Tests in variance components models under skew-normal settings

Rendao Ye (), Tonghui Wang (), Saowanit Sukparungsee () and Arjun Gupta ()

Metrika: International Journal for Theoretical and Applied Statistics, 2015, vol. 78, issue 7, 885-904

Abstract: The hypothesis testing problems of unknown parameters for the variance components model with skew-normal random errors are discussed. Several properties of the model, such as the density function, moment generating function, and independence conditions, are obtained. A new version of Cochran’s theorem is given, which is used to establish exact tests for fixed effects and variance components of the model. For illustration, our main results are applied to two examples and a real data problem. Finally, some simulation results on the type I error probability and power of the proposed test are reported. And the simulation results indicate that the proposed test provides satisfactory performance on the type I error probability and power. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Variance components model; Moment generating function; Cochran’s theorem; Noncentral skew Chi-square distribution; Noncentral skew-F distribution (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s00184-015-0532-1

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