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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>.
Getting started
Browse package contents
Package details |
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| Author | Selcuk Korkmaz [aut, cre] (ORCID: <https://orcid.org/0000-0003-4632-6850>), Dincer Goksuluk [aut], Gokmen Zararsiz [aut] |
| Maintainer | Selcuk Korkmaz <selcukorkmaz@gmail.com> |
| License | MIT + file LICENSE |
| Version | 6.1 |
| URL | https://selcukorkmaz.github.io/mvn-tutorial/ https://github.com/selcukorkmaz/MVN http://biosoft.erciyes.edu.tr/app/MVN |
| Package repository | View on CRAN |
| Installation |
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