7.00.02 - Real-Time Change-Point Detection - Aster Analytics

Teradata Aster® Analytics Foundation User GuideUpdate 2

Aster Analytics
Release Number
September 2017
Content Type
Programming Reference
User Guide
Publication ID
English (United States)
Last Update

Usually, real-time change-point detection uses the sliding window algorithm.

Assume that the data follows a distribution, but has different parameters θ in different segments. In the two following hypotheses about the parameter,

H 0:θ = θ 0

H 1:θ = θ 1

the reference part has parameter θ 0 and the testing part in the sliding window has parameter θ 1, with the following notation:

The decision rule for testing the sliding window is:

If S j k < h 0, choose H 0.

If S j k h 0, choose H 1.