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2022 Change-point detection based on weighted two-sample U-statistics
Herold Dehling, Kata Vuk, Martin Wendler
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Electron. J. Statist. 16(1): 862-891 (2022). DOI: 10.1214/21-EJS1964

Abstract

We investigate the large-sample behavior of change-point tests based on weighted two-sample U-statistics, in the case of short-range dependent data. Under some mild mixing conditions, we establish convergence of the test statistic to an extreme value distribution. A simulation study shows that the weighted tests are superior to the non-weighted versions when the change-point occurs near the boundary of the time interval, while they loose power in the center.

Funding Statement

H. Dehling and K. Vuk were supported by the Collaborative Research Grant SFB 823 Statistical modelling of nonlinear dynamic processes. M. Wendler was supported by the German Research Foundation (DFG), project WE 5988/3 Analyse funktionaler Daten ohne Dimensionsreduktion.

Citation

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Herold Dehling. Kata Vuk. Martin Wendler. "Change-point detection based on weighted two-sample U-statistics." Electron. J. Statist. 16 (1) 862 - 891, 2022. https://doi.org/10.1214/21-EJS1964

Information

Received: 1 February 2021; Published: 2022
First available in Project Euclid: 26 January 2022

Digital Object Identifier: 10.1214/21-EJS1964

Keywords: change-point tests , extreme value distribution , short-range dependence , U-statistics , Wilcoxon test

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Vol.16 • No. 1 • 2022
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