similar to: size limits

Dear all, I don't get it: First of all, the help doesn't say what are the memory limits of R. Say, what's the max heap size for instance ???? Secondly, I invoke R with the following commands each time: rgui --vsize 30M --nsize 1000K rgui --vsize 30M --nsize 2000K rgui --vsize 30M --nsize 3000K rgui --vsize 30M --nsize 4000K I try to open a matrix 8000x8000 by issuing

My group is working with datasets between 100 Mb and 1 GB in size, using multiple log ins. From the documentation, it appears that vsize is limited to 2^30-1, which tends to prove too restrictive for our use. When we drop that restriction (set vsize = NA) we end up hanging the server, which requires a restart. Is there any way to increase the memory limits on R while keeping our jobs from

Hi everyone, I have a problem that some people may have already encountered but i did not find the solution yet. As I use R to simulate several arrays of data, my workspace is now 35Mb big and I cannot launch R with it. An "xdr real data read error occured" and R tells me to delete .RData or increase memory. I WON'T delete this file and changing the max-nsize to 40600k did not

Sorry, but I lost this thread, so I sending this as a new message. This is really a follow-up to a post from a couple days ago saying that fisher.test from the ctest library crashed on the following data set: > T [,1] [,2] [1,] 2 1 [2,] 2 1 [3,] 4 0 [4,] 8 0 [5,] 6 0 [6,] 0 0 [7,] 1 0 [8,] 1 1 [9,] 7 1 [10,] 8 2 [11,]

Hello R-community, It's been a week now that I am struggling with the implementation of a cox model in R. I have 80 cancer patients, so 80 time measurements and 80 relapse or no measurements (respective to censor, 1 if relapsed over the examined period, 0 if not). My microarray data contain around 18000 genes. So I have the expressions of 18000 genes in each of the 80 tumors (matrix

Let me begin stating that I read all help files and faq's on the subject matter (there aren't more than about a dozen) but either did not find solutions or found them not to work. Here is the issue. I am trying to run a spatial regression on a medium-sized dataset. Part of the functions in the spdep package I use require me to allocate a vector of 1.1 Gb (mine is not a spatial SIG

Dear R-users, I am trying to run some simulations in batch mode. In an older version of the program, I used rterm --vsize=100M --nsize=5000K --restore --save <input file> output file, however, in the new version R 2.2.0 , the parameters vsize and nsize are ignored. I can use the command memory.limit to increase memory, but I am not sure if this corresponds to vsize and nsize.

Hi, Is the following command used to increase the memory or any other command when a background R job is run? R --min-vsize=vl --max-vsize=vu --min-nsize=nl --max-nsize=nu --max-ppsize=N source: http://stat.ethz.ch/R-manual/R-patched/library/base/html/Memory.html Thx Carol [[alternative HTML version deleted]]

Dear R-ers, somehow it is not possible to increase nsize to more than 20000k. When I specify e.g. > R --vsize=10M --nsize=21000K the result is: free total (Mb) Ncells 99658 350000 6.7 Vcells 1219173 1310720 10.0 Maybe I have overlooked s.th.... Marcus -- +------------------------------------------------------- | Marcus Eger | E-Mail: eger.m at gmx.de (NEW) |

I am running R version ??? under Redhat 5.2. It seems as though the --nsize object has no effct on the size of the allocated Ncells as determined using gc(). Yes, I have that much data.... That is if I envoke R with R --vsize 100 --nsize 5000000 then type gc() I get free total Ncells 92202 200000 Vcells 12928414 13107200 Thanks Tony Long Ecology and Evolutionary Biology Steinhaus

Dear Group I'm still trying to bring many data into R (see older postings). After solving some troubles with the database I do most of the work in MySQL. But still I could be nice to work on some data using R. Therefore I can use a dedicated Server with Gentoo Linux as OS hosting only R. This Server is a nice machine with two CPU and 4GB RAM which should do the job: Dual Intel XEON 3.06 GHz

Dear R users, I have noticed that my R startup is extremely slow. It takes almost 3 minutes from "double-click" to R prompt. I have been running R-0.64.1 till recently and it took about 30 sec. I still have access to R-0.64.1. When I started it up, it took about 25 sec. Can anyone tell me if this is a bug in R or a problem with my machine? Note: This is after bootup with R being the

I am trying to upload into R 143 Affymetrix chips onto using R on the NIH Nimbus server. I can load 10 chips without a problem, however, when I try to load 143 I receive a error message: cannot create a vector of 523263 KB. I have expanded the memory of R as follows: R --min-vsize=10M --max-vsize=2500M --min-nsize=10M -max-nsize=50M (as specified in help in R). After running this command the

Dear R-helpers, I am running R version 2.9.1 on a Mac Quad with 32Gb of RAM running Mac OS X version 10.5.6. With over 20Gb of RAM "free" (according to the Activity Monitor) the following happens. > x <- matrix(rep(0, 6600^2), ncol = 6600) # So far so good. But I need 3 matrices of this size. > y <- matrix(rep(0, 6600^2), ncol = 6600) R(3219) malloc: ***

Hi, I am not on this mailing list, but here is a terrible bug that has stopped me in my tracks. I am unable to remove observations from a data matrix. temp is the original matrix. Notice that there are 288 entries with a 104 in the first column. I attempt to remove these entries, but R does not do it. brad ACTUAL COMMANDS: > dim(temp) [1] 30528 11 > table(temp[,1]) 1 3 4

I am trying to translate code from S-PLUS to R and R really struggles! After starting R with the foll. R --vsize 50M --nsize 6M --no-restore on a 400 MHz Pentium with 192 MB of memory running Linux (RH 6.2), I run a function that essentially picks up an external dataset with 2121 rows and 30 columns and builds a lm() object and also runs step() ... the step() takes forever to run...(takes very

G'day R friends, I didn't get any replies on the main list so I thought I'd try with the experts. I was wondering if anyone's ported R to os390. If so, are the vsize and nsize limits the same as other platforms? I could really annoy those SAS guys then. thanks, John Strumila john.strumila@team.telstra.com

For anybody who uses ESS with R, how do you invoke the vsize and nsize options when you call R. I can't find any appropriate variables from an apropos. Thanks, Jord -- Jordan Howarth CSIRO Mathematical and Information Sciences mailto:jordan.howarth at cmis.csiro.au -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Dear R-users, I am currently facing what appears to be a strange thing (at least to my humble understanding). If I understood correctly, starting with the version 1.2.3, R memory allocation can be done dynamically, and there is no need to fiddle with the --nsize and --vsize parameter any longer... So far this everything seemed to go this way (I saw the size of my processes growing when I was

Dear all, in a current project I have a pretty huge .Rdata. Thus I was working with R --vsize 100 --nsize 1000000. Today when I tried to restart R I get the following error message: Error: a read error occured Fatal error: unable to restore saved data (remove .RData or increase memory) I increased memory up to --vsize 180 and --nsize 2000000, but the error reoccurrs. Is there a way to know