Selective review of offline change point detection methods

被引：588
作者：
Truong, Charles [1 ]
Oudre, Laurent [2 ]
Vayatis, Nicolas [1 ]
机构：
[1] ENS Paris Saclay, CNRS, CMLA, Cachan, France
[2] Univ Paris 13, L2TI, Villetaneuse, France
来源：
SIGNAL PROCESSING | 2020年 / 167卷 / 167期
关键词：
Change point detection; Segmentation; Statistical signal processing; MULTIPLE CHANGE-POINT; CIRCULAR BINARY SEGMENTATION; LEAST-SQUARES ESTIMATION; ARRAY CGH DATA; NUMBER; MODELS; TESTS; ALGORITHM; DIMENSION; BREAKS;
D O I：
10.1016/j.sigpro.2019.107299
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This article presents a selective survey of algorithms for the offline detection of multiple change points in multivariate time series. A general yet structuring methodological strategy is adopted to organize this vast body of work. More precisely, detection algorithms considered in this review are characterized by three elements: a cost function, a search method and a constraint on the number of changes. Each of those elements is described, reviewed and discussed separately. Implementations of the main algorithms described in this article are provided within a Python package called ruptures. (C) 2019 Elsevier B.V. All rights reserved.
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页数：20
相关论文
共 152 条
  • [1] Time-dependent spectral analysis of nonstationary time series
    Adak, S
    [J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1998, 93 (444) : 1488 - 1501
  • [2] A survey of methods for time series change point detection
    Aminikhanghahi, Samaneh
    Cook, Diane J.
    [J]. KNOWLEDGE AND INFORMATION SYSTEMS, 2017, 51 (02) : 339 - 367
  • [3] Group lassoing change-points in piecewise-constant AR processes
    Angelosante, Daniele
    Giannakis, Georgios B.
    [J]. EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2012,
  • [4] [Anonymous], 2019, P IEEE INT C ACOUSTI
  • [5] [Anonymous], 2007, P 24 INT C MACH LEAR
  • [6] [Anonymous], 2012, ARXIV PREPRINT ARXIV
  • [7] A survey of cross-validation procedures for model selection
    Arlot, Sylvain
    Celisse, Alain
    [J]. STATISTICS SURVEYS, 2010, 4 : 40 - 79
  • [8] Audiffren J., NEUROPHYSIOLOGIE CLI
  • [9] Structural breaks in time series
    Aue, Alexander
    Horvath, Lajos
    [J]. JOURNAL OF TIME SERIES ANALYSIS, 2013, 34 (01) : 1 - 16
  • [10] Testing for and dating common breaks in multivariate time series
    Bai, J
    Lumsdaine, RL
    Stock, JH
    [J]. REVIEW OF ECONOMIC STUDIES, 1998, 65 (03) : 395 - 432
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