Compute the canonical correlations between two data matrices.
cancor(x, y, xcenter = TRUE, ycenter = TRUE)
numeric matrix (\(n \times p_1\)), containing the x coordinates.
numeric matrix (\(n \times p_2\)), containing the y coordinates.
logical or numeric vector of length \(p_1\),
describing any centering to be done on the x values before the
analysis. If TRUE
(default), subtract the column means.
If FALSE
, do not adjust the columns. Otherwise, a vector
of values to be subtracted from the columns.
analogous to xcenter
, but for the y values.
A list containing the following components:
correlations.
estimated coefficients for the x
variables.
estimated coefficients for the y
variables.
the values used to adjust the x
variables.
the values used to adjust the x
variables.
The canonical correlation analysis seeks linear combinations of the
y
variables which are well explained by linear combinations
of the x
variables. The relationship is symmetric as
‘well explained’ is measured by correlations.
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
Hotelling H. (1936). Relations between two sets of variables. Biometrika, 28, 321--327.
Seber, G. A. F. (1984). Multivariate Observations. New York: Wiley, p.506f.