# Copyright (C) 2003,2004, 2005 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/>. # GMM example file, shows initial consistent estimator, # estimation of efficient weight, and second round # efficient estimator n = 1000; k = 5; x = [ones(n,1) randn(n,k-1)]; w = [x, rand(n,1)]; theta_true = ones(k,1); lambda = exp(x*theta_true); y = poisson_rnd(lambda); [xs, scalecoef] = scale_data(x); # The arguments for gmm_estimate theta = zeros(k,1); data = [y xs w]; weight = eye(columns(w)); moments = "poisson_moments"; momentargs = {k}; # needed to know where x ends and w starts # additional args for gmm_results names = str2mat("theta1", "theta2", "theta3", "theta4", "theta5"); gmmtitle = "Poisson GMM trial"; control = {100,0,1,1}; # initial consistent estimate: only used to get efficient weight matrix, no screen output [theta, obj_value, convergence] = gmm_estimate(theta, data, weight, moments, momentargs, control); # efficient weight matrix # this method is valid when moments are not autocorrelated # the user is reponsible to properly estimate the efficient weight m = feval(moments, theta, data, momentargs); weight = inverse(cov(m)); # second round efficient estimator gmm_results(theta, data, weight, moments, momentargs, names, gmmtitle, scalecoef, control); printf("\nThe true parameter values used to generate the data:\n"); prettyprint(theta_true, names, "value"); # Example doing estimation in parallel on a cluster (requires MPITB) # uncomment the following if you have MPITB installed # nslaves = 1; # theta = zeros(k,1); # nslaves = 1; # title = "GMM estimation done in parallel"; # gmm_results(theta, data, weight, moments, momentargs, names, gmmtitle, scalecoef, control, nslaves);

Generated by Doxygen 1.6.0 Back to index