Abstract
In this chapter we compare and contrast three approaches for testing multivariate normality. These are, namely, Mardia’s skewness and kurtosis statistics and the Henze–Zirkler statistic. Type I errors and power are demonstrated using simulations in both the complete-data and the randomly-incomplete-data cases. In the randomly-incomplete-data case, we use Sidak’s method for multiple testing. Examples are also provided.
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Desai, T. (2013). On Testing for Multivariate Normality. In: A Multiple-Testing Approach to the Multivariate Behrens-Fisher Problem. SpringerBriefs in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6443-3_2
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DOI: https://doi.org/10.1007/978-1-4614-6443-3_2
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