Description Usage Arguments Value Author(s) References See Also Examples
View source: R/mshapiro.test.R
Performs the Shapiro-Wilk test for multivariate normality.
1 |
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 |
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.
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)
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