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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