Bayesian change-point problem using Bayes factor with hierarchical prior distribution

Myoungjin Jung, Seongho Song and Younshik Chung

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 3, 1352-1366

Abstract: We consider the hierarchical Bayesian models of change-point problem in a sequence of random variables having either normal population or skew-normal population. Further, we consider the problem of detecting an influential point concerning change point using Bayes factors. Our proposed models are illustrated with the real data example, the annual flow volume data of Nile River at Aswan from 1871 to 1970. The result using our proposed models indicated the largest influential observation in the year 1888 among outliers. We have shown that it is useful to measure the influence of observations on Bayes factors. Here, we consider omitting single observation as well.

Date: 2017
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DOI: 10.1080/03610926.2015.1019143

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