Packaged: 2014-03-15 22:31:08 UTC; selcukorkmaz

Depends: R (>= 2.15.0), nortest, moments, MASS
Packaged: 2014-04-06 22:27:08 UTC; selcukorkmaz

Packaged: 2014-04-08 12:29:58 UTC; selcukorkmaz

Packaged: 2014-04-26 09:18:13 UTC; selcukorkmaz

Authors@R: c(person("Selcuk", "Korkmaz", role = c("aut", "cre"),
person("Dincer", "Goksuluk", role = "aut",
Author: Selcuk Korkmaz [aut, cre], Dincer Goksuluk [aut]
Depends: R (>= 2.15.0), nortest, moments, MASS, robustbase, mvoutlier
Collate: classes.R mardiaTest.R hzTest.R roystonTest.R mvOutlier.R
Description: Assessing the assumption of multivariate normality is required by many parametric multivariate statistical methods, such as discriminant analysis, principal component analysis, MANOVA, etc. Here, we present an R package to asses multivariate normality. The MVN package contains three widely used multivariate normality tests, including Mardia's, Henze-Zirkler's, Royston's, graphical approaches, including chi-square Q-Q plot, perspective plot and contour plot and two outlier detection methods based on Mahalanobis distance. We have also developed web-tool version of the package which is available at http://www.biosoft.hacettepe.edu.tr/MVN/.
Packaged: 2014-10-15 14:20:23 UTC; selcukorkmaz

person("Gokmen", "Zararsiz", role = "aut",
Author: Selcuk Korkmaz [aut, cre], Dincer Goksuluk [aut], Gokmen Zararsiz [aut]
Imports: methods, nortest, moments, MASS, robustbase, mvoutlier, plyr

Imports: methods, nortest, moments, MASS, robustbase, mvoutlier, plyr,
Description: Performs multivariate normality tests and graphical approaches and implements multivariate outlier detection and univariate normality of marginal distributions through plots and tests.

mvnPlot.R uniNorm.R uniPlot.R contourControl.R perspControl.R
Packaged: 2016-11-30 16:07:48 UTC; selcukorkmaz

Packaged: 2016-12-01 13:57:46 UTC; selcukorkmaz

Packaged: 2015-06-03 04:17:13 UTC; selcukorkmaz

psych, boot, energy, kableExtra, magrittr
Description: Performs multivariate normality tests and graphical approaches and
implements multivariate outlier detection and univariate normality of marginal
distributions through plots and tests (Korkmaz et al, (2014), <https://journal.r-project.org/archive/2014-2/korkmaz-goksuluk-zararsiz.pdf>).
Packaged: 2018-02-23 19:12:54 UTC; selcukkorkmaz