74 lines
2.8 KiB
Matlab
74 lines
2.8 KiB
Matlab
function optimize_prior(options_, M_, oo_, bayestopt_, estim_params_)
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% optimize_prior(options_, M_, oo_, bayestopt_, estim_params_)
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% This routine computes the mode of the prior density using an optimization algorithm.
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%
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% INPUTS
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% options_ [structure] describing the options
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% M_ [structure] describing the model
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% oo_ [structure] storing the results
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% bayestopt_ [structure] describing the priors
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% estim_params_ [structure] characterizing parameters to be estimated
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% Copyright © 2015-2023 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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% Initialize to the prior mean
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oo_.dr = set_state_space(oo_.dr,M_);
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xparam1 = bayestopt_.p1;
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% Pertubation of the initial condition.
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look_for_admissible_initial_condition = 1; scale = 1.0; iter = 0;
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while look_for_admissible_initial_condition
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xinit = xparam1+scale*randn(size(xparam1));
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if all(xinit(:)>bayestopt_.p3) && all(xinit(:)<bayestopt_.p4)
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M_ = set_all_parameters(xinit,estim_params_,M_);
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[oo_.dr,INFO,M_.params] = resol(0,M_,options_,oo_.dr,oo_.steady_state, oo_.exo_steady_state, oo_.exo_det_steady_state);
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if ~INFO(1)
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look_for_admissible_initial_condition = 0;
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end
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else
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if iter == 2000
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scale = scale/1.1;
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iter = 0;
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else
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iter = iter+1;
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end
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end
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end
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% Maximization of the prior density
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[xparams, lpd, hessian_mat] = ...
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maximize_prior_density(xinit, bayestopt_.pshape, ...
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bayestopt_.p6, ...
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bayestopt_.p7, ...
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bayestopt_.p3, ...
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bayestopt_.p4,options_,M_,bayestopt_,estim_params_,oo_);
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% Display the results.
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skipline(2)
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disp('------------------')
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disp('PRIOR OPTIMIZATION')
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disp('------------------')
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skipline()
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for i = 1:length(xparams)
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disp(['deep parameter ' int2str(i) ': ' get_the_name(i,0,M_,estim_params_,options_) '.'])
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disp([' Initial condition ....... ' num2str(xinit(i)) '.'])
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disp([' Prior mode .............. ' num2str(bayestopt_.p5(i)) '.'])
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disp([' Optimized prior mode .... ' num2str(xparams(i)) '.'])
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skipline()
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end
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skipline() |