Pacote: golang-github-vividcortex-ewma-dev (1.1.1-2)

Exponentially Weighted Moving Average algorithms for Go

An exponentially weighted moving average is a way to continuously compute a type of average for a series of numbers, as the numbers arrive. After a value in the series is added to the average, its weight in the average decreases exponentially over time. This biases the average towards more recent data. EWMAs are useful for several reasons, chiefly their inexpensive computational and memory cost, as well as the fact that they represent the recent central tendency of the series of values.

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