A robust changepoint detection method

Moshe Pollak*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

For detecting an abrupt change when observations are continuous and independent, classical methods assume that the observations belong to a parametric family. Nonparametric methods have been devised, but usually they do not guarantee asymptotic optimality at a parametric model of choice. This article presents a nonparametric changepoint detection approach that guarantees compliance with a prespecified lower bound on the ARL to false alarm whatever the underlying distribution is, yet promises asymptotic first-order optimality if the true underlying distribution belongs to a suspected parametric family.

Original languageEnglish
Pages (from-to)146-161
Number of pages16
JournalSequential Analysis
Volume29
Issue number2
DOIs
StatePublished - Apr 2010

Keywords

  • Changepoint detection
  • Control chart
  • Sequential analysis
  • Spc

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