Empirical likelihood ratio test for a change-point in linear regression model

Yukun Liu, Changliang Zou, Runchu Zhang

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

A nonparametric method based on the empirical likelihood is proposed to detect the change-point in the coefficient of linear regression models. The empirical likelihood ratio test statistic is proved to have the same asymptotic null distribution as that with classical parametric likelihood. Under some mild conditions, the maximum empirical likelihood change-point estimator is also shown to be consistent. The simulation results show the sensitivity and robustness of the proposed approach. The method is applied to some real datasets to illustrate the effectiveness.

Original languageEnglish
Pages (from-to)2551-2563
Number of pages13
JournalCommunications in Statistics - Theory and Methods
Volume37
Issue number16
DOIs
StatePublished - Jan 2008
Externally publishedYes

Keywords

  • Change-point
  • Empirical likelihood
  • Linear regression model
  • Maximum empirical likelihood estimator
  • Nonparametric
  • Robustness

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