[R] understanding LDA: normalization of the eigenvectors

[Christoph Lehmann]

Hi dear R-users

I try to reproduce the steps included in a LDA. In my textbook (Bortz)
it says, that the matrix with the eigenvectors 

V

usually are not normalized to the length of 1, but in the way that the
following holds (SPSS does the same thing):

t(Vstar)%*%Derror%*%Vstar = I


where Vstar are the normalized eigenvectors. Derror is an "error" or
"within" squaresum- and crossproduct matrix (squaresum of the p
variables on the diagonale, and the non-diagonal elements are the sum of
the crossproducts). For Derror the following holds: Dtotal = Dtreat +
Derror.

Since I assume that many of you are familiar with this transformation:
can anybody of you tell me, how to conduct this transformation in R?
Would be very nice. Thanks a lot

Cheers

Christoph

-- 
Christoph Lehmann <christoph.lehmann at gmx.ch>