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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