Prof Brian Ripley <[EMAIL PROTECTED]> writes: > > Hmm. Shouldn't be all that much faster, but it will produce the Type I > > SS as you go along, whereas R probably wants to fit the 15 different > > models. > > Nope, R can read off the Type I SSQs from the QR decomposition so only one > fit is done. (Effectively you remove the effect of one column at a time, > and you get the change in residual/regression SSq as a side effect. Take > a look at anova.lm, which just aggregates squared effects over terms.)
OK, thanks. > > I'm still surprised that R/S-PLUS manages to use a full 15 minutes on > > a single response variable. It might be due to the singularities -- > > the SAS code indicated that there was a nesting issue with the "A" > > factor in the last 4-factor interaction. If so, a reformulation of the > > model might help. > > I think we need to understand this better. My guess (but only a guess) is > that the model matrix has very many columns and is highly singular. If > the singularity is by design, a reformulation will help. It's certainly not a completely balanced factorial: 1344=2*2*2*2*2*2*3*7 so it could be one in several way, but not with a main effects with 4 DF. An even less well-founded guess is that it might help to replace the last term with interaction(Ar,Ba,Ti,Pr,drop=TRUE) (if I remembered the names correctly). -- O__ ---- Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics 2200 Cph. N (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ [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
