/ 
Statistics-DEA-0.01
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/ Statistics::DEA

NAME

Statistics::DEA - Discontiguous Exponential Averaging

SYNOPSIS

 use Statistics::DEA;

 my $dea = Statistics::DEA->new($alpha, $max_gap);

 while (($data, $time) = some_data_source(...)) {
   ...
   $dea->update($data, $time);
   print $dea->average(), "\n";
   print $dea->standard_deviation(), "\n";
   print $dea->completeness($time), "\n";
   ...
}

DESCRIPTION

The Statistics::DEA module can be used to compute exponentially decaying averages even when the data has gaps. The algorithm also avoids initial value bias and postgap bias.

new

my $dea = Statistics::DEA->new($alpha, $max_gap);

Creates a new (potentially discontiguous) exponential average object.

The $alpha is the exponential decay of data: from zero (inclusive) to one (exclusive): the lower values cause the effect of data to decay more quickly, the higher values cause the effect of data to decay more slowly.

The $max_gap is the maximum time gap after which the data is considered lost (decay should bring the average to zero).

update

$dea->update($data, $time);

Update the average with new data at a particular point in time.

The time parameter is how you can indicate gaps in the data; if you don't have gaps in your data, just monotonously increase it, for example $time++.

average

my $avg = $dea->average();

Return the current average.

Functionally equivalent alias avg() is also available.

standard_deviation

my $std_dev = $dea->standard_deviation();

Return the current standard deviation.

Functionally equivalent alias std_dev() is also available.

completeness

my $completeness = $dea->completeness();

Return the current completeness: how well based the current average and standard deviation are on actual data. Any gaps reduce this value.

alpha

my $alpha = $dea->alpha();

Return the current exponential decay of data.

$dea->alpha($alpha);

Set the exponential decay of data.

max_gap

my $alpha = $dea->alpha();

Return the current maximum time gap.

$dea->max_gap($max_gap);

Set the maximum time gap.

AUTHOR

Jarkko Hietaniemi <jhi@iki.fi>

ACKNOWLEDGEMENT

The idea and the code is from the September 1998 Doctor Dobb's Journal Algorithm Alley article "Discontiguous Exponential Averaging" by John C. Gunther, used with permission. This is just a Perlification of the code, all errors in transcription are solely mine.