Add a useful package (from Source forge) for octave

[CreaPhase.git] / octave_packages / econometrics-1.0.8 / nls_example.m

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+## 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, see <http://www.gnu.org/licenses/>.
+
+## 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 - limit to 50 iters, and print final results
+control = {50,1};
+
+####################################
+# do the estimation               #
+####################################
+printf("\nNLS estimation example\n");
+[theta, obj_value, convergence] = nls_estimate(theta, data, model, modelargs, control);