Asymptotic expansion of the null distribution of test statistic for linear hypothesis in nonnormal linear model
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.
Year of publication: |
2003
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Authors: | Yanagihara, Hirokazu |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 84.2003, 2, p. 222-246
|
Publisher: |
Elsevier |
Keywords: | Analysis of variance Asymptotic expansion Cornish-Fisher expansion Linear hypothesis Linear model Nonnormality Null distribution One-way ANOVA test Two-way ANOVA test |
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