🚀 go-pugleaf

[S on NeXT; an April 1992 version; NeXTStep 3.0; 32MB RAM; ~40-80MB free disk]

I am having a serious problem with lm()'s use of disk space. I have a panel
data set with 1,109 observations and 37 variables, or about 164K in float
storage. One of these variables is a categorical factor, taking about 400
values (firm id's). A rough computation tells me that I would need a maximum
of 1MB (double) space to store one copy of the X'X matrix in full form.

> result <- lm(formula.complete, can, subset= (date<breakdate), singular.ok=TRUE)
Error in data[1:ll] <- old: Cannot allocate 39516128 bytes:
        options("object.size") is 20000000

Now this is a bit too much for my somewhat limited computer. (After I allow
more 40MB as object.size, I get a swapspace overflow.) How can lm() be so
voracious? Is there any way to tell it to be a bit more graceful about its
memory appetite? (I need to move to about 1,000 variables and 2,000 obs at
some point.) Obviously, rewriting lm() (for an S beginner like myself) is very
undesirable.

Please respond to me. I will summarize any helpful suggestions.

/ivo

PS: This is why I cannot do my problem in S. I will post a question on SAS,
where I also tried to solve my problem soon.