A nonparametric test of serial independence for time series and residuals

Kilani Ghoudi; Reg J. Kulperger; Bruno Rémillard

doi:10.1006/jmva.2000.1967

A nonparametric test of serial independence for time series and residuals

Kilani Ghoudi, Reg J. Kulperger, Bruno Rémillard

Research output: Contribution to journal › Article › peer-review

43 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 language	English
Article number	91967
Pages (from-to)	191-218
Number of pages	28
Journal	Journal of Multivariate Analysis
Volume	79
Issue number	2
DOIs	https://doi.org/10.1006/jmva.2000.1967
Publication status	Published - 2001
Externally published	Yes

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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10.1006/jmva.2000.1967

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title = "A nonparametric test of serial independence for time series and residuals",

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.",

keywords = "Cram{\'e}r-von Mises tatistics, Empirical processes, Independence, Pseudo-observations, Residuals, Serial independence, Weak convergence",

author = "Kilani Ghoudi and Kulperger, {Reg J.} and Bruno R{\'e}millard",

note = "Funding Information: The authors are supported in part by the Fonds Institutionnel de Recherche, Universite du Quebec a Trois-Rivieres, the Fonds pour la formation de chercheurs et l{\textquoteright}aide a la recherche du Gouvernement du Quebec, and by the Natural Sciences and Engineering Research Council of Canada, Grants OGP0184065, OGP0005724, and OGP0042137.",

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AU - Ghoudi, Kilani

AU - Kulperger, Reg J.

AU - Rémillard, Bruno

N1 - Funding Information: The authors are supported in part by the Fonds Institutionnel de Recherche, Universite du Quebec a Trois-Rivieres, the Fonds pour la formation de chercheurs et l’aide a la recherche du Gouvernement du Quebec, and by the Natural Sciences and Engineering Research Council of Canada, Grants OGP0184065, OGP0005724, and OGP0042137.

PY - 2001

Y1 - 2001

N2 - 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.

AB - 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.

KW - Cramér-von Mises tatistics

KW - Empirical processes

KW - Independence

KW - Pseudo-observations

KW - Residuals

KW - Serial independence

KW - Weak convergence

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M1 - 91967

ER -

A nonparametric test of serial independence for time series and residuals

Abstract

Keywords

ASJC Scopus subject areas

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