Package 'mvnormtest'

Shapiro-Wilk Multivariate Normality Test

Description

Performs the Shapiro-Wilk test for multivariate normality.

Usage

mshapiro.test(U)

Arguments

U	a numeric matrix of data values, the number of which must be for each sample between 3 and 5000.

Value

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

statistic	the value of the Shapiro-Wilk statistic.
p.value	the p-value for the test.
method	the character string "Shapiro-Wilk normality test".
data.name	a character string giving the name(s) of the data.

Author(s)

Slawomir Jarek ([email protected])

References

Czeslaw Domanski (1998) Wlasnosci testu wielowymiarowej normalnosci Shapiro-Wilka i jego zastosowanie. Cracow University of Economics Rector's Lectures, No. 37.

Patrick Royston (1982) An Extension of Shapiro and Wilk's $W$ Test for Normality to Large Samples. Applied Statistics, 31, 115–124.

Patrick Royston (1982) Algorithm AS 181: The $W$ Test for Normality. Applied Statistics, 31, 176–180.

Patrick Royston (1995) A Remark on Algorithm AS 181: The $W$ Test for Normality. Applied Statistics, 44, 547–551.

See Also

shapiro.test for univariate samples, qqnorm for producing a normal quantile-quantile plot.

Examples

library(mvnormtest)
data(EuStockMarkets)

C <- t(EuStockMarkets[15:29,1:4])
mshapiro.test(C)

C <- t(EuStockMarkets[14:29,1:4])
mshapiro.test(C)

R <- t(diff(t(log(C))))
mshapiro.test(R)

dR <- t(diff(t(R)))
mshapiro.test(dR)

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