Multiple Change-Point Detection in a Functional Sample via the G-Sum Process

Multiple Change-Point Detection in a Functional Sample via the G-Sum Process

We first define the G-CUSUM process and investigate its theoretical aspects including asymptotic behavior. By choosing different sets G, we propose some tests for multiple change-point detections in a functional sample. We apply the proposed testing procedures to the real-world neurophysiological da...

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Bibliographic Details
Main Authors: Danielius, T. (Author), Račkauskas, A. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
functional change-point detection
functional data
functional principal component analysis
p-variation
Online Access:View Fulltext in Publisher
Description
Summary:We first define the G-CUSUM process and investigate its theoretical aspects including asymptotic behavior. By choosing different sets G, we propose some tests for multiple change-point detections in a functional sample. We apply the proposed testing procedures to the real-world neurophysiological data and demonstrate how it can identify the existence of the multiple change-points and localize them. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
ISBN:22277390 (ISSN)
DOI:10.3390/math10132294

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