mshapiro.test: Shapiro-Wilk Multivariate Normality Test. Source code from...

In lixiangchun/lxctk: Li Xiangchun's tool-kit (lxctk)

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 ([e-mail])

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)

lixiangchun/lxctk documentation built on May 21, 2019, 6:44 a.m.