Multiple change-points detection based on U-Statistics under weak dependence

Fuente: arXiv
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Hauptverfasser: Ngatchou-Wandji, Joseph, Elharfaoui, Echarif, Harel, Michel
Format: Preprint
Veröffentlicht: 2025
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author Ngatchou-Wandji, Joseph
Elharfaoui, Echarif
Harel, Michel
author_facet Ngatchou-Wandji, Joseph
Elharfaoui, Echarif
Harel, Michel
contents We study multiple change-points detection using multi-samples tests based on U-statistics for absolutely regular observations. Our results extend those of Ngatchou-Wandji et al. (2022) concerned with the study of one single changepoint. The asymptotic distributions of the test statistics under the null hypothesis and under a sequence of 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 multiple changes in the mean, variance and autocorrelation of some simple times series models.
format Preprint
id arxiv_https___arxiv_org_abs_2511_18524
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Multiple change-points detection based on U-Statistics under weak dependence
Ngatchou-Wandji, Joseph
Elharfaoui, Echarif
Harel, Michel
Statistics Theory
60F17, 62F03, 62M10
We study multiple change-points detection using multi-samples tests based on U-statistics for absolutely regular observations. Our results extend those of Ngatchou-Wandji et al. (2022) concerned with the study of one single changepoint. The asymptotic distributions of the test statistics under the null hypothesis and under a sequence of 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 multiple changes in the mean, variance and autocorrelation of some simple times series models.
title Multiple change-points detection based on U-Statistics under weak dependence
topic Statistics Theory
60F17, 62F03, 62M10
url https://arxiv.org/abs/2511.18524