The R Journal: article published in 2014, volume 6:2

MVN: An R Package for Assessing Multivariate Normality
Selcuk Korkmaz, Dincer Goksuluk and Gokmen Zararsiz , The R Journal (2014) 6:2, pages 151-162.

Abstract Assessing the assumption of multivariate normality is required by many parametric mul tivariate statistical methods, such as MANOVA, linear discriminant analysis, principal component analysis, canonical correlation, etc. It is important to assess multivariate normality in order to proceed with such statistical methods. There are many analytical methods proposed for checking multivariate normality. However, deciding which method to use is a challenging process, since each method may give different results under certain conditions. Hence, we may say that there is no best method, which is valid under any condition, for normality checking. In addition to numerical results, it is very useful to use graphical methods to decide on multivariate normality. Combining the numerical results from several methods with graphical approaches can be useful and provide more reliable decisions. Here, we present an R package, MVN, to assess multivariate normality. It contains the three most widely used multivariate normality tests, including Mardia’s, Henze-Zirkler’s and Royston’s, and graphical approaches, including chi-square Q-Q, perspective and contour plots. It also includes two multivariate outlier detection methods, which are based on robust Mahalanobis distances. Moreover, this package offers functions to check the univariate normality of marginal distributions through both tests and plots. Furthermore, especially for non-R users, we provide a user-friendly web application of the package. This application is available at http://www.biosoft.hacettepe.edu.tr/MVN/.

Received: 2014-06-10; online 2015-01-04
CRAN packages: MASS, FactoMineR, psych, CCA, MVN, shiny
CRAN Task Views implied by cited CRAN packages: Psychometrics, Multivariate, Distributions, Econometrics, Environmetrics, NumericalMathematics, Pharmacokinetics, Robust, SocialSciences, WebTechnologies

This article is licensed under a Creative Commons Attribution 3.0 Unported license .

@article{RJ-2014-031,
  author = {Selcuk Korkmaz and Dincer Goksuluk and Gokmen Zararsiz},
  title = {{MVN: An R Package for Assessing Multivariate Normality}},
  year = {2014},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2014-031},
  url = {https://doi.org/10.32614/RJ-2014-031},
  pages = {151--162},
  volume = {6},
  number = {2}
}