R help - Feb 2006 - linear discriminant analysis in MASS

Hello R people

I now know how to run my discriminant analysis with the lda function in 
MASS:
lda.alain=lda(Groupes ~ Ht.D0 + Lc.Dc + Ram + IDF, gr, CV = FALSE)
and it works fine.

But I am missing a test and cannot find any help on how to get it, if it 
exist.

The "S" equivalent:
discrim(structure(.Data = Groupes ~ Ht.D0 + Lc.Dc + Ram + IDF, class = 
"formula"), data = gr, family = Canonical(cov.structure = 
"homoscedastic"), na.action = na.omit, prior =
"proportional")
outputs a nice matrix of Mahalanobis distances between groups and even 
tests (Hotelling's T Squared) for significant distances.

Why don't I just take the "S" output you say?  Because like you,
I'd
rather put in my paper that I did it using R of course!
Does anyone know of a way to get this test out of lda?  Or of another R 
package that does it?

Thanks
Alain
(on peut me r??pondre en fran??ais aussi, ??videmment!)

-- 
Alain Paquette
Laboratoire d'??cologie v??g??tale
Institut de recherche en biologie v??g??tale
Universit?? de Montr??al
4101 rue Sherbrooke Est
Montr??al (Qu??bec) H1X 2B2
 
alain.paquette at umontreal.ca
labo (514) 872-8488
fax (514) 872-9406
http://www.irbv.umontreal.ca/francais/personnel/cogliastro-paquette.htm

On Mon, 20 Feb 2006, Alain Paquette wrote:
> Hello R people
>
> I now know how to run my discriminant analysis with the lda function in
> MASS:
> lda.alain=lda(Groupes ~ Ht.D0 + Lc.Dc + Ram + IDF, gr, CV = FALSE)
> and it works fine.
CV=FALSE is the default and so not needed.
> But I am missing a test and cannot find any help on how to get it, if it
> exist.
>
> The "S" equivalent:
There is no such function in S, and I rather object as the S equivalent is 
lda() (and as the author of both I should know).  Credit where credit is 
due: discrim() is an S-PLUS function, indebted to lda().
> discrim(structure(.Data = Groupes ~ Ht.D0 + Lc.Dc + Ram + IDF, class >
"formula"), data = gr, family = Canonical(cov.structure >
"homoscedastic"), na.action = na.omit, prior =
"proportional")
> outputs a nice matrix of Mahalanobis distances between groups and even
> tests (Hotelling's T Squared) for significant distances.
Well, it seems not to.  That is part of the output of the summary() 
method, which itself calls the multicomp() method.
> Why don't I just take the "S" output you say?  Because like
you, I'd
> rather put in my paper that I did it using R of course!
No `of course' applies. If you learnt of this output from S-PLUS, I urge 
you to credit it honestly and accurately.  (If you refer to lda, you 
should credit that, not just R.)
> Does anyone know of a way to get this test out of lda?  Or of another R
> package that does it?
Mahalanobis distance between groups is easy, as this is just Euclidean 
distance between group centres in the scaled space.  The test statistics 
can be produced, but

- they are critically dependent on the unrealistic assumptions of 
multivariate normality and variance homogeneity and

- there needs to be an adjustment for multiple comparisons.

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595