mvnTest (version 1.1-0)

CM.test: Cramer-von Mises test for Multivariate Normality

Description

This function implements the Cramer-von Mises test for assessing multivariate normality.

Usage

CM.test(data, qqplot = FALSE)

Arguments

data

A numeric matrix or data frame

qqplot

if TRUE creates a chi-square Q-Q plot

Value

CM

the value of the test statistic

p.value

the p-value of the test

data.name

a character string giving the name of the data

Details

Calculates the value of the Cramer-von Mises test and the approximate p-value.

References

Koziol, J. (1982). A class of invariant procedures for assessing multivariate normality. Biometrika, 69, 423-427

Henze, N. and Zirkler, B. (1990). A class of invariant consistent tests for multivariate normality. Communications in Statistics - Theory and Methods, 19, 3595-3617

See Also

S2.test, AD.test, DH.test, R.test, HZ.test

Examples

## Not run: 
# ## generating n bivariate normal random variables...       
# dat <- rmvnorm(n=100,mean=rep(0,2),sigma=matrix(c(4,2,2,4),2,2)) 
# res <- CM.test(dat)
# res
# 
# ## generating n bivariate t distributed with 10df random variables...       
# dat <- rmvt(n=200,sigma=matrix(c(4,2,2,4),2,2),df=10,delta=rep(0,2)) 
# res1 <- CM.test(dat)
# res1
# 
# data(iris)
# setosa <- iris[1:50, 1:4] # Iris data only for setosa
# res2 <- CM.test(setosa, qqplot = TRUE)
# res2
# ## End(Not run)