Third-order power comparisons for a class of tests for multivariate linear hypothesis under general distributions

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Abstract

The purpose of this paper is, in multivariate linear regression model (Part I) and GMANOVA model (Part II), to investigate the effect of nonnormality upon the nonnull distributions of some multivariate test statistics under normality. It is shown that whatever the underlying distributions, the difference of local powers up to order N- 1after either Bartlett's type adjustment or Cornish-Fisher's type size adjustment under nonnormality coincides with that in Anderson [An Introduction to Multivariate Statistical Analysis, 2nd ed. and 3rd ed., Wiley, New York, 1984, 2003] under normality. The derivation of asymptotic expansions is based on the differential operator associated with the multivariate linear regression model under general distributions. The performance of higher-order results in finite samples, including monotone Bartlett's type adjustment and monotone Cornish-Fisher's type size adjustment, is examined using simulation studies. © 2008 Elsevier Inc. All rights reserved.

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APA

Kakizawa, Y. (2009). Third-order power comparisons for a class of tests for multivariate linear hypothesis under general distributions. Journal of Multivariate Analysis, 100(3), 473–496. https://doi.org/10.1016/j.jmva.2008.06.002

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