Continuous monitoring for changepoints in data streams using adaptive estimation

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Title: Continuous monitoring for changepoints in data streams using adaptive estimation
Authors: Bodenham, DA
Adams, NM
Item Type: Journal Article
Abstract: Data streams are characterised by a potentially unending sequence of high-frequency observations which are subject to unknown temporal variation. Many modern streaming applications demand the capability to sequentially detect changes as soon as possible after they occur, while continuing to monitor the stream as it evolves. We refer to this problem as continuous monitoring. Sequential algorithms such as CUSUM, EWMA and their more sophisticated variants usually require a pair of parameters to be selected for practical application. However, the choice of parameter values is often based on the anticipated size of the changes and a given choice is unlikely to be optimal for the multiple change sizes which are likely to occur in a streaming data context. To address this critical issue, we introduce a changepoint detection framework based on adaptive forgetting factors that, instead of multiple control parameters, only requires a single parameter to be selected. Simulated results demonstrate that this framework has utility in a continuous monitoring setting. In particular, it reduces the burden of selecting parameters in advance. Moreover, the methodology is demonstrated on real data arising from Foreign Exchange markets.
Issue Date: 18-Jul-2016
Date of Acceptance: 8-Jul-2016
URI: http://hdl.handle.net/10044/1/34625
DOI: https://dx.doi.org/10.1007/s11222-016-9684-8
ISSN: 1573-1375
Publisher: Springer Verlag
Start Page: 1257
End Page: 1270
Journal / Book Title: Statistics and Computing
Volume: 27
Issue: 5
Copyright Statement: © Springer Science+Business Media New York 2016. The final publication is available at Springer via https://link.springer.com/article/10.1007%2Fs11222-016-9684-8
Keywords: Science & Technology
Technology
Physical Sciences
Computer Science, Theory & Methods
Statistics & Probability
Computer Science
Mathematics
Changepoint detection
Adaptive estimation
Data stream
Sequential analysis
SELF-TUNING REGULATORS
STATISTICAL PROCESS-CONTROL
CONTROL CHARTS
0104 Statistics
0802 Computation Theory And Mathematics
Publication Status: Published
Appears in Collections:Mathematics
Statistics
Faculty of Natural Sciences



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