Package: mvnormalTest 1.0.0

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).

Authors:Yian Zhang [aut, cre], Ming Zhou [aut], Yongzhao Shao [aut]

mvnormalTest_1.0.0.tar.gz
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mvnormalTest_1.0.0.tgz(r-4.4-any)mvnormalTest_1.0.0.tgz(r-4.3-any)
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mvnormalTest.pdf |mvnormalTest.html
mvnormalTest/json (API)

# Install 'mvnormalTest' in R:
install.packages('mvnormalTest', repos = c('https://yz2777.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

19 exports 1 stars 0.09 score 13 dependencies 25 scripts 505 downloads

Last updated 4 years agofrom:1f468ff8b8. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 31 2024
R-4.5-winNOTEAug 31 2024
R-4.5-linuxNOTEAug 31 2024
R-4.4-winOKAug 31 2024
R-4.4-macOKAug 31 2024
R-4.3-winOKAug 31 2024
R-4.3-macOKAug 31 2024

Exports:copulasfaTestIMMVmardiamhzmskmswMVNMIXmvnTestpower.faTestpower.mhzpower.mskpower.mswRpower.mswVpower.mvnTestpower.uswPSIIPSVIISPH

Dependencies:ADGofTestcolorspacecopulagsllatticeMatrixmomentsmvtnormnortestnumDerivpcaPPpsplinestabledist