# Copyright (C) 2004 Michael Creel <michael.creel@uab.es> # # This program 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 2 of the License, or # (at your option) any later version. # # This program 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 this program; If not, see <http://www.gnu.org/licenses/>. # (c) Michael Creel <michael.creel@uab.es> # battery.m: repeatedly call bfgs using a battery of # start values, to attempt to find global min # of a nonconvex function # INPUTS: # func: function to mimimize # args: args of function # minarg: argument to minimize w.r.t. (usually = 1) # startvals: kxp matrix of values to try for sure (don't include all zeros, that's automatic) # max iters per start value # number of additional random start values to try # OUTPUT: theta - the best value found - NOT iterated to convergence function theta = battery(func, args, minarg, startvals, maxiters) # setup [k,trials] = size(startvals); bestobj = inf; besttheta = zeros(k,1); bfgscontrol = {maxiters,0,0,1}; # now try the supplied start values, and optionally the random start values for i = 1:trials args{minarg} = startvals(:,i); [theta, obj_value, convergence] = bfgsmin (func, args, bfgscontrol); if obj_value < bestobj besttheta = theta; bestobj = obj_value; endif endfor theta = besttheta; endfunction

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