Not specifically in the statistical problem but in the dimensionality of your problem. stefano
On Nov 28, 2005, at 2:27 PM, Alan Olav Bergland wrote: > The data set is fairly big. > > Again, the model I was trying to run was: > lme(ovn~tlc+geno+log(food), clinal, random=~tlc+geno+log(food)|block/ > lat) > > where, > > "ovn" is a continuous, normal (length=999) > "tlc" is continuous, normal, definitely random > "food" could either be a factor with 6 levels or a numerical variable > (making it log(food) makes a more even distribution). Even though it > is an experimental treatment, I would like to treat it as random > because I am interested in the slope and its interaction with the > "geno" variable (although, note, there are no interactions in the > model above, as putting them in at this point would cause even more > problems) > "geno" is genotype, 12 total, 4 from each "lat." "geno" should > really be treated as random too, because they are random draws from > all genotypes in a population > "lat" is latitude, 3 total. Right now I'm treating it as fixed. > "block" is equivalent to replicate, 2 total. > > The experimental design was the following: > > 12 genotypes, from 3 latitudes, reared under 6 conditions, replicated > twice with ~15-20 individuals measured from each geno x food x block > interaction. Because individuals from each g x f x b were reared in > the same rearing chamber, they are not independent thus some grouping > structure is necessary. > > I appreciate your curiosity on this problem. I know, however, that > this forum is not the place to hack out statistical questions, but > this memory thing seemed specific to Macs. > > Cheers, > Alan > > > > > On Nov 28, 2005, at 8:01 AM, stefano iacus wrote: > >> I don't think this is necessarily a user problem of allocating big >> chunks of memory, or at least I did experienced last days the same >> kind of issue by iterating some linear optimization problem of very >> small dimension (something like 5 rows x 5 columns matrix). >> In my particular problem it was a sequence on independent calls to >> lpSolve on very small problems. Looking at "top" command on the >> shell, I've seen a growing number of vmem (VSIZE?) almost linearly >> with iteration up to 3.5 giga. >> This is also occurring after forcing gc(). If i stop the iteration >> before the alloc failure, the previously allocated ram never gets >> back until I quit R itself. >> I'm not able to debug myself, but I can try to provide a >> reproducible example (not these days, but later on) >> I've faced the same problem on a G4 and a dual G5. >> >> I'm curious to see the dimension of the data Alan is using, but I'm >> confident that this is not where the problem lies. >> >> stefano >> >> >> On Nov 28, 2005, at 1:31 AM, Simon Urbanek wrote: >> >>> >>> On Nov 27, 2005, at 4:37 PM, Alan Olav Bergland wrote: >>> >>>> When I attempt to run a rather hefty lme model, I get the following >>>> error message: >>>> >>>>> clinal7.lme<-lme(ovn~tlc+geno+log(food), clinal, random=~tlc+geno >>>> +log(food)|block/lat) >>>> Error in logLik.lmeStructInt(lmeSt, lmePars) : >>>> Calloc could not allocate (500237956 of 8) memory >>>> R(1049,0xa000ed68) malloc: *** vm_allocate(size=4001906688) failed >>>> (error code=3) >>>> R(1049,0xa000ed68) malloc: *** error: can't allocate region >>>> R(1049,0xa000ed68) malloc: *** set a breakpoint in szone_error to >>>> debug >>>> >>>> >>>> I'm running R Version 2.2.0 (2005-10-06 r35749) on a iMac running >>>> OS 10.4.3 >>>> >>>> >>>> Any suggestions? >>> >>> Reformulate your problem. >>> The lme you run with that data attempts to allocate 4GB of memory >>> which is a bit too much. Even if you put 8GB in a G5 and run 64-bit >>> version of R it's likely to run out of memory or to take forever ... >>> Maybe someone will be able to help you to solve your problem in a >>> different way if you specify more precisely what you are trying >>> to do >>> (including size of the data etc.). >>> >>> Cheers, >>> Simon >>> >>> _______________________________________________ >>> R-SIG-Mac mailing list >>> [email protected] >>> https://stat.ethz.ch/mailman/listinfo/r-sig-mac >>> >> > > _______________________________________________ > R-SIG-Mac mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/r-sig-mac _______________________________________________ R-SIG-Mac mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-mac
