Statistical inference of covariance change points in gaussian model

Jie Chen, A. K. Gupta

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

In this paper, we study the testing and estimation of multiple covariance change points for a sequence of m-dimensional (m > 1) Gaussian random vectors by using the Schwarz information criterion (SIC). The unbiased SIC is also obtained. The asymptotic null distribution of the test statistic is derived. The result is applied to a simulated bivariate normal vector sequence (m = 2), and changes are successfully detected.

Original languageEnglish (US)
Pages (from-to)17-28
Number of pages12
JournalStatistics
Volume38
Issue number1
DOIs
StatePublished - Feb 1 2004
Externally publishedYes

Keywords

  • Asymptotic distribution
  • Change-points
  • Information criterion
  • SIC

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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