The canonCommonality function produces commonality data
for a given canonical variable set. Using the variables in a
given canonical set to partition the variance of the canonical
variates produced from the other canonical set,
commonality data is supplied for the number of canonical
functions requested.
canonVariate(A, B, nofns)Matrix containing variable set A
Matrix containing variable set B
Number of canonical functions to analyze
The function canonVariate returns commonality data for
the canonical variable set input. For the number of functions
requested, two tables are returned. The first table lists the
commonality coefficients for each canonical function together
with its contribution to the total effect, while the second
table lists the unique and common effects for each regressor.
For each canonical function, canonVariate: (a) creates
a dataset that combines the matrix of variables for a given
canonical set and the canonicate variate for the other
canonical set; (b) calls commonalityCoefficients,
passing the dataset, the name of the canonical variate, and
the names of the variates in a given canonical set; (c) saves
resultant output.
Nimon, K., Henson, R., & Gates, M. (2010). Revisiting interpretation of canonical correlation analysis: A tutorial and demonstration of canonical commonality analysis. Multivariate Behavioral Research, 45,702-724.