文章基本信息

标题：On a Nonparametric Change Point Detection Model in Markovian Regimes
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作者：Asael Fabian Martínez ; Ramsés H. Mena
期刊名称：Bayesian Analysis
印刷版ISSN：1931-6690
电子版ISSN：1936-0975
出版年度：2014
卷号：9
期号：4
页码：823-858
DOI：10.1214/14-BA878
语种：English
出版社：International Society for Bayesian Analysis
摘要：Change point detection models aim to determine the most probable grouping for a given sample indexed on an ordered set. For this purpose, we propose a methodology based on exchangeable partition probability functions, specifically on Pitman’s sampling formula. Emphasis will be given to the Markovian case, in particular for discretely observed Ornstein-Uhlenbeck diffusion processes. Some properties of the resulting model are explained and posterior results are obtained via a novel Markov chain Monte Carlo algorithm.