Sequential block bootstrap in a Hilbert space with application to change\n point analysis

2014/12/01 by Olimjon Sh. Sharipov, Sharipov, Olimjon, Johannes Tewes +3
Mathematics · #FOS: Mathematics #Statistical Methods and Inference #Statistics Theory (math.ST)

paper · pdf · doi:10.48550/arxiv.1412.0446

openalex publication_date 2014/12/01 · openalex created_date 2022/09/22 · openalex updated_date 2026/07/28

Abstract

A new test for structural changes in functional data is investigated. It is\nbased on Hilbert space theory and critical values are deduced from bootstrap\niterations. Thus a new functional central limit theorem for the block bootstrap\nin a Hilbert space is required. The test can also be used to detect changes in\nthe marginal distribution of random vectors, which is supplemented by a\nsimulation study. Our methods are applied to hydrological data from Germany.\n

Related

• Change-Point Detection and Bootstrap for Hilbert Space Valued Random\n Fields
• Bootstrap for dependent Hilbert space-valued random variables with application to von Mises statistics
• Bootstrapping Covariance Operators of Functional Time Series
• Robust Change-Point Detection for Functional Time Series Based on U-Statistics and Dependent Wild Bootstrap
• A Kernel Multiple Change-point Algorithm via Model Selection