Multiscale change point detection

A. Suvorikova, V. Spokoiny

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Pages (from-to)665-691
Number of pages27
JournalTheory of Probability and its Applications
Volume61
Issue number4
DOIs
Publication statusPublished - 2017
Externally publishedYes

Keywords

  • Likelihood ratio test
  • Multiplier bootstrap
  • Multiscale change point detection
  • Scrolling window

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