similar to: R Crashes when using "large" matrices (Ubuntu 11.04)

Hello, This simple SVD calculation (commands are copied immediately below) crashes on my Ubuntu machine (R 2.13.0). However it worked fine with R.12 and Ubuntu 10.04, and it also works fine on my Windows 7 machine with R 2.13, so I suspect there's a problem with (my?) Ubuntu and / or R. I'm using the R distribution that is accessible with Ubuntu's repositories manager, I am not

Hello, I'm using the eclat function of the arules package (1.0-6) for the identification of frequent itemsets. I need the tidLists, but if I set in the function tidLists=TRUE R crashes (Windows XP Professional SP3, 32 bit, R version 2.12.1 (2010-12-16), reproducible on two different computers) with two different error messages or non at all. Minimum examples are: library(arules)

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https://bugs.freedesktop.org/show_bug.cgi?id=109342 Sih Sîng-hông <ihcaoe at gmail.com> changed: What |Removed |Added ---------------------------------------------------------------------------- QA Contact| |xorg-team at lists.x.org Component|DRM/other |Driver/nouveau

https://bugs.freedesktop.org/show_bug.cgi?id=109342 Sih Sîng-hông <ihcaoe at gmail.com> changed: What |Removed |Added ---------------------------------------------------------------------------- OS|All |Linux (All) -- You are receiving this mail because: You are the assignee for the bug. -------------- next part

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I was surprised to observe the following difference between 2.4.1 and 2.6.0 after a long overdue upgrade a few months ago of our departmental server. It wasn't a bug fix, but a subtle improvement. Here's the simplest example I could create. The size is excessive, on the order of the Netflix Competition data. The integer matrix is about 1.12 GB, and if coerced to numeric it is 2.24 GB.

Hello, I am facing the dreaded "Error: cannot allocate vector of size x Gb" and don't understand enough about R (or operating system) memory management to diagnose and solve the problem -- despite studying previous posts and relevant R help -- e.g.: "Error messages beginning cannot allocate vector of size indicate a failure to obtain memory, either because the size exceeded

Hi there, I'm trying to install the package RcppArmadillo in my R 2.11.1 which I installed and regularly update via Ubuntu's repositories. When I try to install RcppArmadillo from CRAN I get: > install.packages('RcppArmadillo', lib='~/myRlibs') [...] g++ -shared -o RcppArmadillo.so RcppArmadillo.o fastLm.o -L/home/matias/myRlibs/Rcpp/lib -lRcpp

I have distilled my bootstrap problem down to this bit of code, which calculates an estimate of the 95th percentile of 7500 random numbers drawn from a standard normal distribution: library(boot) per95 <- function( annual.data, b.index) { sample.data <- annual.data[b.index] return(quantile(sample.data,probs=c(0.95))) } m <- 10000 x <- rnorm(7500,0,1) B <-

Dear all, I am trying to apply kmeans clusterring on a data file (size is about 300 Mb) I read this file using x=read.table('file path' , sep=" ") then i do kmeans(x,25) but the process stops after two minutes with an error : Error: cannot allocate vector of size 907.3 Mb when i read the archive i notice that the best solution is to use a 64bit OS. "Error messages

Full_Name: Don Maszle Version: 2.3.0 OS: x86_64-unknown-linux-gnu Submission from: (NULL) (206.86.87.3) # On our new 32 GB x86_64 machine R : Copyright 2006, The R Foundation for Statistical Computing Version 2.3.0 (2006-04-24) ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or

I haven't quite figured out how I can change the environment of a function. I have a main function and want to use different auxillary functions, which I supply as parameter (or names). What I want to do is something like this: main.fun=function(aux.fun,dat){ x <- 1 fun.dat() } aux.fun.one=function(){ mean(dat)+x } aux.fun.one=function(){ median(dat)-x } I don't want to

I'm working with a very large matrix ( 22k rows x 2k cols) of RNA expression data with R v.2.5.0 on a RedHat Enterprise machine, x86_64 architecture. The relevant code is below, but I call a function that takes a cluster of this data ( a list structure that contains a $rows elt which lists the rows (genes ) in the cluster by ID, but not the actual data itself ). The

Dear all, I am trying to make some matrix operations (whose size I think is smaller than what R allows) but the operations are not feasible when they run in one session but it is feasible if they run separately while each operation is totally independent of the other. I run the code in one session the error that appears is: Error: cannot allocate vector of size 915.5 Mb R(16467,0xa0421540)

I'm using external pointers and seemingly leaking memory. My determination of a memory leak is that the R process continually creeps up in memory as seen by top while the usage as reported by gc() stays flat. I have isolated the C code: void h5R_allocate_finalizer(SEXP eptr) { Rprintf("Calling the finalizer\n"); void* vector = R_ExternalPtrAddr(eptr); free(vector);

Hi All, I''m having a similar issue as Ian Tobin some weeks ago here: http://lists.xensource.com/archives/html/xen-users/2010-02/msg00645.html I''m using Debian Squeeze amd64, downloaded the experimental debian xen-amd64 kernel with pv_ops support. linux-headers-2.6.32-5-common-xen_2.6.32-13_amd64.deb linux-headers-2.6.32-5-xen-amd64_2.6.32-13_amd64.deb

I am getting "Error: cannot allocate vector of size 197 MB". I know that similar problems were discussed a lot already, but I didn't find any satisfactory answers so far! Details: *** I have XP (32bit) with 4GB ram. At the time when the problem appeared I had 1.5GB of available physical memory. *** I increased R memory limit to 3GB via memory.limit(3000) *** I did gs() and got

Hi, After I create a long list e.g. with x <- vector(mode="list", length=3e9) many bad things start to happen e.g. some things stop working with a spurious error message: gc() # Error in gc() : # long vectors not supported yet: /home/hpages/src/R-3.3.2/src/main/memory.c:1137 x_lens <- lengths(x) # Error in lengths(x) : # long vectors not supported yet:

dear R experts: I am of course no R experts, but use it regularly. I thought I would share some experimentation with memory use. I run a linux machine with about 4GB of memory, and R 2.5.0. upon startup, gc() reports used (Mb) gc trigger (Mb) max used (Mb) Ncells 268755 14.4 407500 21.8 350000 18.7 Vcells 139137 1.1 786432 6.0 444750 3.4 This is my baseline. linux