varmx: Rotate a Matrix of Component Loadings using the VARIMAX Criterion
Description
The matrix being rotated contains the values of the component
functional data objects computed in either a principal
components analysis or a canonical correlation analysis.
The values are computed over a fine mesh of argument values.
Usage
varmx(amat)
Arguments
amat
the matrix to be rotated. The number of rows is
equal to the number of argument values nx used
in a fine mesh. The number of columns is the number of
components to be rotated.
Value
a square rotation matrix of order equal to the number
of components that are rotated. A rotation matrix
$T$ has that property that $T'T = TT' = I$.
Details
The VARIMAX criterion is the variance of the squared component values.
As this criterion is maximized with respect to a rotation of the
space spanned by the columns of the matrix, the squared loadings
tend more and more to be either near 0 or near 1, and this tends to
help with the process of labelling or interpreting the rotated matrix.