dynare/matlab/osr_obj.m

68 lines
2.5 KiB
Matlab

function [loss,info,exit_flag,vx,junk]=osr_obj(x,i_params,i_var,weights)
% objective function for optimal simple rules (OSR)
% INPUTS
% x vector values of the parameters
% over which to optimize
% i_params vector index of optimizing parameters in M_.params
% i_var vector variables indices
% weights vector weights in the OSRs
%
% OUTPUTS
% loss scalar loss function returned to solver
% info vector info vector returned by resol
% exit_flag scalar exit flag returned to solver
% vx vector variances of the endogenous variables
% junk empty dummy output for conformable
% header
%
% SPECIAL REQUIREMENTS
% none
% Copyright © 2005-2017 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 <https://www.gnu.org/licenses/>.
global M_ oo_ options_ optimal_Q_ it_
% global ys_ Sigma_e_ endo_nbr exo_nbr optimal_Q_ it_ ykmin_ options_
junk = [];
exit_flag = 1;
vx = [];
info=zeros(4,1);
loss=[];
% set parameters of the policiy rule
M_.params(i_params) = x;
% don't change below until the part where the loss function is computed
it_ = M_.maximum_lag+1;
[dr,info,M_,oo_] = resol(0,M_,options_,oo_);
if info(1)
if info(1) == 3 || info(1) == 4 || info(1) == 5 || info(1)==6 ||info(1) == 19 ||...
info(1) == 20 || info(1) == 21 || info(1) == 23 || info(1) == 26 || ...
info(1) == 81 || info(1) == 84 || info(1) == 85
loss = 1e8;
info(4)=info(2);
return
else
loss = 1e8;
info(4)=0.1;
return
end
end
vx = get_variance_of_endogenous_variables(dr,i_var);
loss = full(weights(:)'*vx(:));