Add a useful package (from Source forge) for octave

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

diff --git a/octave_packages/econometrics-1.0.8/mle_estimate.m b/octave_packages/econometrics-1.0.8/mle_estimate.m
new file mode 100644 (file)
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+++ b/octave_packages/econometrics-1.0.8/mle_estimate.m
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+## 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/>.
+
+# usage:
+# [theta, obj_value, conv, iters] = mle_estimate(theta, data, model, modelargs, control, nslaves)
+#
+# inputs:
+# theta: column vector of model parameters
+# data: data matrix
+# model: name of function that computes log-likelihood
+# modelargs: (cell) additional inputs needed by model. May be empty ("")
+# control: (optional) BFGS or SA controls (see bfgsmin and samin). May be empty ("").
+# nslaves: (optional) number of slaves if executed in parallel (requires MPITB)
+#
+# outputs:
+# theta: ML estimated value of parameters
+# obj_value: the value of the log likelihood function at ML estimate
+# conv: return code from bfgsmin (1 means success, see bfgsmin for details)
+# iters: number of BFGS iteration used
+#
+# please see mle_example.m for examples of how to use this
+function [theta, obj_value, convergence, iters] = mle_estimate(theta, data, model, modelargs, control, nslaves)
+
+
+       if nargin < 3
+               error("mle_estimate: 3 arguments required");
+       endif
+
+       if nargin < 4 modelargs = {}; endif # create placeholder if not used
+       if !iscell(modelargs) modelargs = {}; endif # default controls if receive placeholder
+       if nargin < 5 control = {-1,0,1,1}; endif # default controls and method
+       if !iscell(control) control = {-1,0,1,1}; endif # default controls if receive placeholder
+       if nargin < 6 nslaves = 0; endif
+       if nslaves > 0
+               global NSLAVES PARALLEL NEWORLD TAG;
+               LAM_Init(nslaves);
+               # Send the data to all nodes
+               NumCmds_Send({"data", "model", "modelargs"}, {data, model, modelargs});
+       endif
+
+       # bfgs or sa?
+       if (size(control,1)*size(control,2) == 0) # use default bfgs if no control
+               control = {Inf,0,1,1};
+               method = "bfgs";
+       elseif (size(control,1)*size(control,2) < 11)
+               method = "bfgs";
+       else method = "sa";
+       endif
+
+       # do estimation using either bfgsmin or samin
+       if strcmp(method, "bfgs")
+         [theta, obj_value, convergence, iters] = bfgsmin("mle_obj", {theta, data, model, modelargs, nslaves}, control);
+       elseif strcmp(method, "sa")
+         [theta, obj_value, convergence] = samin("mle_obj", {theta, data, model, modelargs, nslaves}, control);
+       endif
+
+       if nslaves > 0
+               LAM_Finalize;
+       endif # cleanup
+       obj_value = - obj_value; # recover from minimization rather than maximization
+endfunction