A nonparametric test of serial independence for time series and residuals

被引：47

作者：

Ghoudi, K ^{[1
]}

Kulperger, RJ

Rémillard, B

机构：

[1] Univ Quebec, Trois Rivieres, PQ GA9 5H7, Canada

[2] Univ Western Ontario, London, ON, Canada

来源：

JOURNAL OF MULTIVARIATE ANALYSIS | 2001年 / 79卷 / 02期

基金：

加拿大自然科学与工程研究理事会;

关键词：

independence; serial independence; empirical processes; pseudo-observations; residuals; weak convergence; Cramer-von Mises statistics;

D O I：

10.1006/jmva.2000.1967

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

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. (C) 2001 Academic Press.

引用

页码：191 / 218

页数：28

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Abramowitz M., 1964, HDB MATH FUNCTIONS

[2]

[Anonymous], 1991, APPL MULTIVARIATE DA

[3] On Kendall's process [J].