Real-Time Change-Point Detection - Aster Analytics

Teradata Aster® Analytics Foundation User GuideUpdate 2

Product
Aster Analytics
Release Number
7.00.02
Published
September 2017
Language
English (United States)
Last Update
2018-04-17
dita:mapPath
uce1497542673292.ditamap
dita:ditavalPath
AA-notempfilter_pdf_output.ditaval
dita:id
B700-1022
lifecycle
previous
Product Category
Software

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.