Bayesian Multiple Changepoints Detection for the Power Law Process with Binary Segmentation Procedures
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We consider a power law process assumed to have multiple changepoints. We propose a binary segmentation procedure for locating changepoints. We select one model between no-changepoint model and changepoint model by the Bayes factor. We repeat this procedure until no more changepoint is found. Then we carry out a multiple test with the Bayes factor through the intrinsic priors of Berger and Pericchi (1996) to investigate the system behaviour of failure times. We demonstrate our results with a real dataset and some simulated datasets.
Abstract
We consider a power law process assumed to have multiple changepoints. We propose a binary segmentation procedure for locating changepoints. We select one model between no-changepoint model and changepoint model by the Bayes factor. We repeat this procedure until no more changepoint is found. Then we carry out a multiple test with the Bayes factor through the intrinsic priors of Berger and Pericchi (1996) to investigate the system behaviour of failure times. We demonstrate our results with a real dataset and some simulated datasets.
참고문헌 (14)
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