Asymptotic expansion of the null distribution of test statistic for linear hypothesis in nonnormal linear model

被引:6
作者
Yanagihara, H [1 ]
机构
[1] Inst Stat Math, Div Multidimens Anal, Dept Stat Methodol, Minato Ku, Tokyo 1068569, Japan
关键词
analysis of variance; asymptotic expansion; Cornish-Fisher expansion; linear hypothesis; linear model; normormality; null distribution; one-way ANOVA test; two-way ANOVA test;
D O I
10.1016/S0047-259X(02)00049-0
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 is concerned with the null distribution of test statistic T for testing a linear hypothesis in a linear model without assuming normal errors. The test statistic includes typical ANOVA test statistics. It is known that the null distribution of T converges to chi(2) when the sample size n is large under an adequate condition of the design matrix. We extend this result by obtaining an asymptotic expansion under general condition. Next, asymptotic expansions of one- and two-way test statistics are obtained by using this general one. Numerical accuracies are studied for some approximations of percent points and actual test sizes of T for two-way ANOVA test case based on the limiting distribution and an asymptotic expansion. (C) 2003 Elsevier Science (USA). All rights reserved.
引用
收藏
页码:222 / 246
页数:25
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