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Teor. Veroyatnost. i Primenen., 2016, Volume 61, Issue 4, Pages 774–804 (Mi tvp5087)  

Multiscale approach for change point detection

A. L. Suvorikovaab, V. G. Spokoinycb

a Humboldt University, Berlin
b Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevich Institute), Moscow
c Weierstrass Institute for Applied Analysis and Stochastics, Berlin

Abstract: In this paper we present a multiscale approach for change point detection. The algorithm estimates likelihood-ratio (LR) test in several scrolling windows simultaneously. This makes the method adaptive to structural breaks of different scales. Critical values are calibrated in a data-driven way using multiplier bootstrap, which estimates nonasymptotic distribution of the test statistics.

Keywords: multiscale change point detection, multiplier bootstrap, scrolling window, likelihood ratio test.

Funding Agency Grant Number
Russian Science Foundation 14-50-00150


DOI: https://doi.org/10.4213/tvp5087

Full text: PDF file (432 kB)
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English version:
Theory of Probability and its Applications, 2017, 61:4, 665–691

Bibliographic databases:

Document Type: Article
Received: 05.09.2016

Citation: A. L. Suvorikova, V. G. Spokoiny, “Multiscale approach for change point detection”, Teor. Veroyatnost. i Primenen., 61:4 (2016), 774–804; Theory Probab. Appl., 61:4 (2017), 665–691

Citation in format AMSBIB
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  • http://mi.mathnet.ru/eng/tvp/v61/i4/p774

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