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Bayesian Changepoints Detection for the Power Law Process with Binary Segmentation Procedures
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 Title & Authors
Bayesian Changepoints Detection for the Power Law Process with Binary Segmentation Procedures
Kim Hyunsoo; Kim Seong W.; Jang Hakjin;
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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.
 Keywords
Binary segmentation;Changepoint;Model selection;Intrinsic prior;Power law process;
 Language
English
 Cited by
 References
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