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http://dx.doi.org/10.5351/CKSS.2005.12.2.483

Bayesian Changepoints Detection for the Power Law Process with Binary Segmentation Procedures  

Kim Hyunsoo (School of Information and Communications Engineering, Sungkyunkwan University)
Kim Seong W. (Division of Applied Mathematics, Hanyang University)
Jang Hakjin (Division of Applied Mathematics, Hanyang University)
Publication Information
Communications for Statistical Applications and Methods / v.12, no.2, 2005 , pp. 483-496 More about this Journal
Abstract
We consider the power law process which is assumed to have multiple changepoints. We propose a binary segmentation procedure for locating all existing changepoints. We select one model between the no-changepoints model and the single changepoint model by the Bayes factor. We repeat this procedure until no more changepoints are found. Then we carry out a multiple test based on the Bayes factor through the intrinsic priors of Berger and Pericchi (1996) to investigate the system behaviour of failure times. We demonstrate our procedure with a real dataset and some simulated datasets.
Keywords
Binary segmentation; Changepoint; Model selection; Intrinsic prior; Power law process;
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