The changepoint problem in a multinomial sequence

Douglas A. Wolfe · Yun‐Shiow Chen

20 citations0/0 files storedCommunications in Statistics - Simulation and Computation

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Advanced Statistical Process Monitoring Probability and Statistical Research Bayesian Methods and Mixture Models

Abstract

The univariate changepoint problem has been extensively studied in the literature. Several investigators have developed test statistics and estimators (both parametric and nonparametric) in classical and Bayesian frameworks. Extensions to multivariate changepoint problems have also been considered. Most such papers have assumed that the variables have continuous distributions. In our study we consider the at most one changepoint(AMOC) problem in a sequence of multinomial random variables. Three estimators to detect a possible change in the sequence are proposed. The results of a Monte Carlo simulation study of the estimators are presented.

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References

1970Inference About the Change-Point in a Sequence of Random Variables 1975A Bayesian approach to inference about a change-point in a sequence of random variables 1986Likelihood Ratio Tests for a Change in the Multivariate Normal Mean 1970Inference About the Change-Point in a Sequence of Binomial Variables 1987Maximum likelihood estimation of a change-point in the distribution of independent random variables: General multiparameter case

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2013Change-point detection in multinomial data using phi-divergence test statistics 2020An online Bayesian approach to change-point detection for categorical data 2022Changepoint detection in autocorrelated ordinal categorical time series

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