85 lines
2.5 KiB
Matlab
85 lines
2.5 KiB
Matlab
function xparam = get_posterior_parameters(type,M_,estim_params_,oo_,options_,field1)
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% function xparam = get_posterior_parameters(type,M_,estim_params_,oo_,options_,field1)
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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 M_: [structure] Dynare structure describing the model.
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% o estim_params_: [structure] Dynare structure describing the estimated parameters.
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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) 2006-2018 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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if nargin<6
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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 = M_.exo_names{k1};
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xparam(m) = oo_.([field1 type]).shocks_std.(name1);
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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 = M_.exo_names{k1};
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name2 = M_.exo_names{k2};
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xparam(m) = oo_.([field1 type]).shocks_corr.([name1 '_' name2]);
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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 = M_.param_names{estim_params_.param_vals(i,1)};
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xparam(m) = oo_.([field1 type]).parameters.(name1);
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m = m+1;
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end |