Description Usage Arguments Details Value Author(s) References See Also Examples
Given a d-dimensional random sample of size n, this function computes the test statistic and p-value of the Shapiro-Wilk test for multivariate normality proposed by Villasenor-Alva and Gonzalez-Estrada (2009).
1 |
X |
Numeric data matrix with d columns (vector dimension) and n rows (sample size). |
n must be larger than d.
When d=1, mvShapiro.Test(X)
produces the same results as shapiro.test(X)
.
A list with class "htest"
containing the following components.
statistic |
the value of the generalized Shapiro-Wilk statistic for testing multivariate normality. |
p.value |
the p-value of the test. |
method |
the character string "Generalized Shapiro-Wilk test for multivariate normality". |
data.name |
a character string giving the name of the data set. |
Elizabeth Gonzalez-Estrada egonzalez@colpos.mx, Jose A. Villasenor-Alva
Villasenor-Alva, J.A. and Gonzalez-Estrada, E. (2009). A generalization of Shapiro-Wilk's test for multivariate normality. Communications in Statistics: Theory and Methods,38 11,1870-1883.
1 2 3 4 5 6 7 8 9 | X <- matrix(rnorm(40),ncol=2) # Generating a two dimensional random sample of size 20
mvShapiro.Test(X) # Testing multivariate normality on X
#-----------------------------------------------------------------------------------
# iris.virginica contains a set of measurements corresponding to
# Iris virginica of the famous iris dataset.
iris.virginica <- as.matrix(iris[iris$Species == "virginica",1:4],ncol=4)
mvShapiro.Test(iris.virginica) # Testing multivariate normality on iris.virginica
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