mshapiro.test {mvnormtest} | R Documentation |
Performs the Shapiro-Wilk test for multivariate normality.
mshapiro.test(U)
U |
a numeric matrix of data values, the number of which must be for each sample between 3 and 5000. |
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. |
Slawomir Jarek (slawomir.jarek@gallus.edu.pl)
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.
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)