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)