Package 'mvShapiroTest'

Generalized Shapiro-Wilk test for multivariate normality

Description

Given a d-dimensional random sample of size n, this function computes the test statistic and p-value of the Shapiro-Wilk test for multivariate normality proposed by Villasenor-Alva and Gonzalez-Estrada (2009).

Usage

mvShapiro.Test(X)

Arguments

X	Numeric data matrix with d columns (vector dimension) and n rows (sample size).

Details

n must be larger than d.

When d=1, mvShapiro.Test(X) produces the same results as shapiro.test(X).

Value

A list with class "htest" containing the following components.

statistic	the value of the generalized Shapiro-Wilk statistic for testing multivariate normality.
p.value	the p-value of the test.
method	the character string "Generalized Shapiro-Wilk test for multivariate normality".
data.name	a character string giving the name of the data set.

Author(s)

Elizabeth Gonzalez-Estrada [email protected], Jose A. Villasenor-Alva

References

Villasenor-Alva, J.A. and Gonzalez-Estrada, E. (2009). A generalization of Shapiro-Wilk's test for multivariate normality. Communications in Statistics: Theory and Methods,38 11,1870-1883.

See Also

shapiro.test

Examples

X <-  matrix(rnorm(40),ncol=2)    # Generating a two dimensional random sample of size 20
mvShapiro.Test(X)                 # Testing multivariate normality on X

#-----------------------------------------------------------------------------------
# iris.virginica contains a set of measurements corresponding to 
# Iris virginica of the famous  iris dataset.

iris.virginica <- as.matrix(iris[iris$Species == "virginica",1:4],ncol=4) 
mvShapiro.Test(iris.virginica)    # Testing multivariate normality on iris.virginica

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