I don't think this is `discriminant analysis' as used in English (the French translation has a wider meaning). I suggest you start with multinom (in package nnet, part of the standard R distribution) which does fit a log-linear model, and rpart (in package rpart) as a classification tree is often useful to select variables in this sort of problem (and with 49 explanatory variables you are presumably hoping that only a few are needed).
On Fri, 23 Jul 2004, Pierre.Olivier.Mazagol wrote: > Hello. > I have a data base with 50 qualitative variables and a lot of > individuals. I try to estimate the links between one of these variables > (landcover) and the 49 others (geomorphology, hydrography...). I want to > use a "discriminant analysis on qualitative variables" (as DISQUAL in > SPAD) or a " log-linear model ". Which R-Package(s) or other methods can > you advise me. -- Brian D. Ripley, [EMAIL PROTECTED] 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 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
