Linear discriminant analysis

Hi.
I have successfully performed the discriminant analysis with the lda
function, I can classify new individuals with the predict function, but I
cannot figure out how the lda results translate into the classification
decision. That is, I don't realize how the classification equation for new
individuals is constructed from the lda output. I want to understand it but
also, I need to communicate it and provide a mechanism for other colleagues
to make classifications with their data.
Thank you very much,
Fernando

Do you want to know the principles of the theory behind LDA? That is 
available in lots of textbooks.

Do you want the implementation detials of MASS::lda()?
That is hard. It is based (but does not follow in all details) on a 
paper by Nils Hjort from Norway.
A former student of mine, Swetlana Herbrandt, has analysed and reverse 
engineered the code and wrote down the theory in a German thesis. The 
implementation uses some nice tricks to get numerically rather stable 
results that are typically not mentioned in any textbook.

Do you really want to do prediction with LDA?
I typically look at classificatuion performance of LDA as a reference to 
compare better and more modern techniques with.

I think you should ask some trained local statistician for advise on 
both, the LDA theory and for prediction in general.

Best,
Uwe Ligges