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

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  • Yanagihara, Hirokazu

Abstract

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.

Suggested Citation

  • Yanagihara, Hirokazu, 2003. "Asymptotic expansion of the null distribution of test statistic for linear hypothesis in nonnormal linear model," Journal of Multivariate Analysis, Elsevier, vol. 84(2), pages 222-246, February.
    • Handle: RePEc:eee:jmvana:v:84:y:2003:i:2:p:222-246
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    References listed on IDEAS

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    1. Qumsiyeh, Maher B., 1990. "Edgeworth expansion in regression models," Journal of Multivariate Analysis, Elsevier, vol. 35(1), pages 86-101, October.
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    Cited by:

    1. Robert Boik, 2008. "Accurate confidence intervals in regression analyses of non-normal data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(1), pages 61-83, March.
    2. Yanagihara, Hirokazu, 2007. "A family of estimators for multivariate kurtosis in a nonnormal linear regression model," Journal of Multivariate Analysis, Elsevier, vol. 98(1), pages 1-29, January.
    3. Islam, Tanweer ul, 2008. "Normality Testing- A New Direction," MPRA Paper 16452, University Library of Munich, Germany.

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