[R] memory problems for fixed effect models

[Jörg Schaber]

Hi,

I am trying to fit a simple two-way fixed effect linear model (o ~ y + s 
- 1). However, my problem is large (length(o)=79333).
I am already using slm.fit with a dense design matrix (ddm), but still:

fit <- slm.fit(ddm,o)
Error: cannot allocate vector of size 9.1 Gb

Is there a way to redefine the model or any other trick such that I do 
not run into these memory problems?

Running a mixed effect model, like
lme(o ~ y - 1 ,random = ~ 1 | s, method="REML", 
contrasts=list(s=("contr.sum")),na.action=na.exclude)
poses no problem, but I want to have both effects fixed.

Thanks,

joerg