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Robust Wilcoxon†Type Estimation of Change†Point Location Under Short†Range Dependence

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  • Carina Gerstenberger

Abstract

We introduce a robust estimator of the location parameter for the change†point in the mean based on Wilcoxon statistic and establish its consistency for L1 near†epoch dependent processes. It is shown that the consistency rate depends on the magnitude of the change. A simulation study is performed to evaluate the finite sample properties of the Wilcoxon†type estimator under Gaussianity as well as under heavy†tailed distributions and disturbances by outliers, and to compare it with a CUSUM†type estimator. It shows that the Wilcoxon†type estimator is equivalent to the CUSUM†type estimator under Gaussianity but outperforms it in the presence of heavy tails or outliers in the data.

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  • Carina Gerstenberger, 2018. "Robust Wilcoxon†Type Estimation of Change†Point Location Under Short†Range Dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(1), pages 90-104, January.
    • Handle: RePEc:bla:jtsera:v:39:y:2018:i:1:p:90-104
    DOI: 10.1111/jtsa.12268
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    Cited by:

    1. Lazar, Emese & Wang, Shixuan & Xue, Xiaohan, 2023. "Loss function-based change point detection in risk measures," European Journal of Operational Research, Elsevier, vol. 310(1), pages 415-431.
    2. Carina Gerstenberger, 2021. "Robust discrimination between long‐range dependence and a change in mean," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(1), pages 34-62, January.
    3. Josephine Njeri Ngure & Anthony Gichuhi Waititu, 2021. "Consistency of an Estimator for Change Point in Volatility of Financial Returns," Journal of Mathematics Research, Canadian Center of Science and Education, vol. 13(1), pages 1-56, February.
    4. Kang-Ping Lu & Shao-Tung Chang, 2022. "Robust Switching Regressions Using the Laplace Distribution," Mathematics, MDPI, vol. 10(24), pages 1-24, December.
    5. Kang-Ping Lu & Shao-Tung Chang, 2021. "Robust Algorithms for Change-Point Regressions Using the t -Distribution," Mathematics, MDPI, vol. 9(19), pages 1-28, September.

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