Abstract #301651

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JSM 2003 Abstract #301651
Activity Number: 175
Type: Contributed
Date/Time: Monday, August 4, 2003 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #301651
Title: Detecting Changepoints in Markov Chains
Author(s): Alan M. Polansky*+
Companies: Northern Illinois University
Address: Division of Statistics, Dekalb, IL, 60115,
Keywords: bootstrap ; dependence ; estimation ; p value
Abstract:

Markov chains provide a flexible model for weakly dependent random variables with applications in such disciplines as physics, environmental science and economics. In the applied study of Markov chains, it may be of interest to assess whether at some points during an observed realization of the process the transition probability matrix changes form. In such a case it would be of interest to estimate the transitions where a change takes place, the probability transition matrix before each change, and the probability transition matrix after each change. It would also be of interest to perform a statistical test on the existence of such a changes. This paper presents a methodology for addressing these issues that is based on a distance measure between estimated transition probability matrices. Statistical inference is performed using the bootstrap to compute the relevant p values. The proposed methods are studied empirically and are applied to an example problem.

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