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On the asymptotic behavior of a class of nonparametric tests for a change-point problem

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  • Yao, Yi-Ching

Abstract

A class of linear rank statistics is considered for testing a sequence of independent random variables with common distribution against alternatives involving a change in distribution at an unknown time point. It is shown that, under the null hypothesis and suitably normalized, this class of statistics converges in distribution to the double exponential extreme value distribution.

Suggested Citation

  • Yao, Yi-Ching, 1990. "On the asymptotic behavior of a class of nonparametric tests for a change-point problem," Statistics & Probability Letters, Elsevier, vol. 9(2), pages 173-177, February.
    • Handle: RePEc:eee:stapro:v:9:y:1990:i:2:p:173-177
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    Cited by:

    1. Cho, Haeran & Kirch, Claudia, 2024. "Data segmentation algorithms: Univariate mean change and beyond," Econometrics and Statistics, Elsevier, vol. 30(C), pages 76-95.
    2. Csörgo, Miklós & Horváth, Lajos, 1996. "A note on the change-point problem for angular data," Statistics & Probability Letters, Elsevier, vol. 27(1), pages 61-65, March.
    3. 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.
    4. Husková, M., 1997. "Limit theorems for rank statistics," Statistics & Probability Letters, Elsevier, vol. 32(1), pages 45-55, February.
    5. Zdeněk Hlávka & Marie Hušková & Claudia Kirch & Simos Meintanis, 2012. "Monitoring changes in the error distribution of autoregressive models based on Fourier methods," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(4), pages 605-634, December.

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