--- Deepayan Sarkar <[EMAIL PROTECTED]> wrote: > On Thursday 16 October 2003 17:59, Alexander > Sirotkin \[at Yahoo\] wrote: > > Thanks for all the help on my previous questions. > > > > One more (hopefully last one) : I've been very > > surprised when I tried to fit a model (using > aov()) > > for a sample of size 200 and 10 variables and > their > > interactions. > > That doesn't really say much. How many of these > variables are factors ? How > many levels do they have ? And what is the order of > the interaction ? (Note > that for 10 numeric variables, if you allow all > interactions, then there will > be a 100 terms in your model. This increases for > factors.) > > In other words, how big is your model matrix ? (See > ?model.matrix) > > Deepayan >
I see... Unfortunately, model.matrix() ran out of memory :) I have 10 variables, 6 of which are factor, 2 of which have quite a lot of levels (about 40). And I would like to allow all interactions. I understand your point about categorical variables, but still - this does not seem like too much data to me. I remmeber fitting all kinds of models (mostly decision trees) for much, much larger data sets. ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
