mvnormalTest: Powerful Tests for Multivariate Normality

A simple informative powerful test (mvnTest()) for multivariate normality proposed by Zhou and Shao (2014) <doi:10.1080/02664763.2013.839637>, which combines kurtosis with Shapiro-Wilk test that is easy for biomedical researchers to understand and easy to implement in all dimensions. This package also contains some other multivariate normality tests including Fattorini's FA test (faTest()), Mardia's skewness and kurtosis test (mardia()), Henze-Zirkler's test (mhz()), Bowman and Shenton's test (msk()), Royston’s H test (msw()), and Villasenor-Alva and Gonzalez-Estrada's test (msw()). Empirical power calculation functions for these tests are also provided. In addition, this package includes some functions to generate several types of multivariate distributions mentioned in Zhou and Shao (2014).

Getting started

Package details

AuthorYian Zhang [aut, cre], Ming Zhou [aut], Yongzhao Shao [aut]
MaintainerYian Zhang <>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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mvnormalTest documentation built on April 28, 2020, 5:06 p.m.