changeset 2324:b94cc195d5b6 octave-forge

Example for nonlinear least squares estimation
author mcreel
date Tue, 13 Jun 2006 13:25:13 +0000
parents 3a720be3b267
children 61855097ec0c
files main/econometrics/nls_example.m
diffstat 1 files changed, 60 insertions(+), 0 deletions(-) [+]
line wrap: on
line diff
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/main/econometrics/nls_example.m	Tue Jun 13 13:25:13 2006 +0000
@@ -0,0 +1,60 @@
+## Copyright (C) 2006  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, write to the Free Software
+## Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
+
+## Example to show how to use NLS
+
+# Generate data
+n = 100; # how many observations?
+
+# the explanatory variables: note that they have unequal scales
+x = [ones(n,1) rand(n,2)];
+theta = 1:3; # true coefficients are 1,2,3
+theta = theta';
+
+lambda = exp(x*theta);
+y = randp(lambda); # generate the dependent variable
+
+# example objective function for nls
+function [obj_contrib, score] = nls_example_obj(theta, data, otherargs)
+	y = data(:,1);
+	x = data(:,2:columns(data));
+	lambda = exp(x*theta);
+	errors =  y - lambda;
+	obj_contrib = errors .* errors;
+	score = "na";
+endfunction
+
+
+####################################
+# define arguments for nls_estimate #
+####################################
+
+# starting values
+theta = zeros(3,1);
+
+# data
+data = [y, x];
+
+# name of model to estimate
+model = "nls_example_obj";
+modelargs = {}; # none required for this obj fn.
+
+
+# controls for bfgsmin
+control = {50,1,1,1};
+
+printf("\n\NLS estimation example\n");
+[theta, obj_value, convergence] = nls_estimate(theta, data, model, modelargs, control);