Package: mvnormalTest 1.0.1

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_1.0.1.tar.gz
mvnormalTest_1.0.1.zip(r-4.7-any)mvnormalTest_1.0.1.zip(r-4.6-any)mvnormalTest_1.0.1.zip(r-4.5-any)
mvnormalTest_1.0.1.tgz(r-4.6-any)mvnormalTest_1.0.1.tgz(r-4.5-any)
mvnormalTest_1.0.1.tar.gz(r-4.7-any)mvnormalTest_1.0.1.tar.gz(r-4.6-any)
mvnormalTest_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
mvnormalTest/json (API)

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

On CRAN:

Conda:

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

2.08 score 1 stars 1 packages 40 scripts 556 downloads 19 exports 14 dependencies

Last updated from:87155675ca. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK144
source / vignettesOK150
linux-releaseOK140
macos-releaseOK211
macos-oldrelOK171
windows-develOK109
windows-releaseOK105
windows-oldrelOK96
wasm-releaseOK84

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

Dependencies:ADGofTestclustercolorspacecopulagsllatticeMatrixmomentsmvtnormnortestnumDerivpcaPPpsplinestabledist