Canonical Redundancy Analysis
Calculates indices of redundancy (Stewart & Love, 1968) from a canonical correlation analysis. These give the proportion of variances of the variables in each set (X and Y) which are accounted for by the variables in the other set through the canonical variates.
redundancy(object, ...)
## S3 method for class 'cancor.redundancy'
print(x, digits = max(getOption("digits") - 3, 3), ...)object |
A |
x |
A |
digits |
Number of digits to print |
... |
Other arguments |
None yet.
An object of class "cancor.redundancy", a list with the following 5 components:
Xcan.redun |
Canonical redundancies for the X variables, i.e., the total fraction of X variance accounted for by the Y variables through each canonical variate. |
Ycan.redun |
Canonical redundancies for the Y variables |
X.redun |
Total canonical redundancy for the X variables, i.e., the sum of
|
Y.redun |
Total canonical redundancy for the Y variables |
set.names |
names for the X and Y sets of variables |
Michael Friendly
Stewart, D. and Love, W. (1968). A general canonical correlation index. Psychological Bulletin, 70, 160-163.
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"))
redundancy(cc)
##
## Redundancies for the PA variables & total X canonical redundancy
##
## Xcan1 Xcan2 Xcan3 total X|Y
## 0.17342 0.04211 0.00797 0.22350
##
## Redundancies for the Ability variables & total Y canonical redundancy
##
## Ycan1 Ycan2 Ycan3 total Y|X
## 0.2249 0.0369 0.0156 0.2774Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.