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A semiparametric changepoint model

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  • Zhong Guan

Abstract

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. Copyright 2004, Oxford University Press.

Suggested Citation

  • Zhong Guan, 2004. "A semiparametric changepoint model," Biometrika, Biometrika Trust, vol. 91(4), pages 849-862, December.
    • Handle: RePEc:oup:biomet:v:91:y:2004:i:4:p:849-862
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    File URL: http://hdl.handle.net/10.1093/biomet/91.4.849
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    Cited by:

    1. Wei Ning, 2012. "Empirical likelihood ratio test for a mean change point model with a linear trend followed by an abrupt change," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(5), pages 947-961, September.
    2. Gabriela Ciuperca & Zahraa Salloum, 2015. "Empirical likelihood test in a posteriori change-point nonlinear model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(8), pages 919-952, November.
    3. Zonghui Hu & Jing Qin & Dean Follmann, 2008. "Semiparametric two‐sample changepoint model with application to human immunodeficiency virus studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(5), pages 589-607, December.
    4. Zhu, Xiaoqian & Xie, Yongjia & Li, Jianping & Wu, Dengsheng, 2015. "Change point detection for subprime crisis in American banking: From the perspective of risk dependence," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 18-28.
    5. Zou, Changliang & Liu, Yukun & Qin, Peng & Wang, Zhaojun, 2007. "Empirical likelihood ratio test for the change-point problem," Statistics & Probability Letters, Elsevier, vol. 77(4), pages 374-382, February.
    6. Venkata Jandhyala & Stergios Fotopoulos & Ian MacNeill & Pengyu Liu, 2013. "Inference for single and multiple change-points in time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 423-446, July.

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