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Biometrika 2004 91(4):849-862; doi:10.1093/biomet/91.4.849
© 2004 by Biometrika Trust
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A semiparametric changepoint model

Zhong Guan

Department of Mathematical Sciences, Indiana University South Bend, South Bend, Indiana 46634, U.S.A. zhong.guan{at}yale.edu

A semiparametric changepoint model is considered and the empirical likelihood method is applied to detect the change from a distribution to a weighted distribution in a sequence of independent random variables. The maximum likelihood changepoint estimator is shown to be consistent. The empirical likelihood ratio test statistic is proved to have the same limit null distribution as that with parametric models. A data-based test for the validity of the models is also proposed. Simulation shows the sensitivity and robustness of the semiparametric approach. The methods are applied to some classical datasets such as the Nile River data and stock price data.

Key Words: Changepoint; Empirical likelihood; Exponential family; Limit theorem; Power; Resampling; Robustness; Semiparametric changepoint model; Weighted distribution

Received February 2003. Revised February 2004.


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