Background - Aster Analytics

Teradata Aster Analytics Foundation User Guide

Product
Aster Analytics
Release Number
6.21
Published
November 2016
Language
English (United States)
Last Update
2018-04-14
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kiu1466024880662.ditamap
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AA-notempfilter_pdf_output.ditaval
dita:id
B700-1021
lifecycle
previous
Product Category
Software

Exponential moving average (EMA), or exponentially weighted moving average (EWMA), applies a damping factor, alpha, that exponentially decreases the weights of older values. This technique gives much more weight to recent observations, while retaining older observations.

The EMAVG function computes the arithmetic average of the first n rows and then, for each subsequent row, computes the new value with this formula:

new_emavg = alpha * new_value + (1-alpha) * old_emavg

The initial value of old_emavg is the arithmetic average of the first n rows. The values n and alpha are specified by the function arguments Start_Rows and Alpha, respectively.