108 lines
4.2 KiB
Matlab
108 lines
4.2 KiB
Matlab
function [fval,info,exit_flag,Q,H]=check_bounds_and_definiteness_estimation(xparam1, M_, estim_params_, bounds)
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% [fval,info,exit_flag,Q,H]=check_bounds_and_definiteness_estimation(xparam1, M_, estim_params_, bounds)
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% Checks whether parameter vector satisfies bounds and the positive
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% definiteness of covariance matrices
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%
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% INPUTS
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% - xparam1 [double] n by 1 vector, estimated parameters.
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% - M_ [struct] Matlab's structure describing the Model.
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% - estim_params_ [struct] Matlab's structure describing the estimated_parameters.
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% - bounds [struct] Matlab's structure specifying the bounds on the paramater values (initialized by dynare_estimation_init).
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%
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% OUTPUTS
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% - fval [double] scalar, value of the likelihood or posterior kernel.
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% - info [integer] 4 by 1 vector, informations resolution of the model and evaluation of the likelihood.
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% - exit_flag [integer] scalar, equal to 1 (no issues when evaluating the likelihood) or 0 (not able to evaluate the likelihood).
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% - Q [matrix] Covariance matrix of structural shocks
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% - H [matrix] Covariance matrix of measurement errors
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% Copyright © 2020-2023 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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fval = [];
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exit_flag = 1;
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info = zeros(4,1);
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Q=[];
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H=[];
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% Return, with endogenous penalty, if some parameters are smaller than the lower bound of the prior domain.
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if any(xparam1<bounds.lb)
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k = find(xparam1(:) < bounds.lb);
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fval = Inf;
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exit_flag = 0;
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info(1) = 41;
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info(4) = sum((bounds.lb(k)-xparam1(k)).^2);
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return
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end
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% Return, with endogenous penalty, if some parameters are greater than the upper bound of the prior domain.
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if any(xparam1>bounds.ub)
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k = find(xparam1(:)>bounds.ub);
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fval = Inf;
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exit_flag = 0;
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info(1) = 42;
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info(4) = sum((xparam1(k)-bounds.ub(k)).^2);
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return
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end
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Q = M_.Sigma_e;
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H = M_.H;
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if ~issquare(Q) || estim_params_.ncx || isfield(estim_params_,'calibrated_covariances')
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[Q_is_positive_definite, penalty] = ispd(Q(estim_params_.Sigma_e_entries_to_check_for_positive_definiteness,estim_params_.Sigma_e_entries_to_check_for_positive_definiteness));
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if ~Q_is_positive_definite
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fval = Inf;
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exit_flag = 0;
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info(1) = 43;
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info(4) = penalty;
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return
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end
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if isfield(estim_params_,'calibrated_covariances')
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correct_flag=check_consistency_covariances(Q);
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if ~correct_flag
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penalty = sum(Q(estim_params_.calibrated_covariances.position).^2);
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fval = Inf;
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exit_flag = 0;
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info(1) = 71;
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info(4) = penalty;
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return
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end
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end
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end
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if ~issquare(H) || estim_params_.ncn || isfield(estim_params_,'calibrated_covariances_ME')
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[H_is_positive_definite, penalty] = ispd(H(estim_params_.H_entries_to_check_for_positive_definiteness,estim_params_.H_entries_to_check_for_positive_definiteness));
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if ~H_is_positive_definite
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fval = Inf;
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exit_flag = 0;
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info(1) = 44;
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info(4) = penalty;
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return
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end
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if isfield(estim_params_,'calibrated_covariances_ME')
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correct_flag=check_consistency_covariances(H);
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if ~correct_flag
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penalty = sum(H(estim_params_.calibrated_covariances_ME.position).^2);
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fval = Inf;
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exit_flag = 0;
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info(1) = 72;
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info(4) = penalty;
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return
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end
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end
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end
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