Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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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)
  • Published : 2005.08.01
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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.

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References

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