EWMean

Exponentially weighted mean.

Parameters

• fading_factor

  Default → 0.5

  The closer fading_factor is to 1 the more the statistic will adapt to recent values.

Attributes

• mean (float)

  The running exponentially weighted mean.

Examples

from river import stats

X = [1, 3, 5, 4, 6, 8, 7, 9, 11]
ewm = stats.EWMean(fading_factor=0.5)
for x in X:
    ewm.update(x)
    print(ewm.get())

1.0
2.0
3.5
3.75
4.875
6.4375
6.71875
7.859375
9.4296875

Methods

get

Return the current value of the statistic.

update

Update the called instance.

Parameters

• x — 'numbers.Number'

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1. Finch, T., 2009. Incremental calculation of weighted mean and variance. University of Cambridge, 4(11-5), pp.41-42. ↩

2. Exponential Moving Average on Streaming Data ↩