# 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

 `1` ```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.

`shapiro.test` for univariate samples, `qqnorm` for producing a normal quantile-quantile plot.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14``` ```##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) ```