orthomax(amat, gamma=1, normalize=T, iter.max=100, eps=1e-05)
p by
k orthogonal matrix with p < k.
gamma are:
varimax (1), quartimax (0), and equamax (
k/2).
Generally positive values (not larger than about
5*k) are used for
gamma,
but negative values are possible.
TRUE,
Kaiser normalization is performed. In Kaiser normalization
(Kaiser, 1958), the criterion is adjusted so that the rows
in
amat are adjusted to an L-2 norm of 1.
eps from one iteration
to the next, convergence is assumed.
amat.
gamma used.
normalize.
rmat up to numerical precision.
TRUE.
This computes rotations for the orthomax family of rotations by
performing rotations on pairs of columns.
The criterion that is being minimized is:
sum(lam^2) - gamma/p * sum(apply(lam, 1, sum)^2)
where
lam is the (possibly) normalized version of the
rmat output
with all elements squared.
Harman, H. H. (1976).
Modern Factor Analysis,
3rd Edition.
University of Chicago Press, Chicago.
Kaiser, H. F. (1958). The varimax criterion for analytic rotation in
factor analysis.
Psychometrika
23 187-200.
prim9.pcl <- princomp(prim9)$loadings orthomax(prim9.pcl[,1:4], gamma=3)