68 lines
2.6 KiB
Matlab
68 lines
2.6 KiB
Matlab
function [ldens,parameters] = evaluate_prior(parameters,M_,estim_params_,oo_,options_,bayestopt_)
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% Evaluate the prior density at parameters.
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%
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% INPUTS
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% o parameters a string ('posterior mode','posterior mean','posterior median','prior mode','prior mean') or a vector of values for
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% the (estimated) parameters of the model.
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% o M_ [structure] Definition of the model
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% o oo_ [structure] Storage of results
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% o options_ [structure] Options
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% o bayestopt_ [structure] describing the priors
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% o estim_params_ [structure] characterizing parameters to be estimated
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%
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%
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% OUTPUTS
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% o ldens [double] value of the logged prior density.
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% o parameters [double] vector of values for the estimated parameters.
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%
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% SPECIAL REQUIREMENTS
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% None
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%
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% REMARKS
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% [1] This function cannot evaluate the prior density of a dsge-var model...
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% Copyright © 2009-2017 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 <https://www.gnu.org/licenses/>.
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if nargin==0
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parameters = 'posterior mode';
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end
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if ischar(parameters)
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switch parameters
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case 'posterior mode'
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parameters = get_posterior_parameters('mode',M_,estim_params_,oo_,options_);
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case 'posterior mean'
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parameters = get_posterior_parameters('mean',M_,estim_params_,oo_,options_);
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case 'posterior median'
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parameters = get_posterior_parameters('median',M_,estim_params_,oo_,options_);
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case 'prior mode'
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parameters = bayestopt_.p5(:);
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case 'prior mean'
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parameters = bayestopt_.p1;
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otherwise
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disp('eval_prior:: If the input argument is a string, then it has to be equal to:')
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disp(' ''posterior mode'', ')
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disp(' ''posterior mean'', ')
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disp(' ''posterior median'', ')
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disp(' ''prior mode'' or')
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disp(' ''prior mean''.')
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error
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end
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end
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ldens = priordens(parameters, bayestopt_.pshape, bayestopt_.p6, bayestopt_.p7, bayestopt_.p3, bayestopt_.p4); |