File Coverage

blib/lib/Text/NSP/Measures/3D/MI/ll.pm

Criterion	Covered	Total	%
statement	28	29	96.5
branch	2	2	100.0
condition			n/a
subroutine	6	7	85.7
pod			n/a
total	36	38	94.7

=head1 NAME

Text::NSP::Measures::3D::MI::ll - Perl module that implements Loglikelihood
                                  measure of association for trigrams.

=head1 SYNOPSIS

=head3 Basic Usage

  use Text::NSP::Measures::3D::MI::ll;

  $ll_value = calculateStatistic( n111=>10,
                                  n1pp=>40,
                                  np1p=>45,
                                  npp1=>42,
                                  n11p=>20,
                                  n1p1=>23,
                                  np11=>21,
                                  nppp=>100);

  if( ($errorCode = getErrorCode()))
  {
    print STDERR $erroCode." - ".getErrorMessage()."\n";
  }
  else
  {
    print getStatisticName."value for trigram is ".$ll_value."\n";
  }


=head1 DESCRIPTION

The log-likelihood ratio measures the devitation between the observed data
and what would be expected if ,  and  were independent.
The higher the score, the less evidence there is in favor of concluding that
the words are independent.

The expected values for the internal cells are calculated by taking the
product of their associated marginals and dividing by the sample size,
for example:

            n1pp * np1p * npp1
   m111=   --------------------
                   nppp

Then the deviation between observed and expected values for each internal
cell is computed to arrive at the log-likelihood value.

 Log-Likelihood = 2 * [n111 * log(n111/m111) + n112 * log(n112/m112) +
           n121 * log(n121/m121) + n122 * log(n122/m122) +
           n211 * log(n211/m211) + n212 * log(n212/m212) +
           n221 * log(n221/m221) + n222 * log(n222/m222)]

=over

=cut


package Text::NSP::Measures::3D::MI::ll;


use Text::NSP::Measures::3D::MI;
use strict;
use Carp;
use warnings;
no warnings 'redefine';
require Exporter;

our ($VERSION, @EXPORT, @ISA);

@ISA  = qw(Exporter);

@EXPORT = qw(initializeStatistic calculateStatistic
             getErrorCode getErrorMessage getStatisticName);

$VERSION = '0.97';

=item calculateStatistic($count_values) - This method calculates
the ll value

INPUT PARAMS  : $count_values       .. Reference of an hash containing
                                       the count values computed by the
                                       count.pl program.

RETURN VALUES : $loglikelihood      .. Loglikelihood value for this trigram.

=cut

sub calculateStatistic
{
  my %values = @_;

  # computes and sets the observed and expected values from
  # the frequency combination values. returns 0 if there is an
  # error in the computation or the values are inconsistent.
  if( !(Text::NSP::Measures::3D::MI::getValues(\%values)) ) {
    return;
  }

  #  Now for the actual calculation of Loglikelihood!
  my $logLikelihood = 0;

  # dont want ($nxy / $mxy) to be 0 or less! flag error if so!
  $logLikelihood += $n111 * Text::NSP::Measures::3D::MI::computePMI( $n111, $m111 );
  $logLikelihood += $n112 * Text::NSP::Measures::3D::MI::computePMI( $n112, $m112 );
  $logLikelihood += $n121 * Text::NSP::Measures::3D::MI::computePMI( $n121, $m121 );
  $logLikelihood += $n122 * Text::NSP::Measures::3D::MI::computePMI( $n122, $m122 );
  $logLikelihood += $n211 * Text::NSP::Measures::3D::MI::computePMI( $n211, $m211 );
  $logLikelihood += $n212 * Text::NSP::Measures::3D::MI::computePMI( $n212, $m212 );
  $logLikelihood += $n221 * Text::NSP::Measures::3D::MI::computePMI( $n221, $m221 );
  $logLikelihood += $n222 * Text::NSP::Measures::3D::MI::computePMI( $n222, $m222 );

  return ( 2 * $logLikelihood );
}


=item getStatisticName() - Returns the name of this statistic

INPUT PARAMS  : none

RETURN VALUES : $name      .. Name of the measure.

=cut

sub getStatisticName
{
    return "Loglikelihood";
}



1;
__END__