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Rates of convergence for the change-point estimator for long-range dependent sequences

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  • Hariz, Samir Ben
  • Wylie, Jonathan J.

Abstract

We consider a cumulative sum estimator for the change-point of a (possibly) long-range dependent sequence with a shift in the mean. We show that the 1/n convergence rate typical of the independent case is also achieved for short-memory and long-memory sequences.

Suggested Citation

  • Hariz, Samir Ben & Wylie, Jonathan J., 2005. "Rates of convergence for the change-point estimator for long-range dependent sequences," Statistics & Probability Letters, Elsevier, vol. 73(2), pages 155-164, June.
    • Handle: RePEc:eee:stapro:v:73:y:2005:i:2:p:155-164
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    References listed on IDEAS

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    1. Kokoszka, Piotr & Leipus, Remigijus, 1998. "Change-point in the mean of dependent observations," Statistics & Probability Letters, Elsevier, vol. 40(4), pages 385-393, November.
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    Cited by:

    1. Zhou, Houlin & Zhu, Hanbing & Wang, Xuejun, 2024. "Change point detection via feedforward neural networks with theoretical guarantees," Computational Statistics & Data Analysis, Elsevier, vol. 193(C).
    2. Zhuoheng Chen & Yijun Hu, 2017. "Cumulative sum estimator for change-point in panel data," Statistical Papers, Springer, vol. 58(3), pages 707-728, September.
    3. Yi Wu & Wei Wang & Xuejun Wang, 2024. "Convergence of the CUSUM estimation for a mean shift in linear processes with random coefficients," Computational Statistics, Springer, vol. 39(7), pages 3753-3778, December.
    4. 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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