93 lines
2.6 KiB
Matlab
93 lines
2.6 KiB
Matlab
function xparam = get_posterior_parameters(type,field1)
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% function xparam = get_posterior_parameters(type)
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% Selects (estimated) parameters (posterior mode or posterior mean).
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%
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% INPUTS
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% o type [char] = 'mode' or 'mean'.
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% o field_1 [char] optional field like 'mle_'.
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%
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% OUTPUTS
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% o xparam vector of estimated parameters
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%
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% SPECIAL REQUIREMENTS
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% None.
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% Copyright (C) 2006-2016 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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global estim_params_ oo_ options_ M_
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if nargin<2
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field1='posterior_';
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end
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nvx = estim_params_.nvx;
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nvn = estim_params_.nvn;
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ncx = estim_params_.ncx;
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ncn = estim_params_.ncn;
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np = estim_params_.np;
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xparam = zeros(nvx+nvn+ncx+ncn+np,1);
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m = 1;
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for i=1:nvx
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k1 = estim_params_.var_exo(i,1);
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name1 = deblank(M_.exo_names(k1,:));
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xparam(m) = oo_.([field1 type]).shocks_std.(name1);
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M_.Sigma_e(k1,k1) = xparam(m)^2;
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m = m+1;
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end
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for i=1:nvn
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k1 = estim_params_.nvn_observable_correspondence(i,1);
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name1 = options_.varobs{k1};
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xparam(m) = oo_.([field1 type]).measurement_errors_std.(name1);
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m = m+1;
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end
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for i=1:ncx
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k1 = estim_params_.corrx(i,1);
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k2 = estim_params_.corrx(i,2);
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name1 = deblank(M_.exo_names(k1,:));
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name2 = deblank(M_.exo_names(k2,:));
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xparam(m) = oo_.([field1 type]).shocks_corr.([name1 '_' name2]);
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M_.Sigma_e(k1,k2) = xparam(m);
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M_.Sigma_e(k2,k1) = xparam(m);
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m = m+1;
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end
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for i=1:ncn
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k1 = estim_params_.corrn_observable_correspondence(i,1);
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k2 = estim_params_.corrn_observable_correspondence(i,2);
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name1 = options_.varobs{k1};
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name2 = options_.varobs{k2};
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xparam(m) = oo_.([field1 type]).measurement_errors_corr.([name1 '_' name2]);
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m = m+1;
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end
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FirstDeep = m;
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for i=1:np
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name1 = deblank(M_.param_names(estim_params_.param_vals(i,1),:));
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xparam(m) = oo_.([field1 type]).parameters.(name1);
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%assignin('base',name1,xparam(m));% Useless with version 4 (except maybe for users)
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m = m+1;
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end
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if np
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M_.params(estim_params_.param_vals(:,1)) = xparam(FirstDeep:end);
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end |