R: Shapiro-Wilk Multivariate Normality Test

mshapiro.test {mvnormtest} | R Documentation

## 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 (slawomir.jarek@gallus.edu.pl)

### 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)

[Package mvnormtest version 0.1-9 Index]