Canonical correlation analysis
canocor performs canonical correlation analysis on the
basis of the standardized variables and stores extensive output
in a list object.
canocor(X, Y)
X |
a matrix containing the X variables |
Y |
a matrix containing the Y variables |
canocor computes the solution by a singular value
decomposition of the transformed between set correlation matrix.
Returns a list with the following results
ccor |
the canonical correlations |
A |
canonical weights of the x variables |
B |
canonical weights of the y variables |
U |
canonical x variates |
V |
canonical y variates |
Fs |
biplot markers for x variables (standard coordinates) |
Gs |
biplot markers for y variables (standard coordinates) |
Fp |
biplot markers for x variables (principal coordinates) |
Gp |
biplot markers for y variables (principal coordinates) |
fitRxy |
goodness of fit of the between-set correlation matrix |
fitXs |
adequacy coefficients of x variables |
fitXp |
redundancy coefficients of x variables |
fitYs |
adequacy coefficients of y variables |
fitYp |
redundancy coefficients of y variables |
Jan Graffelman jan.graffelman@upc.edu
Hotelling, H. (1935) The most predictable criterion. Journal of Educational Psychology (26) pp. 139-142.
Hotelling, H. (1936) Relations between two sets of variates. Biometrika (28) pp. 321-377.
Johnson, R. A. and Wichern, D. W. (2002) Applied Multivariate Statistical Analysis. New Jersey: Prentice Hall.
set.seed(123) X <- matrix(runif(75),ncol=3) Y <- matrix(runif(75),ncol=3) cca.results <- canocor(X,Y)
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