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On change-points tests based on two-samples U-Statistics for weakly dependent observations

Author

Listed:
  • Joseph Ngatchou-Wandji

    (EHESP Sorbonne Paris Cité & Institut Élie Cartan de Lorraine)

  • Echarif Elharfaoui

    (Université Chouaîb Doukkali)

  • Michel Harel

    (INSPÉ Limoges
    IMT, UMR 5219 UPS)

Abstract

We study change-points tests based on U-statistics for absolutely regular observations. Our method avoids some technical assumptions on the data and the kernel. The asymptotic properties of the U-statistics are studied under the null hypothesis, under fixed alternatives and under a sequence of local alternatives. The asymptotic distributions of the test statistics under the null hypothesis and under the local alternatives are given explicitly and the tests are shown to be consistent. A small set of simulations is done for evaluating the performance of the tests in detecting changes in the mean, variance and autocorrelation of some simple time series.

Suggested Citation

  • Joseph Ngatchou-Wandji & Echarif Elharfaoui & Michel Harel, 2022. "On change-points tests based on two-samples U-Statistics for weakly dependent observations," Statistical Papers, Springer, vol. 63(1), pages 287-316, February.
    • Handle: RePEc:spr:stpapr:v:63:y:2022:i:1:d:10.1007_s00362-021-01242-3
    DOI: 10.1007/s00362-021-01242-3
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    Cited by:

    1. Mohamed Salah Eddine Arrouch & Echarif Elharfaoui & Joseph Ngatchou-Wandji, 2023. "Change-Point Detection in the Volatility of Conditional Heteroscedastic Autoregressive Nonlinear Models," Mathematics, MDPI, vol. 11(18), pages 1-31, September.

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    Keywords

    60F17; 62F03; 62M10;
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