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/.
MASS, FactoMineR, psych, CCA, MVN, shiny
Psychometrics, Multivariate, Distributions, Econometrics, Environmetrics, NumericalMathematics, Pharmacokinetics, Robust, SocialSciences, WebTechnologies
Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".
For attribution, please cite this work as
Korkmaz, et al., "MVN: An R Package for Assessing Multivariate Normality", The R Journal, 2015
BibTeX citation
@article{RJ-2014-031,
author = {Korkmaz, Selcuk and Goksuluk, Dincer and Zararsiz, Gokmen},
title = {MVN: An R Package for Assessing Multivariate Normality},
journal = {The R Journal},
year = {2015},
note = {https://doi.org/10.32614/RJ-2014-031},
doi = {10.32614/RJ-2014-031},
volume = {6},
issue = {2},
issn = {2073-4859},
pages = {151-162}
}