Statistics::Descriptive::Smoother::Weigthedexponential − Implement weighted exponential smoothing
use Statistics::Descriptive::Smoother; my $smoother = Statistics::Descriptive::Smoother−>instantiate({ method => 'weightedexponential', coeff => 0.5, data => [1, 2, 3, 4, 5], samples => [110, 120, 130, 140, 150], }); my @smoothed_data = $smoother−>get_smoothed_data();
This module implement the weighted exponential smoothing algorithm to smooth the trend of a series of statistical data.
This algorithm can help to control large swings in the unsmoothed data that arise from small samples for those data points.
The algorithm implements the following formula:
W(t) = ( W(t−1) * CoeffA + N(t) * CoeffB ) / (CoeffA + CoeffB)
CoeffA = C * ( W(t−1) / (W(t−1) + N(t) ) )
CoeffB = (1 − C) * ( N(t) * (W(t−1) + N(t)) )
S(t) = (S(t−1)*CoeffA + X(t)*CoeffB) / (CoeffA + CoeffB)
where:
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t = index in the series |
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S(t) = smoothed series value at position t |
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C = smoothing coefficient. Value in the [0;1] range. 0 means that the series is not smoothed at all, while 1 the series is universally equal to the initial unsmoothed value. |
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X(t) = unsmoothed series value at position t |
$stats−>get_smoothed_data();
Returns a copy of the smoothed data array.
Fabio Ponciroli
Copyright(c) 2012 by Fabio Ponciroli.
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