47 lines
2.1 KiB
Matlab
47 lines
2.1 KiB
Matlab
function lpkern = evaluate_posterior_kernel(parameters,M_,estim_params_,oo_,options_,bayestopt_,llik)
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% Evaluate the evaluate_posterior_kernel 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 estim_params_ [structure] characterizing parameters to be estimated
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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 llik [double] value of the logged likelihood if it
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% should not be computed
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%
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% OUTPUTS
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% o lpkern [double] value of the logged posterior kernel.
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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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% [2] This function use persistent variables for the dataset and the description of the missing observations. Consequently, if this function
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% is called more than once (by changing the value of parameters) the sample *must not* change.
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% Copyright (C) 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 <http://www.gnu.org/licenses/>.
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[ldens,parameters] = evaluate_prior(parameters,M_,estim_params_,oo_,options_,bayestopt_);
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if nargin==6 %llik provided as an input
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llik = evaluate_likelihood(parameters,M_,estim_params_,oo_,options_,bayestopt_);
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end
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lpkern = ldens+llik; |