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Sourcecode: octave-econometrics version File versions  Download package

mle_obj.m

# 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: [obj_value, score] = mle_obj(theta, data, model, modelargs, nslaves)
##
## Returns the average log-likelihood for a specified model
## This is for internal use by mle_estimate


function [obj_value, score] = mle_obj(theta, data, model, modelargs, nslaves)

      n = rows(data);   
      
      if nargin < 5 nslaves = 0; endif
      if nslaves > 0
            global NSLAVES PARALLEL NEWORLD NSLAVES TAG;

            nn = floor(n/(NSLAVES + 1)); # number of obsns per slave

            # The command that the slave nodes will execute
            cmd=; 

            # send items to slaves
            NumCmds_Send({"theta", "nn", "cmd"}, {theta, nn, cmd});

            # evaluate last block on master while slaves are busy
            obj_value = mle_obj_nodes(theta, data, model, modelargs, nn);

            # collect slaves' results
            contrib = 0.0; # must be initialized to use MPI_Recv
            for i = 1:NSLAVES
                  MPI_Recv(contrib,i,TAG,NEWORLD);
                  obj_value = obj_value + contrib;
            endfor

            # compute the average
            obj_value = - obj_value / n;
            score = "na"; # fix this later to allow analytic score in parallel
            
      else # serial version
            [contribs, score] = feval(model, theta, data, modelargs);
            obj_value = - mean(contribs);
            if isnumeric(score) score = - mean(score)'; endif # model passes "na" when score not available
      endif

      # let's bullet-proof this in case the model goes nuts
      if (((abs(obj_value) == Inf)) || (isnan(obj_value)))
            obj_value = realmax/10;
      endif     

endfunction

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