89 lines
2.5 KiB
Matlab
89 lines
2.5 KiB
Matlab
function xparam = get_posterior_parameters(type)
|
|
|
|
% function xparam = get_posterior_parameters(type)
|
|
% Selects (estimated) parameters (posterior mode or posterior mean).
|
|
%
|
|
% INPUTS
|
|
% o type [char] = 'mode' or 'mean'.
|
|
%
|
|
% OUTPUTS
|
|
% o xparam vector of estimated parameters
|
|
%
|
|
% SPECIAL REQUIREMENTS
|
|
% None.
|
|
|
|
% Copyright (C) 2006-2009 Dynare Team
|
|
%
|
|
% This file is part of Dynare.
|
|
%
|
|
% Dynare is free software: you can redistribute it and/or modify
|
|
% it under the terms of the GNU General Public License as published by
|
|
% the Free Software Foundation, either version 3 of the License, or
|
|
% (at your option) any later version.
|
|
%
|
|
% Dynare is distributed in the hope that it will be useful,
|
|
% but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
|
% GNU General Public License for more details.
|
|
%
|
|
% 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_
|
|
|
|
nvx = estim_params_.nvx;
|
|
nvn = estim_params_.nvn;
|
|
ncx = estim_params_.ncx;
|
|
ncn = estim_params_.ncn;
|
|
np = estim_params_.np;
|
|
|
|
xparam = zeros(nvx+nvn+ncx+ncn+np,1);
|
|
|
|
m = 1;
|
|
for i=1:nvx
|
|
k1 = estim_params_.var_exo(i,1);
|
|
name1 = deblank(M_.exo_names(k1,:));
|
|
xparam(m) = eval(['oo_.posterior_' type '.shocks_std.' name1]);
|
|
M_.Sigma_e(k1,k1) = xparam(m)^2;
|
|
m = m+1;
|
|
end
|
|
|
|
for i=1:nvn
|
|
k1 = estim_params_.var_endo(i,1);
|
|
name1 = deblank(options_.varobs(k1,:));
|
|
xparam(m) = eval(['oo_.posterior_' type '.measurement_errors_std.' name1]);
|
|
m = m+1;
|
|
end
|
|
|
|
for i=1:ncx
|
|
k1 = estim_params_.corrx(i,1);
|
|
k2 = estim_params_.corrx(i,2);
|
|
name1 = deblank(M_.exo_names(k1,:));
|
|
name2 = deblank(M_.exo_names(k2,:));
|
|
xparam(m) = eval(['oo_.posterior_' type '.shocks_corr.' name1 '_' name2]);
|
|
M_.Sigma_e(k1,k2) = xparam(m);
|
|
M_.Sigma_e(k2,k1) = xparam(m);
|
|
m = m+1;
|
|
end
|
|
|
|
for i=1:ncn
|
|
k1 = estim_params_.corrn(i,1);
|
|
k2 = estim_params_.corrn(i,2);
|
|
name1 = deblank(options_.varobs(k1,:));
|
|
name2 = deblank(options_.varobs(k2,:));
|
|
xparam(m) = eval(['oo_.posterior_' type '.measurement_errors_corr.' name1 '_' name2]);
|
|
m = m+1;
|
|
end
|
|
|
|
FirstDeep = m;
|
|
|
|
for i=1:np
|
|
name1 = deblank(M_.param_names(estim_params_.param_vals(i,1),:));
|
|
xparam(m) = eval(['oo_.posterior_' 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 |