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Commit 91f3cc5c authored by MichelJuillard's avatar MichelJuillard
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adding new functions for penalty optimization

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function [fval,DLIK,Hess,exit_flag] = objective_function_penalty(x0,fcn,penalty,varargin)
[fval,DLIK,Hess,exit_flag,SteadyState,trend_coeff,info] = fcn(x0,varargin{:});
if info(1) ~= 0
fval = penalty + info(2);
end
end
function hessian_mat = penalty_hessian(func,x,penalty,gstep,varargin) % --*-- Unitary tests --*--
% Computes second order partial derivatives with penalty_objective_function
%
% INPUTS
% func [string] name of the function
% x [double] vector, the Hessian of "func" is evaluated at x.
% penalty [double] penalty base used if function fails
% gstep [double] scalar, size of epsilon.
% varargin [void] list of additional arguments for "func".
%
% OUTPUTS
% hessian_mat [double] Hessian matrix
%
% ALGORITHM
% Uses Abramowitz and Stegun (1965) formulas 25.3.23
% \[
% \frac{\partial^2 f_{0,0}}{\partial {x^2}} = \frac{1}{h^2}\left( f_{1,0} - 2f_{0,0} + f_{ - 1,0} \right)
% \]
% and 25.3.27 p. 884
%
% \[
% \frac{\partial ^2f_{0,0}}{\partial x\partial y} = \frac{-1}{2h^2}\left(f_{1,0} + f_{-1,0} + f_{0,1} + f_{0,-1} - 2f_{0,0} - f_{1,1} - f_{-1,-1} \right)
% \]
%
% SPECIAL REQUIREMENTS
% none
%
% Copyright (C) 2001-2014 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 <http://www.gnu.org/licenses/>.
if ~isa(func, 'function_handle')
func = str2func(func);
end
n=size(x,1);
h1=max(abs(x),sqrt(gstep(1))*ones(n,1))*eps^(1/6)*gstep(2);
h_1=h1;
xh1=x+h1;
h1=xh1-x;
xh1=x-h_1;
h_1=x-xh1;
xh1=x;
f0=penalty_objective_function(x,func,penalty,varargin{:});
f1=zeros(size(f0,1),n);
f_1=f1;
for i=1:n
%do step up
xh1(i)=x(i)+h1(i);
f1(:,i)=penalty_objective_function(xh1,func,penalty,varargin{:});
%do step up
xh1(i)=x(i)-h_1(i);
f_1(:,i)=penalty_objective_function(xh1,func,penalty,varargin{:});
xh1(i)=x(i);%reset parameter
end
xh_1=xh1;
hessian_mat = zeros(size(f0,1),n*n);
temp=f1+f_1-f0*ones(1,n); %term f_(1,0)+f_(-1,0)-f_(0,0) used later
for i=1:n
if i > 1 %fill symmetric part of Hessian based on previously computed results
k=[i:n:n*(i-1)];
hessian_mat(:,(i-1)*n+1:(i-1)*n+i-1)=hessian_mat(:,k);
end
hessian_mat(:,(i-1)*n+i)=(f1(:,i)+f_1(:,i)-2*f0)./(h1(i)*h_1(i)); %formula 25.3.23
for j=i+1:n
%step in up direction
xh1(i)=x(i)+h1(i);
xh1(j)=x(j)+h_1(j);
%step in down direction
xh_1(i)=x(i)-h1(i);
xh_1(j)=x(j)-h_1(j);
hessian_mat(:,(i-1)*n+j)=-(-penalty_objective_function(xh1,func,penalty,varargin{:})-penalty_objective_function(xh_1,func,penalty,varargin{:})+temp(:,i)+temp(:,j))./(2*h1(i)*h_1(j)); %formula 25.3.27
%reset grid points
xh1(i)=x(i);
xh1(j)=x(j);
xh_1(i)=x(i);
xh_1(j)=x(j);
end
end
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