Once again: Error: cannot allocate vector of size

Hi,

I have browsed the help list and looked at the FAQ but I don't find 
conclusive evidence if this is normal or I am doing something wrong.
I am running a lm() on a data.frame with 27136 observations of 6 variables 
(3 num and 3 factor).
After a while R throws this:

lm(log(y) ~ log(a) + log(b) + c + d + e, data=reg.data , 
na.action=na.exclude)

Error: cannot allocate vector of size 203.7 MB

This is a Windows XP 32 bit machine with 4 GB in it so that theoretically, 
R should be able to claim close to 2 GB.
This is the gc() after the regression:
         used (Mb) gc trigger  (Mb)  max used   (Mb)
Ncells  272299  7.3     875833  23.4   1368491   36.6
Vcells 4526037 34.6  116536251 889.2 145524997 1110.3

memory.size(max=T)

[1] 1230.25

memory.size(max=F)

[1] 47.89

Looking at memory.size, R should be easily able to allocate that space, 
shouldn't it?

Many thanks for any hints!

--Werner

Hi,

I have browsed the help list and looked at the FAQ but I don't find conclusive evidence if this is normal or I am doing something wrong.
I am running a lm() on a data.frame with 27136 observations of 6 variables (3 num and 3 factor).
After a while R throws this:

lm(log(y) ~ log(a) + log(b) + c + d + e, data=reg.data , na.action=na.exclude)

Error: cannot allocate vector of size 203.7 MB

This is a Windows XP 32 bit machine with 4 GB in it so that theoretically, R should be able to claim close to 2 GB.
This is the gc() after the regression:
? ? ? ? ?used (Mb) gc trigger ?(Mb) ?max used ? (Mb)
Ncells ?272299 ?7.3 ? ? 875833 ?23.4 ? 1368491 ? 36.6
Vcells 4526037 34.6 ?116536251 889.2 145524997 1110.3

memory.size(max=T)

[1] 1230.25

memory.size(max=F)

[1] 47.89

Looking at memory.size, R should be easily able to allocate that space, shouldn't it?

Thanks Matthew, you are absolutely right.

I am working on Windows XP SP2 32bit with R versions 2.9.1.

Here is an example:
 d <- as.data.frame(matrix(trunc(rnorm(6*27136, 10000, 100)),ncol=6))
 d[,4:5] <- trunc(100*runif(2*27136, 0, 1))
 d[,6] <- trunc(1000*runif(27136, 0, 1))
 for (i in 4:6) d[,i] <- as.factor(d[,i])
 lm(V1 ~ log(V2) + log(V3) + V4 + V5 + V6, data=d)
 memory.size(max=F)
 memory.size(max=T)

I managed to get it run through after setting the 3GB switch for Windows 
and
with a clean R session.
I also noticed later, that after removing na.action=na.exclude more
regressions run through.

But before and after the lm() it seems there should be enough memory which
means that lm() builds up some quite large objects during its 
computations?
-- 
View this message in context: 
http://n4.nabble.com/Once-again-Error-cannot-allocate-vector-of-size-tp1083506p1100164.html
Sent from the R help mailing list archive at Nabble.com.

Fantastic. You're much more likely to get a response now.  Best of
luck.

"werner w" <pensterfuzzer at yahoo.de> wrote in message
news:1264175935970-1100164.post at n4.nabble.com...

Thanks Matthew, you are absolutely right.

I am working on Windows XP SP2 32bit with R versions 2.9.1.

Here is an example:
 d <- as.data.frame(matrix(trunc(rnorm(6*27136, 10000, 100)),ncol=6))
d[,4:5] <- trunc(100*runif(2*27136, 0, 1))  d[,6] <-
trunc(1000*runif(27136, 0, 1))  for (i in 4:6) d[,i] <-
as.factor(d[,i])  lm(V1 ~ log(V2) + log(V3) + V4 + V5 + V6, data=d)
 memory.size(max=F) memory.size(max=T)

I managed to get it run through after setting the 3GB switch for
Windows and
with a clean R session.
I also noticed later, that after removing na.action=na.exclude more
regressions run through.

But before and after the lm() it seems there should be enough memory
which means that lm() builds up some quite large objects during its
computations? --
View this message in context:
http://n4.nabble.com/Once-again-Error-cannot-allocate-vector-of-size-tp1083506p1100164.html
Sent from the R help mailing list archive at Nabble.com.