,iteration), ...
idemodel.cond(iteration), idemoments.cond(iteration), idelre.cond(iteration), ...
idemodel.ee(:,:,iteration), idemoments.ee(:,:,iteration), idelre.ee(:,:,iteration), ...
idemodel.ind(:,iteration), idemoments.ind(:,iteration), ...
idemodel.indno{iteration}, idemoments.indno{iteration}] = ...
identification_checks(H(indH,:),JJ(indJJ,:), gp(indLRE,:), bayestopt_);
identification_checks(H(indH,:)./normH(:,ones(nparam,1)),JJ(indJJ,:)./normJ(:,ones(nparam,1)), gp(indLRE,:)./normLRE(:,ones(size(gp,2),1)), bayestopt_);
if run_index==MAX_tau | iteration==SampleSize,
file_index = file_index + 1;
if run_index<MAX_tau,
@ -212,7 +225,7 @@ if iload <=0,
end
waitbar(iteration/SampleSize,h,['MC Identification, iteration ',int2str(iteration),'/',int2str(SampleSize)])
waitbar(iteration/SampleSize,h,['MC Identification checks ',int2str(iteration),'/',int2str(SampleSize)])
end
end
end
@ -226,9 +239,41 @@ if iload <=0,
else
load([IdentifDirectoryName '/' M_.fname '_identif'], 'pdraws', 'idemodel', 'idemoments', 'idelre', 'indJJ', 'indH', 'indLRE', ...
'siHmean', 'siJmean', 'siLREmean', 'derHmean', 'derJmean', 'derLREmean', 'TAU', 'GAM', 'LRE')
options_ident.prior_mc=size(pdraws,1);
SampleSize = options_ident.prior_mc;
options_.options_ident = options_ident;
identFiles = dir([IdentifDirectoryName '/' M_.fname '_identif_*']);
options_ident.prior_mc=size(pdraws,1);
SampleSize = options_ident.prior_mc;
options_.options_ident = options_ident;
if iload>1,
idemodel0=idemodel;
idemoments0=idemoments;
idelre0 = idelre;
iteration = 0;
h = waitbar(0,'Monte Carlo identification checks ...');
for file_index=1:length(identFiles)
load([IdentifDirectoryName '/' M_.fname '_identif_' int2str(file_index)], 'stoH', 'stoJJ', 'stoLRE')
for index=1:size(stoH,3),
iteration = iteration+1;
normH = max(abs(stoH(:,:,index))')';
normJ = max(abs(stoJJ(:,:,index))')';
normLRE = max(abs(stoLRE(:,:,index))')';
% normH = TAU(:,iteration);
% normJ = GAM(:,iteration);
% normLRE = LRE(:,iteration);
[idemodel.Mco(:,iteration), idemoments.Mco(:,iteration), idelre.Mco(:,iteration), ...
idemodel.Pco(:,:,iteration), idemoments.Pco(:,:,iteration), idelre.Pco(:,:,iteration), ...
idemodel.cond(iteration), idemoments.cond(iteration), idelre.cond(iteration), ...
idemodel.ee(:,:,iteration), idemoments.ee(:,:,iteration), idelre.ee(:,:,iteration), ...
idemodel.ind(:,iteration), idemoments.ind(:,iteration), ...
idemodel.indno{iteration}, idemoments.indno{iteration}] = ...
identification_checks(stoH(:,:,index)./normH(:,ones(nparam,1)), ...
stoJJ(:,:,index)./normJ(:,ones(nparam,1)), ...
stoLRE(:,:,index)./normLRE(:,ones(size(stoLRE,2),1)), bayestopt_);
waitbar(iteration/SampleSize,h,['MC Identification checks ',int2str(iteration),'/',int2str(SampleSize)])
end
end
close(h);
save([IdentifDirectoryName '/' M_.fname '_identif'], 'idemodel', 'idemoments', 'idelre', '-append')
end
end
offset = estim_params_.nvx;
@ -494,7 +539,11 @@ for j=1:estim_params_.np,
mmm = mean(squeeze(idelre.Pco(:,j,:))');
[sss, immm] = sort(-mmm);
subplot(3,4,iplo),
myboxplot(squeeze(idelre.Pco(immm(2:nbox+1),j,:))'),
if nbox==1,
myboxplot(squeeze(idelre.Pco(immm(2:nbox+1),j,:))),
else
myboxplot(squeeze(idelre.Pco(immm(2:nbox+1),j,:))'),
end
set(gca,'ylim',[0 1])
set(gca,'xticklabel','')
for ip=1:nbox, %estim_params_.np,
@ -521,7 +570,11 @@ for j=1:nparam,
mmm = mean(squeeze(idemodel.Pco(:,j,:))');
[sss, immm] = sort(-mmm);
subplot(3,4,iplo),
myboxplot(squeeze(idemodel.Pco(immm(2:nbox+1),j,:))'),
if nbox==1,
myboxplot(squeeze(idemodel.Pco(immm(2:nbox+1),j,:))),
else
myboxplot(squeeze(idemodel.Pco(immm(2:nbox+1),j,:))'),
end
set(gca,'ylim',[0 1])
set(gca,'xticklabel','')
for ip=1:nbox, %estim_params_.np,
@ -548,7 +601,11 @@ for j=1:nparam,
mmm = mean(squeeze(idemoments.Pco(:,j,:))');
[sss, immm] = sort(-mmm);
subplot(3,4,iplo),
myboxplot(squeeze(idemoments.Pco(immm(2:nbox+1),j,:))'),
if nbox==1,
myboxplot(squeeze(idemoments.Pco(immm(2:nbox+1),j,:))),
else
myboxplot(squeeze(idemoments.Pco(immm(2:nbox+1),j,:))'),
end
set(gca,'ylim',[0 1])
set(gca,'xticklabel','')
for ip=1:nbox, %estim_params_.np,