Dear colleagues,

This is to inform you that Version 1.0 of the R package MVN has been released on CRAN yesterday. This package contain several multivariate normality tests such as Henze-Zirkler, Mardia and Royston. 
HZ.test: The Henze-Zirkler (HZ) test is based on a non-negative functional distance that measures the distance between two distribution functions. If the data is multivariate normality, the test statistic HZ is approximately lognormally distributed. It proceeds to calculate the mean, variance and smoothness parameter. Then, mean and variance are lognormalized and the p-value is estimated. The HZ.test function have two options for calculating covariance: population (covariance matrix normalized by n) and sample (covariance matrix normalized by n-1). It also draws a chi-square Q-Q plot.mardia.test: Calculates the Mardia's multivariate skewness and kurtosis coefficients as well as their corresponding statistical tests. For large sample size the multivariate skewness is asymptotically distributed as a Chi-square random variable; here it is corrected for small sample size. Likewise, the multivariate kurtosis it is distributed as a unit-normal. The mardia.test function have two options for calculating covariance: population (covariance matrix normalized by n) and sample (covariance matrix normalized by n-1). It also draws a chi-square Q-Q plot.royston.test: A function to generate the Shapiro-Wilk's W statistic needed to feed the Royston's H test for multivariate normality However, if kurtosis of the data greater than 3 then Shapiro-Francia test is used for leptokurtic samples else Shapiro-Wilk test is used for platykurtic samples. The royston.test function also draws a chi-square Q-Q plot.
For more details, see the following URL:
http://cran.r-project.org/web/packages/MVN/index.html

Res. Assist. Selçuk KorkmazHacettepe University Faculty of Medicine Department of Biostatistics 
Sıhhiye, Ankara. 		 	   		   		 	   		  
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