similar to: big databases

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.

Dear list users, I need to learn about MCMC methods, and since there are several packages in R that deal with this subject, I want to use them. I want to buy a book (or more than one, if necessary) that satisfies the following requirements: - it teaches well MCMC methods; - it is easy to implement numerically the ideas of the book, and notation and concepts are similar to the corresponding R

Hi - I am doing some monte carlo simulations comparing bayesian (using Plummer's jags) and maximum likelihood (using lmer from package lme4 by Bates et al). I would like to know if there is a way I can flag nonconvergence and exceptions. Currently the simulations just stop and the output reads things like: Error in optim(.Call("lmer_coef", x, 2, PACKAGE = "Matrix"), fn,

Hi there, I am running Monte Carlo Simulations in R using ordinary "while (condition)" loops. Since the number of iterations is something like 100.000 and within each iteration a given subsample is extended sequentially it takes hours to run the simulation. Does anyone know if there is either a way to avoid using loops in Monte Carlo Simulations or how to include possible faster

i am having problem running my own data. yesterday it was working just fine. today it is not. this is the code i was using as an example to follow. this code ALSO worked just fine yesterday, and is no longer working at all. i suspect it is a problem with either my computer or the software, at this point. if THIS won't even run.... something is wrong. i can assure you this isn't

all, below command not reporting the actual usage report on dovecot 2.2.13. please share your suggestion to how to fix this issue doveadm -f flow mailbox status -A -t 'messages vsize' '*' is just showing rkreddy messages=0 vsize=0 jcplho messages=0 vsize=0 planning messages=0 vsize=0 accounts messages=0 vsize=0 spam.notify messages=0 vsize=0 jsraju messages=0 vsize=0 amarnath

> Date: Mon, 30 Nov 1998 12:07:10 -0500 > From: Paul Gilbert <pgilbert@bank-banque-canada.ca> > To: Ed Kademan <kademan@phz.com> > > >Is there anything R can do that Splus can't? > > Problems which require lots of looping and cannot be re-coded as vector/matrix > operations are theoretically possible but practically infeasible in S, unless > they

I've looked through all of the posts about this issue (and there are plenty!) but I am still unable to solve the error. ERROR: cannot allocate vector of size 455 Mb I am using R 2.6.2 - x86_64 on a Linux x86_64 Redhat cluster system. When I log in, based on the specs I provide [qsub -I -X -l arch=x86_64] I am randomly assigned to a x86_64 node. I am using package GenABEL. My data (~ 650,000

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, I upgraded from Dovecot v2.0.16 to v2.1.7 over night and I noticed this morning that one of my daily reports which lists summarised mailbox sizes per user has started listing nonsense for vsizes. The reporting script at its core calls : doveadm -f flow mailbox status -A -t 'messages vsize' '*' It appears that Dovecot 2.1.7 is not resetting the vsize after collating the sum

Hello, I am doing mcmc=10000 simulations from a posterior distribution of the parameters of a mixture of K=6 normal densities. I have mcmc by K matrices simMeans, simVars and simWeights containing the simulation output: one row for each simulation, one column for each normal component of the mixture. One thing I would like to do is a plot of the posterior predictive density. In order to do that

I've seen several posts over the past 2-3 weeks about memory issues. I've tried to carefully follow the suggestions, but remain baffled as to why I can't load data into R. I hope that in revisiting this issue that I don't exasperate the list. The setting: 1 gig RAM , Linux machine 10 Stata files of approximately 14megs each File contents appear at the end of this boorishly long

I've seen several posts over the past 2-3 weeks about memory issues. I've tried to carefully follow the suggestions, but remain baffled as to why I can't load data into R. I hope that in revisiting this issue that I don't exasperate the list. The setting: 1 gig RAM , Linux machine 10 Stata files of approximately 14megs each File contents appear at the end of this boorishly long

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

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

Hi: I am doing a MCMC algorithm which is well known to consume much computer memory. And I have a problem everytime I run my R program. It stopped at certain iteration and says "can not allocate a vector of 19 kb". It seems that the computer's memory has been exhausted. However, it is said that after each iteration the objects (such as a huge matrix) can be set to NULL. And the

The R memory docs say that the --*-vsize option takes an integer argument and then 'G', 'M', 'K', or 'k'. When I start R using R --max-vsize=10G I receive the warning: WARNING: --max-vsize=10G=10'M': too large and ignored The system that I'm working on is a 64-bit Sun server with 40G of memory. What is the correct syntax for this command? Daniel

Hi, In both R 2.13 and the SVN trunk, I observe odd behaviour with the --max-vsize command-line argument: 1. passing a largeish value (about 260M or greater) makes mem.limits() report NA for the vsize limit; gc() continues to report a value... 2. ...but that value (and the actual limit) is wrong by a factor of 8. I attach a patch for issue 2, lightly tested. I believe that fixing issue 1

Good day Sir/Ma'am! This is Alyssa Fatmah S. Mastura taking up Master of Science in Statistics at Mindanao State University-Iligan Institute Technology (MSU-IIT), Philippines. I am currently working on my master's thesis titled "Comparing the Three Estimation Methods for the Four Parametric Logistic (4PL) Item Response Model". While I am looking for a package about Markov chain

Hi all, I'm trying to estimate a nested model (purchase decision, cloglog formula, & quantity bought given a purchase, truncated Poisson). Some of the parameters are mixed (6) and 4 are fixed for all the respondent. The simulated ML (500 simulations) method forwards highly correlated estimates. After some research, Hybrid Monte Carlo seems to be a good alternative to estimate the model. I