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Research Article | Open Access

Sieve bootstrap test for multiple change points in the mean of long memory sequence

Wenzhi Zhao( ), Dou Liu, Huiming Wang
School of Science, Xi'an Polytechnic University, Xi'an, Shaanxi 710048, China
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Abstract

In this paper, the sieve bootstrap test for multiple change points in the mean of long memory sequence is studied. Firstly, the ANOVA test statistics for change points detection is obtained. Secondly, sieve bootstrap statistics is constructed and the consistency under the Mallows measure is proved. Finally, the effectiveness of the method was illustrated by simulation and example analysis. Simulation results show that our method can not only control the empirical size well but also have reasonable good power.

Keywords

long memorymultiple change pointsANOVAsieve bootstraptest
CLC number: 62F05, 62M10

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AIMS Mathematics
Volume 7 Issue 6,
June 2022
Pages 10245-10255
DOI: 10.3934/math.2022570

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Cite this article:
Zhao W, Liu D, Wang H. Sieve bootstrap test for multiple change points in the mean of long memory sequence. AIMS Mathematics, 2022, 7(6): 10245-10255. https://doi.org/10.3934/math.2022570

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Received: 16 December 2021
Revised: 05 March 2022
Accepted: 14 March 2022
Published: 15 June 2022
©2022 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)