MVN: Multivariate Normality Tests

A comprehensive suite for assessing multivariate normality using six statistical tests (Mardia, Henze–Zirkler, Henze–Wagner, Royston, Doornik–Hansen, Energy). Also includes univariate diagnostics, bivariate density visualization, robust outlier detection, power transformations (e.g., Box–Cox, Yeo–Johnson), and imputation strategies ("mean", "median", "mice") for handling missing data. Bootstrap resampling is supported for selected tests to improve p-value accuracy in small samples. Diagnostic plots are available via both 'ggplot2' and interactive 'plotly' visualizations. See Korkmaz et al. (2014) <https://journal.r-project.org/archive/2014-2/korkmaz-goksuluk-zararsiz.pdf>.

Version:	6.1
Imports:	methods, nortest, moments, MASS, boot, car, dplyr, tidyr, purrr, stringr, tibble, ggplot2, viridis, cli, energy, plotly, mice
Published:	2025-06-10
DOI:	10.32614/CRAN.package.MVN
Author:	Selcuk Korkmaz [aut, cre], Dincer Goksuluk [aut], Gokmen Zararsiz [aut]
Maintainer:	Selcuk Korkmaz <selcukorkmaz at gmail.com>
BugReports:	https://github.com/selcukorkmaz/MVN/issues
License:	MIT + file LICENSE
URL:	https://selcukorkmaz.github.io/mvn-tutorial/, https://github.com/selcukorkmaz/MVN, http://biosoft.erciyes.edu.tr/app/MVN
NeedsCompilation:	no
Citation:	MVN citation info
Materials:	README
CRAN checks:	MVN results

Documentation:

Reference manual:

MVN.pdf

Downloads:

Package source:	MVN_6.1.tar.gz
Windows binaries:	r-devel: MVN_6.1.zip, r-release: MVN_6.1.zip, r-oldrel: MVN_6.1.zip
macOS binaries:	r-release (arm64): MVN_6.1.tgz, r-oldrel (arm64): MVN_6.1.tgz, r-release (x86_64): MVN_6.0.tgz, r-oldrel (x86_64): MVN_6.0.tgz
Old sources:	MVN archive

Reverse dependencies:

Reverse imports:	DFA.CANCOR, KarsTS, RSP, stats4teaching
Reverse suggests:	micompr

Linking:

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