A nonparametric test of serial independence for time series and residuals

Kilani Ghoudi, Reg J. Kulperger, Bruno Rémillard

Research output: Contribution to journalArticlepeer-review

38 Citations (Scopus)

Abstract

This paper presents nonparametric tests of independence that can be used to test the independence of p random variables, serial independence for time series, or residuals data. These tests are shown to generalize the classical portmanteau statistics. Applications to both time series and regression residuals are discussed.

Original languageEnglish
Article number91967
Pages (from-to)191-218
Number of pages28
JournalJournal of Multivariate Analysis
Volume79
Issue number2
DOIs
Publication statusPublished - 2001
Externally publishedYes

Keywords

  • Cramér-von Mises tatistics
  • Empirical processes
  • Independence
  • Pseudo-observations
  • Residuals
  • Serial independence
  • Weak convergence

ASJC Scopus subject areas

  • Statistics and Probability
  • Numerical Analysis
  • Statistics, Probability and Uncertainty

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