function [xparams,lpd,hessian] = ... maximize_prior_density(iparams, prior_shape, prior_hyperparameter_1, prior_hyperparameter_2, prior_inf_bound, prior_sup_bound) % Maximizes the logged prior density using Chris Sims' optimization routine. % % INPUTS % iparams [double] vector of initial parameters. % prior_shape [integer] vector specifying prior densities shapes. % prior_hyperparameter_1 [double] vector, first hyperparameter. % prior_hyperparameter_2 [double] vector, second hyperparameter. % prior_inf_bound [double] vector, prior's lower bound. % prior_sup_bound [double] vector, prior's upper bound. % % OUTPUTS % xparams [double] vector, prior mode. % lpd [double] scalar, value of the logged prior density at the mode. % hessian [double] matrix, Hessian matrix at the prior mode. % Copyright (C) 2009 Dynare Team % % This file is part of Dynare. % % Dynare is free software: you can redistribute it and/or modify % it under the terms of the GNU General Public License as published by % the Free Software Foundation, either version 3 of the License, or % (at your option) any later version. % % Dynare is distributed in the hope that it will be useful, % but WITHOUT ANY WARRANTY; without even the implied warranty of % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. % % You should have received a copy of the GNU General Public License % along with Dynare. If not, see . number_of_estimated_parameters = length(iparams); H0 = 1e-4*eye(number_of_estimated_parameters); crit = 1e-7; nit = 1000; verbose = 2; gradient_method = 2; [lpd,xparams,grad,hessian,itct,fcount,retcodehat] = ... csminwel('minus_logged_prior_density',iparams,H0,[],crit,nit,gradient_method, ... prior_shape, prior_hyperparameter_1, prior_hyperparameter_2, prior_inf_bound, prior_sup_bound); lpd = -lpd;