{"title":"A sequential feature selection approach to change point detection in mean-shift change point models","authors":"","doi":"10.1007/s00362-024-01548-y","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>Change point detection is an important area of scientific research and has applications in a wide range of fields. In this paper, we propose a sequential change point detection (SCPD) procedure for mean-shift change point models. Unlike classical feature selection based approaches, the SCPD method detects change points in the order of the conditional change sizes and makes full use of the identified change points information. The extended Bayesian information criterion (EBIC) is employed as the stopping rule in the SCPD procedure. We investigate the theoretical property of the procedure and compare its performance with other methods existing in the literature. It is established that the SCPD procedure has the property of detection consistency. Simulation studies and real data analyses demonstrate that the SCPD procedure has the edge over the other methods in terms of detection accuracy and robustness.</p>","PeriodicalId":51166,"journal":{"name":"Statistical Papers","volume":"33 1","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistical Papers","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s00362-024-01548-y","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
Change point detection is an important area of scientific research and has applications in a wide range of fields. In this paper, we propose a sequential change point detection (SCPD) procedure for mean-shift change point models. Unlike classical feature selection based approaches, the SCPD method detects change points in the order of the conditional change sizes and makes full use of the identified change points information. The extended Bayesian information criterion (EBIC) is employed as the stopping rule in the SCPD procedure. We investigate the theoretical property of the procedure and compare its performance with other methods existing in the literature. It is established that the SCPD procedure has the property of detection consistency. Simulation studies and real data analyses demonstrate that the SCPD procedure has the edge over the other methods in terms of detection accuracy and robustness.
期刊介绍：
The journal Statistical Papers addresses itself to all persons and organizations that have to deal with statistical methods in their own field of work. It attempts to provide a forum for the presentation and critical assessment of statistical methods, in particular for the discussion of their methodological foundations as well as their potential applications. Methods that have broad applications will be preferred. However, special attention is given to those statistical methods which are relevant to the economic and social sciences. In addition to original research papers, readers will find survey articles, short notes, reports on statistical software, problem section, and book reviews.
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