diff --git a/matlab/GetOneDraw.m b/matlab/GetOneDraw.m
index f8e2a0d63b96c9264e2cd35e4a110d16fe409373..e4fba3a4319a51ccd4e30138add672563aa7ada9 100644
--- a/matlab/GetOneDraw.m
+++ b/matlab/GetOneDraw.m
@@ -1,10 +1,15 @@
-function [xparams, logpost] = GetOneDraw(type)
-% function [xparams, logpost] = GetOneDraw(type)
+function [xparams, logpost] = GetOneDraw(type,M_,estim_params_,oo_,options_,bayestopt_)
+% function [xparams, logpost] = GetOneDraw(type,M_,estim_params_,oo_,options_,bayestopt_)
% draws one parameter vector and its posterior from MCMC or the prior
%
% INPUTS
% type: [string] 'posterior': draw from MCMC draws
% 'prior': draw from prior
+% M_ [structure] Definition of the model
+% estim_params_ [structure] characterizing parameters to be estimated
+% oo_ [structure] Storage of results
+% options_ [structure] Options
+% bayestopt_ [structure] describing the priors
%
% OUTPUTS
% xparams: vector of estimated parameters (drawn from posterior or prior distribution)
@@ -36,6 +41,6 @@ switch type
case 'prior'
xparams = prior_draw();
if nargout>1
- logpost = evaluate_posterior_kernel(xparams');
+ logpost = evaluate_posterior_kernel(xparams',M_,estim_params_,oo_,options_,bayestopt_);
end
end
\ No newline at end of file
diff --git a/matlab/PosteriorIRF.m b/matlab/PosteriorIRF.m
index 157a5e3a13a22be663ff72f1db6d11716bf05562..12cc6c8d8beb213bc541d60d4a61a8c6105d8549 100644
--- a/matlab/PosteriorIRF.m
+++ b/matlab/PosteriorIRF.m
@@ -174,7 +174,7 @@ localVars.type=type;
if strcmpi(type,'posterior')
while b<B
b = b + 1;
- x(b,:) = GetOneDraw(type);
+ x(b,:) = GetOneDraw(type,M_,estim_params_,oo_,options_,bayestopt_);
end
end
diff --git a/matlab/PosteriorIRF_core1.m b/matlab/PosteriorIRF_core1.m
index 561104f673c8c0921c84f9c345d58a5183ac6093..2f5a931c4612407e4a27eaa64f59470be799a010 100644
--- a/matlab/PosteriorIRF_core1.m
+++ b/matlab/PosteriorIRF_core1.m
@@ -141,7 +141,7 @@ while fpar<B
irun = irun+1;
irun2 = irun2+1;
if strcmpi(type,'prior')
- deep = GetOneDraw(type);
+ deep = GetOneDraw(type,M_,estim_params_,oo_,options_,bayestopt_);
else
deep = x(fpar,:);
end
diff --git a/matlab/dynare_estimation_1.m b/matlab/dynare_estimation_1.m
index 3fe420a2bfc85aab6dde28eca940e8991c5fe9aa..1a674c32bfb3392e77c2a745b37126b9b03324a8 100644
--- a/matlab/dynare_estimation_1.m
+++ b/matlab/dynare_estimation_1.m
@@ -519,7 +519,7 @@ if (any(bayestopt_.pshape >0 ) && options_.mh_replic) || ...
end
prior_posterior_statistics('posterior',dataset_,dataset_info);
end
- xparam1 = get_posterior_parameters('mean');
+ xparam1 = get_posterior_parameters('mean',M_,estim_params_,oo_,options_);
M_ = set_all_parameters(xparam1,estim_params_,M_);
end
end
diff --git a/matlab/dynare_identification.m b/matlab/dynare_identification.m
index 7b5c1e5569e803ecd1d8a1f952620e8896452288..bc16725fa9411eb35244423c6c671e9a51f96939 100644
--- a/matlab/dynare_identification.m
+++ b/matlab/dynare_identification.m
@@ -271,15 +271,15 @@ if iload <=0
case 'posterior_mode'
parameters_TeX = 'Posterior mode';
disp('Testing posterior mode')
- params(1,:) = get_posterior_parameters('mode');
+ params(1,:) = get_posterior_parameters('mode',M_,estim_params_,oo_,options_);
case 'posterior_mean'
parameters_TeX = 'Posterior mean';
disp('Testing posterior mean')
- params(1,:) = get_posterior_parameters('mean');
+ params(1,:) = get_posterior_parameters('mean',M_,estim_params_,oo_,options_);
case 'posterior_median'
parameters_TeX = 'Posterior median';
disp('Testing posterior median')
- params(1,:) = get_posterior_parameters('median');
+ params(1,:) = get_posterior_parameters('median',M_,estim_params_,oo_,options_);
case 'prior_mode'
parameters_TeX = 'Prior mode';
disp('Testing prior mode')
diff --git a/matlab/evaluate_likelihood.m b/matlab/evaluate_likelihood.m
index a76534adff87bc0f301bbcbc6e218a024f175dcc..20da8eb4c6c196104cc02103a67c4f2d7413cb43 100644
--- a/matlab/evaluate_likelihood.m
+++ b/matlab/evaluate_likelihood.m
@@ -1,10 +1,14 @@
-function [llik,parameters] = evaluate_likelihood(parameters)
+function [llik,parameters] = evaluate_likelihood(parameters,M_,estim_params_,oo_,options_,bayestopt_)
% Evaluate the logged likelihood at parameters.
%
% INPUTS
% o parameters a string ('posterior mode','posterior mean','posterior median','prior mode','prior mean') or a vector of values for
% the (estimated) parameters of the model.
-%
+% o M_ [structure] Definition of the model
+% o estim_params_ [structure] characterizing parameters to be estimated
+% o oo_ [structure] Storage of results
+% o options_ [structure] Options
+% o bayestopt_ [structure] describing the priors
%
% OUTPUTS
% o ldens [double] value of the sample logged density at parameters.
@@ -35,8 +39,6 @@ function [llik,parameters] = evaluate_likelihood(parameters)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-global options_ M_ bayestopt_ oo_ estim_params_
-
persistent dataset dataset_info
if nargin==0
@@ -46,11 +48,11 @@ end
if ischar(parameters)
switch parameters
case 'posterior mode'
- parameters = get_posterior_parameters('mode');
+ parameters = get_posterior_parameters('mode',M_,estim_params_,oo_,options_);
case 'posterior mean'
- parameters = get_posterior_parameters('mean');
+ parameters = get_posterior_parameters('mean',M_,estim_params_,oo_,options_);
case 'posterior median'
- parameters = get_posterior_parameters('median');
+ parameters = get_posterior_parameters('median',M_,estim_params_,oo_,options_);
case 'prior mode'
parameters = bayestopt_.p5(:);
case 'prior mean'
@@ -72,5 +74,5 @@ end
options_=select_qz_criterium_value(options_);
llik = -dsge_likelihood(parameters,dataset,dataset_info,options_,M_,estim_params_,bayestopt_,prior_bounds(bayestopt_,options_.prior_trunc),oo_);
-ldens = evaluate_prior(parameters);
+ldens = evaluate_prior(parameters,M_,estim_params_,oo_,options_,bayestopt_);
llik = llik - ldens;
\ No newline at end of file
diff --git a/matlab/evaluate_posterior_kernel.m b/matlab/evaluate_posterior_kernel.m
index 997962127a7a672e38cc6e7529a4828c3d495c5d..c4132fb38f04dd4e9c3422e4ce056c7c22e1d8d7 100644
--- a/matlab/evaluate_posterior_kernel.m
+++ b/matlab/evaluate_posterior_kernel.m
@@ -1,10 +1,16 @@
-function lpkern = evaluate_posterior_kernel(parameters,llik)
-% Evaluate the prior density at parameters.
+function lpkern = evaluate_posterior_kernel(parameters,M_,estim_params_,oo_,options_,bayestopt_,llik)
+% Evaluate the evaluate_posterior_kernel at parameters.
%
% INPUTS
% o parameters a string ('posterior mode','posterior mean','posterior median','prior mode','prior mean') or a vector of values for
% the (estimated) parameters of the model.
-%
+% o M_ [structure] Definition of the model
+% o estim_params_ [structure] characterizing parameters to be estimated
+% o oo_ [structure] Storage of results
+% o options_ [structure] Options
+% o bayestopt_ [structure] describing the priors
+% o llik [double] value of the logged likelihood if it
+% should not be computed
%
% OUTPUTS
% o lpkern [double] value of the logged posterior kernel.
@@ -34,8 +40,8 @@ function lpkern = evaluate_posterior_kernel(parameters,llik)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-[ldens,parameters] = evaluate_prior(parameters);
-if nargin==1
- llik = evaluate_likelihood(parameters);
+[ldens,parameters] = evaluate_prior(parameters,M_,estim_params_,oo_,options_,bayestopt_);
+if nargin==6 %llik provided as an input
+ llik = evaluate_likelihood(parameters,M_,estim_params_,oo_,options_,bayestopt_);
end
lpkern = ldens+llik;
\ No newline at end of file
diff --git a/matlab/evaluate_prior.m b/matlab/evaluate_prior.m
index 01cede921ea4ccd78acd10cbf38e0d865f2f1ddc..e340667c3ecad7c19982ed348c158530b0d7e914 100644
--- a/matlab/evaluate_prior.m
+++ b/matlab/evaluate_prior.m
@@ -1,9 +1,14 @@
-function [ldens,parameters] = evaluate_prior(parameters)
+function [ldens,parameters] = evaluate_prior(parameters,M_,estim_params_,oo_,options_,bayestopt_)
% Evaluate the prior density at parameters.
%
% INPUTS
% o parameters a string ('posterior mode','posterior mean','posterior median','prior mode','prior mean') or a vector of values for
% the (estimated) parameters of the model.
+% o M_ [structure] Definition of the model
+% o oo_ [structure] Storage of results
+% o options_ [structure] Options
+% o bayestopt_ [structure] describing the priors
+% o estim_params_ [structure] characterizing parameters to be estimated
%
%
% OUTPUTS
@@ -33,8 +38,6 @@ function [ldens,parameters] = evaluate_prior(parameters)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-global bayestopt_
-
if nargin==0
parameters = 'posterior mode';
end
@@ -42,11 +45,11 @@ end
if ischar(parameters)
switch parameters
case 'posterior mode'
- parameters = get_posterior_parameters('mode');
+ parameters = get_posterior_parameters('mode',M_,estim_params_,oo_,options_);
case 'posterior mean'
- parameters = get_posterior_parameters('mean');
+ parameters = get_posterior_parameters('mean',M_,estim_params_,oo_,options_);
case 'posterior median'
- parameters = get_posterior_parameters('median');
+ parameters = get_posterior_parameters('median',M_,estim_params_,oo_,options_);
case 'prior mode'
parameters = bayestopt_.p5(:);
case 'prior mean'
diff --git a/matlab/evaluate_smoother.m b/matlab/evaluate_smoother.m
index 9ab94654b1f42e0d134fa8ce5193c56817624ed5..0c67142ddc9a0b48b14249a61a7c54d51eac55c3 100644
--- a/matlab/evaluate_smoother.m
+++ b/matlab/evaluate_smoother.m
@@ -73,13 +73,13 @@ end
if ischar(parameters)
switch parameters
case 'posterior_mode'
- parameters = get_posterior_parameters('mode');
+ parameters = get_posterior_parameters('mode',M_,estim_params_,oo_,options_);
case 'posterior_mean'
- parameters = get_posterior_parameters('mean');
+ parameters = get_posterior_parameters('mean',M_,estim_params_,oo_,options_);
case 'posterior_median'
- parameters = get_posterior_parameters('median');
+ parameters = get_posterior_parameters('median',M_,estim_params_,oo_,options_);
case 'mle_mode'
- parameters = get_posterior_parameters('mode','mle_');
+ parameters = get_posterior_parameters('mode',M_,estim_params_,oo_,options_,'mle_');
case 'prior_mode'
parameters = bayestopt_.p5(:);
case 'prior_mean'
diff --git a/matlab/execute_prior_posterior_function.m b/matlab/execute_prior_posterior_function.m
index 1370ab34ee4176a34a3cbd20aa38770675e1fdd5..cb7884e83916c945a4c19fb069f3f130204c5ec1 100644
--- a/matlab/execute_prior_posterior_function.m
+++ b/matlab/execute_prior_posterior_function.m
@@ -75,11 +75,11 @@ else
end
%get draws for later use
-first_draw=GetOneDraw(type);
+first_draw=GetOneDraw(type,M_,estim_params_,oo_,options_,bayestopt_);
parameter_mat=NaN(n_draws,length(first_draw));
parameter_mat(1,:)=first_draw;
for draw_iter=2:n_draws
- parameter_mat(draw_iter,:) = GetOneDraw(type);
+ parameter_mat(draw_iter,:) = GetOneDraw(type,M_,estim_params_,oo_,options_,bayestopt_);
end
% get output size
diff --git a/matlab/get_all_parameters.m b/matlab/get_all_parameters.m
index 289b6a67994a50007c44085e80e429787ccac3ac..d2aa30c61bc3500138f78928e328d65cfd5651a8 100644
--- a/matlab/get_all_parameters.m
+++ b/matlab/get_all_parameters.m
@@ -6,7 +6,7 @@ function xparam1=get_all_parameters(estim_params_,M_)
% parameter values
%
% INPUTS
-% estim_params_: Dynare structure describing the estimated parameters.
+% estim_params_: Dynare structure describing the estimated parameters.
% M_: Dynare structure describing the model.
%
% OUTPUTS
diff --git a/matlab/get_posterior_parameters.m b/matlab/get_posterior_parameters.m
index e10616d2078e964ff6f47aa16a5f0ccfb947f775..0417956ed232d1870a0d0befc71cfd17c4b2afa1 100644
--- a/matlab/get_posterior_parameters.m
+++ b/matlab/get_posterior_parameters.m
@@ -1,11 +1,13 @@
-function xparam = get_posterior_parameters(type,field1)
+function xparam = get_posterior_parameters(type,M_,estim_params_,oo_,options_,field1)
-% function xparam = get_posterior_parameters(type)
+% function xparam = get_posterior_parameters(type,M_,estim_params_,oo_,options_,field1)
% Selects (estimated) parameters (posterior mode or posterior mean).
%
% INPUTS
-% o type [char] = 'mode' or 'mean'.
-% o field_1 [char] optional field like 'mle_'.
+% o type [char] = 'mode' or 'mean'.
+% o M_: [structure] Dynare structure describing the model.
+% o estim_params_: [structure] Dynare structure describing the estimated parameters.
+% o field_1 [char] optional field like 'mle_'.
%
% OUTPUTS
% o xparam vector of estimated parameters
@@ -30,9 +32,7 @@ function xparam = get_posterior_parameters(type,field1)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-global estim_params_ oo_ options_ M_
-
-if nargin<2
+if nargin<6
field1='posterior_';
end
nvx = estim_params_.nvx;
@@ -48,7 +48,6 @@ for i=1:nvx
k1 = estim_params_.var_exo(i,1);
name1 = deblank(M_.exo_names(k1,:));
xparam(m) = oo_.([field1 type]).shocks_std.(name1);
- M_.Sigma_e(k1,k1) = xparam(m)^2;
m = m+1;
end
@@ -65,8 +64,6 @@ for i=1:ncx
name1 = deblank(M_.exo_names(k1,:));
name2 = deblank(M_.exo_names(k2,:));
xparam(m) = oo_.([field1 type]).shocks_corr.([name1 '_' name2]);
- M_.Sigma_e(k1,k2) = xparam(m);
- M_.Sigma_e(k2,k1) = xparam(m);
m = m+1;
end
@@ -84,10 +81,5 @@ FirstDeep = m;
for i=1:np
name1 = deblank(M_.param_names(estim_params_.param_vals(i,1),:));
xparam(m) = oo_.([field1 type]).parameters.(name1);
- %assignin('base',name1,xparam(m));% Useless with version 4 (except maybe for users)
m = m+1;
-end
-
-if np
- M_.params(estim_params_.param_vals(:,1)) = xparam(FirstDeep:end);
end
\ No newline at end of file
diff --git a/matlab/imcforecast.m b/matlab/imcforecast.m
index 66841319a847fd3bf43f1d5269cfc2ea6ab6a114..3f77a3f2fbe0523bd4d1f14e0103298c57204e1e 100644
--- a/matlab/imcforecast.m
+++ b/matlab/imcforecast.m
@@ -80,16 +80,16 @@ if estimated_model
if ischar(options_cond_fcst.parameter_set)
switch options_cond_fcst.parameter_set
case 'posterior_mode'
- xparam = get_posterior_parameters('mode');
+ xparam = get_posterior_parameters('mode',M_,estim_params_,oo_,options_);
graph_title='Posterior Mode';
case 'posterior_mean'
- xparam = get_posterior_parameters('mean');
+ xparam = get_posterior_parameters('mean',M_,estim_params_,oo_,options_);
graph_title='Posterior Mean';
case 'posterior_median'
- xparam = get_posterior_parameters('median');
+ xparam = get_posterior_parameters('median',M_,estim_params_,oo_,options_);
graph_title='Posterior Median';
case 'mle_mode'
- xparam = get_posterior_parameters('mode','mle_');
+ xparam = get_posterior_parameters('mode',M_,estim_params_,oo_,options_,'mle_');
graph_title='ML Mode';
case 'prior_mode'
xparam = bayestopt_.p5(:);
diff --git a/matlab/prior_posterior_statistics.m b/matlab/prior_posterior_statistics.m
index 064e7874ae0dac8c38be2bc7cb8b4a79c7c9d0ca..72aca1e7948e074bf5f49aa2730700f6f2f5644b 100644
--- a/matlab/prior_posterior_statistics.m
+++ b/matlab/prior_posterior_statistics.m
@@ -226,7 +226,7 @@ if strcmpi(type,'posterior')
else
logpost=NaN(B,1);
for b=1:B
- [x(b,:), logpost(b)] = GetOneDraw(type);
+ [x(b,:), logpost(b)] = GetOneDraw(type,M_,estim_params_,oo_,options_,bayestopt_);
end
end
localVars.logpost=logpost;
diff --git a/matlab/prior_posterior_statistics_core.m b/matlab/prior_posterior_statistics_core.m
index 8e39e5ae2c4b629515275f03e7c136fc5927e68c..7fa6832d2de4c6297bb876f91a107746ac6a08f2 100644
--- a/matlab/prior_posterior_statistics_core.m
+++ b/matlab/prior_posterior_statistics_core.m
@@ -190,14 +190,14 @@ end
for b=fpar:B
if strcmpi(type,'prior')
- [deep, logpo] = GetOneDraw(type);
+ [deep, logpo] = GetOneDraw(type,M_,estim_params_,oo_,options_,bayestopt_);
else
deep = x(b,:);
if strcmpi(type,'posterior')
logpo = logpost(b);
else
- logpo = evaluate_posterior_kernel(deep');
+ logpo = evaluate_posterior_kernel(deep',M_,estim_params_,oo_,options_,bayestopt_);
end
end
M_ = set_all_parameters(deep,estim_params_,M_);