Wilks: Wilks Lambda Tests for Canonical Correlations
In candisc: Visualizing Generalized Canonical Discriminant and Canonical Correlation Analysis

Description Usage Arguments Details Value Author(s) References See Also Examples

Tests the sequential hypotheses that the ith canonical correlation and all that follow it are zero,

ρ_i = ρ_{i+1} = \cdots = 0

Wilks(object, ...)

## S3 method for class 'cancor'
Wilks(object, ...)
## S3 method for class 'candisc'
Wilks(object, ...)

`object`	An object of class `"cancor""} or \code{"candisc""`
`...`	Other arguments passed to methods (not used)

Wilks' Lambda values are calculated from the eigenvalues and converted to F statistics using Rao's approximation.

A data.frame (of class "anova") containing the test statistics

Michael Friendly

Mardia, K. V., Kent, J. T. and Bibby, J. M. (1979). Multivariate Analysis. London: Academic Press.

cancor, ~~~

data(Rohwer, package="heplots")
X <- as.matrix(Rohwer[,6:10])  # the PA tests
Y <- as.matrix(Rohwer[,3:5])   # the aptitude/ability variables

cc <- cancor(X, Y, set.names=c("PA", "Ability"))
Wilks(cc)

iris.mod <- lm(cbind(Petal.Length, Sepal.Length, Petal.Width, Sepal.Width) ~ Species, data=iris)
iris.can <- candisc(iris.mod, data=iris)
Wilks(iris.can)