similar to: possible memory leak involving looping, optimization, and gam

Hi, I'm trying to follow the R-admin instructions for using MKL10 as the external BLAS compiling R-2.6.2 under Linux on a RH EL head node of a cluster. The configure process seems to have problems when it checks for dgemm in the BLAS. I'm using configure as: ./configure CC=icc F77=ifort --with-lapack="$MKL" --with-blas="$MKL" where $MKL is defined as in R-admin

Looking at parLapplyLB, one sees that it takes in X and then passes splitList(X, length(cl)) to clusterApplyLB, which then calls dynamicClusterApply. Thus while dynamicClusterApply does handle tasks in a load-balancing fashion, sending out individual tasks as previous tasks complete, parLapplyLB preempts that by splitting up the tasks in advance into as many groups of tasks as there are cluster

Hi, I am new to R and I have been trying it out. I ran into a problem with the plot() function. Below is my code: > d <- read.table("c:/test/sp.txt",header=0) > spval <- d[,2] > plot(spval,type="l") Warning messages: 1: graphical parameter "type" is obsolete in: plot.window(xlim, ylim, log, asp, ...) 2: graphical parameter "type" is

There is an unannounced and non-backwards-compatible change to the behaviour of 'get' in R2.8.0. 'get'ting a missing value now causes an error, whereas hitherto it's just returned a "missing" object. For example, in R2.8.0 this happens: test> getto <- function( x) get( 'x', sys.frame(1)) test> getto() Error in get("x", sys.frame(1)) :

I can successfully "check" a package with source under 2.5.1, including compiling source files and running examples with no errors or warnings. when I try with R2.6.2, I get make errors: making bayesmc.d from bayesmc.c make[3]:gcc-sjlj: Command not found etc. my gcc is version 3.4.2 I'm using Windows XP. Any thoughts? thanks! peter r ................................ Peter

I am running R on Ubuntu Heron. I recently updated to R 2.8.0 from the default (2.6) in the Ubuntu heron repository by adding deb http://cran.stat.sfu.ca/bin/linux/ubuntu hardy/ I updated all packages installed in /usr/lib/R/site-library and those in my home directory /home/duncan/R/i486-pc-linux-gnu-library/2.6 without obvious issues. I installed adehabitat and gpclib, which should be good

Hi, When I install new packages from CRAN, I frequently find that some packages were missing from the download queue. For example, on one of my computer with R2.6.2, I can not find package glmpath from the download queue. On my other computer with R2.5.1, I could still find that particular package. What could be the reason for this? Is this computer related or R version related? I downloaded the

hello, i have something like: out<-list() for(i in 1:n){ data<-gen(...) #fixed size data out[[i]]<- fun(data) } > object.size(out[[1]]) 6824 In principle 1 GB should allow n = 1024^3/6824 = 157347? i have about 2GB are not taken by other processes. however, I can see the memory shrinking quite rapidly on my system monitor and have to stop the simulation after only n=300. why

Hi Allen and list, See the code below.? I've tried it on R2.13 and R2.8.0 using either heatmap.plus 1.3 or the latest.? All gave the same results.? The problem is in the last line: when I tried to plot two different color bars, the one corresponding to "cm.colors(10)" is not correct (it starts with one black and one red.? Not sure where they're from?) Any ideas? Thanks!

Hi Everybody I use R2.8.0 on Mac OS X. I set up LyX 1.6.1 to use Sweave today. I can compile the test file I found on CRAN ( http://cran.r-project.org/contrib/extra/lyx/) without a problem and the output looks very nice. In the test file the following R code is used. <<myFirstChunkInLyX>>= xObs <- 100; xMean <- 10; xVar <- 9 x <- rnorm(n=xObs, mean=xMean, sd=sqrt(xVar))

Hello all, I just upgraded to R 2.7.0 and found that the behavior of 'var' and 'sd' have changed in the presence NAs (this wasn't explicit in the NEWS file, though I see it probably has to do with the change for cor/cov). Anyway, I just want to make sure that it was intentional to produce an error when there was all NAs and na.rm=TRUE, rather than returning an NA (like R

NIMBLE version 0.6-2 has been released on CRAN and at r-nimble.org. NIMBLE is a system that allows you to: - Write general hierarchical statistical models in BUGS code and create a corresponding model object to use in R. - Build Markov chain Monte Carlo (MCMC), particle filters, Monte Carlo Expectation Maximization (MCEM), or write generic algorithms that can be applied to any model. -

NIMBLE version 0.6-2 has been released on CRAN and at r-nimble.org. NIMBLE is a system that allows you to: - Write general hierarchical statistical models in BUGS code and create a corresponding model object to use in R. - Build Markov chain Monte Carlo (MCMC), particle filters, Monte Carlo Expectation Maximization (MCEM), or write generic algorithms that can be applied to any model. -

Here is a demonstration of behaviour that is probably an optimization by someone far smarter than me that did not anticipate anyone wanting to do this, but for my purposes it looks more like a bug than a feature. I have tested this with R2.6.2 on Windows, no additional packages loaded (beyond the default), I have tested using the default graphics object, pdf, jpeg, and cairoDevice (ok I loaded a

This is hopefully a trivial problem for list subscribers, but I am very new to writing R functions. I wish to call an R function written by myself from another program to fit a model. I need to tell it which of the independent variables are factors. I need to do this in a generic way, so that when the list is passed, R will work through the variables in the data frame and coerce them into being

Hi R-Helpers, I am having difficulty plotting a coxph model with two predictors. My predictors are "morder" (a factor with five levels where the mean of each level is plotted as a separate line) and tmean (continuous). When I run a model with just morder it is fine and the plot is fine. When I add tmean, the coxph model runs fine but this model will not plot and I receive an

Dear developers, I have noticed difference in computation time for the data.frame function between R2.9.0 and R2.8.1. The older release is more efficient: typically, R2.9.0 spends three more time in the data.frame function. Therefore, when many calls of this kind is done inside a function, the additional time spent with R2.9.0 may be several minutes. Looking at the profiling results (see file

Dear R users, I want to conduct a small simulation study and I have to use the lme function in a loop to save the restricted log likelihood. However, for one simulated data set the lme function gives this error Error en lme.formula(yboot ~ X[, -1], data = data.fr, random = Z.block) : nlminb problem, convergence error code = 1 message = singular convergence (7) and then, the

Dear friends - occurring in Windows R2.6.2 I am modeling physical chemistry in collaboration with a friend who has preferred working in Excel. I used uniroot, and find a solution to a two buffer problem in acid-base chemistry which I believe is physiologically sensible. Using "goal seek" in Excel my friend found another plausible root, quite close to zero, and a plot of the function

Dear All, I installed R 2.7.0 and tried to call a dataset i had ealier own called on R2.6.2 but i keep on getting an error: use("maltreat.dta") Error in fromchar(x) : character string is not in a standard unambiguous format Tried doing the same with R2.7.1 but i get the same error. However if i call the same on R 2.6.2, there is no error: use("maltreat.dta") > des()