Functional Sieve Bootstrap for the Partial Sum Process With an Application to Change-Point Detection

IF 1 4区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Journal of Time Series Analysis Pub Date : 2026-04-07 Epub Date: 2025-06-23 DOI:10.1111/jtsa.12852
Efstathios Paparoditis, Lea Wegner, Martin Wendler
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引用次数: 0

Abstract

This article applies the functional sieve bootstrap (FSB) to estimate the distribution of the partial sum process for time series stemming from a weakly stationary functional process. Consistency of the FSB procedure under weak assumptions on the underlying functional process is established. This result allows for the application of the FSB procedure to testing for a change-point in the mean of a functional time series using the CUSUM-statistic. We show that the FSB asymptotically correctly estimates critical values of the CUSUM-based test under the null-hypothesis. Consistency of the FSB-based test under local alternatives is also proven. The finite-sample performance of the procedure is studied via simulations.

Abstract Image

部分和过程的功能筛引导及其在变化点检测中的应用
本文应用功能筛子自举法(FSB)估计由弱平稳泛函过程产生的时间序列的部分和过程的分布。建立了FSB过程在底层功能过程弱假设下的一致性。该结果允许应用FSB程序来测试使用cusum统计量的函数时间序列平均值中的变化点。我们证明了FSB在零假设下渐近正确地估计了基于cusum的检验的临界值。验证了基于fsb的测试在局部替代方案下的一致性。通过仿真研究了该方法的有限样本性能。
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来源期刊
Journal of Time Series Analysis
Journal of Time Series Analysis 数学-数学跨学科应用
CiteScore
2.00
自引率
0.00%
发文量
39
审稿时长
6-12 weeks
期刊介绍: During the last 30 years Time Series Analysis has become one of the most important and widely used branches of Mathematical Statistics. Its fields of application range from neurophysiology to astrophysics and it covers such well-known areas as economic forecasting, study of biological data, control systems, signal processing and communications and vibrations engineering. The Journal of Time Series Analysis started in 1980, has since become the leading journal in its field, publishing papers on both fundamental theory and applications, as well as review papers dealing with recent advances in major areas of the subject and short communications on theoretical developments. The editorial board consists of many of the world''s leading experts in Time Series Analysis.
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