similar to: doSMP package works better than perfect, at least sometimes.

Hello, I'd like to use package 'doSMP'. But I can only found source codes in the CRAN. I tried to build source code using 'r CMD build doSMP' in the source directory, the following error is shown: ERROR: dependencies 'foreach', 'iterators', 'revoIPC' are not available for pack age 'doSMP' So, i tried to install dependency packages. But I

Hello dear list, I just noticed that: Package ‘doSMP’ was removed from the CRAN repository. http://cran.r-project.org/web/packages/doSMP/index.html Does any one know the reason for this? Is this a technical or a legal (e.g: license) issue? Thanks, Tal ----------------Contact Details:------------------------------------------------------- Contact me: Tal.Galili@gmail.com | 972-52-7275845

Hello, I am having trouple installing doSMP and revoIPC from: https://r-forge.r-project.org/R/?group_id=950 My Linux system: Linux 2.6.35-25-generic #44-Ubuntu SMP Fri Jan 21 17:40:44 UTC 2011 x86_64 GNU/Linux Ubuntu 10.10 \n \l I get this reply: costas at ELEPHANT:~/Downloads$ sudo R CMD INSTALL revoIPC_1.0-3.tar.gz * installing to library ?/home/costas/R/x86_64-pc-linux-gnu-library/2.11? *

Hi list, I was testing out the "doSMP" package from REvolutionR in my regular R2.11.0 installation and I got the following error message.? Well, one obvious thing is that R2.11.0 was built using "i386-pc-mingw32" which is different from what revoIPC used.? I could just use REvolutionR, but all my R peripherals were set up to work with the regular R2.11.0.? So, I really want

This patch allows virtio-net driver to report traffic distribution to inbound/outbound queues through ethtool -S. The per_cpu virtnet_stats is split into receive and transmit stats and are maintained on a per receive_queue and send_queue basis. virtnet_stats() is modified to aggregate interface level statistics from per-queue statistics. Sample output below: NIC statistics: rxq0:

This patch allows virtio-net driver to report traffic distribution to inbound/outbound queues through ethtool -S. The per_cpu virtnet_stats is split into receive and transmit stats and are maintained on a per receive_queue and send_queue basis. virtnet_stats() is modified to aggregate interface level statistics from per-queue statistics. Sample output below: NIC statistics: rxq0:

Hi, R newb here. I've coded a function that inputs N dimensional array(s) [or class=numeric if it's dim=1] of coefficients and tstats, where dim(coef_matrix)=dim(tstat_matrix), it will then output a same dimension matrix of coefficients pasted to tstats in brackets pasted to significance stars. If I go straight to the code INSIDE the function, it works 100% as it's supposed to. The

I was experiencing a strange pattern of slowdowns when using sample.int(), where sampling from a one population would sometimes take 1000x longer than taking the same number of samples from a slightly larger population. For my application, this resulted in a runtime of several hours rather than a few seconds. Looking into it, I saw that sample.int() is hardcoded to switch algorithms when the

Hi, New to R, using version 2.0.1 (2004-11-15) on debian Linux (sid), kernel 2.6.8-2-686. I have data in files with separate vectors on each row of the file, e.g., $ cat /tmp/stats freq,0,1,2,3,4,5,6,7,8,9,16,17,18,19,20,... noise,49,47,48,48,50,47,48,47,46,50,48,54,49,47,49,... signal,99,0,100,0,0,100,0,100,100,0,100,101,100,0,0,... pctrcv,5,0,5,0,0,5,0,5,11,0,5,5,5,0,0,...

Dear r-devel, I am mutating rpart to do calculations on trees. I am trying to extract information from the tree. However, I got a seg. fault. This is the offending line in "rpmatrix.c": deltaI[0][0] = spl->improve; (Commenting it out cures the seg fault) I would like some advice on how to debug this. I have allocated memory with calloc and deltaI[0][0] should be

Hello! I am running a very simple mini Monte-Carlo below using the function tstatistic (right below this sentence): tstatistic = function(x,y){ m=length(x) n=length(y) sp=sqrt( ((m-1)*sd(x)^2 + (n-1)*sd(y)^2)/(m+n-2) ) t=(mean(x)-mean(y))/(sp*sqrt(1/m+1/n)) return(t) } alpha=.1; m=10; n=10 # sets alpha, m, n - for run 1 N=10000 # sets the number of simulations n.reject=0 # counter of num.

As a very new user of R, and a user of S with very limited experience, I thought I would start humbly with a simple t.test. The response to the command sequence sample <- scan() 4 5 6 7 8 9 t.test(sample,mu=20) rather surprised me, because of the idiosyncratic choice of a confidence interval for the mean of the population from which the sample was drawn. I asked my colleague Bob Henery

Hi, people. I was a bit intrigued by the message quoted below. Indeed, if pt() is given a matrix, it returns a matrix. Should this feature be documented? ?pt speaks about "a vector of quantiles", and says nothing about the type of what it returns. The same might presumably apply to other distribution-related functions. ----- Forwarded message from Martyn Plummer <plummer at

Here's one possibility, assuming muhat and sigmahat are estimtes of mu and sigma from N iid draws of N(mu, sigma^2): tStat <- abs(x - muhat) / sigmahat pValue <- pt(tStat, df=N, lower=TRUE) I'm not quite sure what df tStat should have (exercise for math stat), but given fairly large N, that should make little difference. Andy > From: Ross Clement > > Hi. I have a

My parallel code is running slower than my non-parallel code! Can someone pls advise what am I doing wrong here? t and tTA are simple matrices of equal dimensions. #NON PARALLEL CODE nCols=ncol(t) nRows=nrow(t) tTA = matrix(nrow=nRows,ncol=nCols) require(TTR) system.time( for (i in 1:nCols) { x = t[,i] xROC = ROC(x) tTA[,i]=xROC } ) user system elapsed 123.24 0.07 123.47 #

I am trying to assign values to a vector (pvalue). Similar code works in C but not in R. What am I doing wrong? r <- pvalue <- 0 for(i in (1:(k-1))){ for(j in (i+1):k){ r <- r+1 tstat <- (means[i]-means[j])/rms pvalue[r] <- 2*(1-pt(abs(tstat),df)) } } Thank you. Peter B. -- Peter B. Mandeville mandevip at deimos.tc.uaslp.mx Jefe del

RE t.test in R I objected a day or two ago to the behaviour of the one-sample t.test in R where it is easy to generate a "confidence interval" for the mean of the population which does not contain the sample mean, in the case where the null hypothesis is rejected. It now appears that the same behaviour is latent in the code for the two-sample version of this test. The relevant lines

I am trying to pass an equation as an arguement to a function, which seems pretty straightforward given lazy evaluation. I constructed the following little test to make sure I sort of knew what I was doing: go <- function(X,eq) { C <<- X*2; d <<- eq} a _ rnorm(100) go(10,eq=a[.5*length(a)]+C+1) > C [1] 20 > d [1] 21.10551 > a[.5*length(a)] [1] 0.1055086 Everything

Hi, I would like to get suggestion about parallel computing package on a multicore windows workstation. I tried doSMP, but it crashes R a lot. I am wondering if "snow" and "snowfall" can be used on a single workstation (i,e, not cluster). At suggestion would be appreciated, Best, Richard [[alternative HTML version deleted]]

Hi all, I would like to parallelize some R code and would like to use the 'foreach' package with a foreach loop. However, whenever I call a function from an enabled package outside of MASS, I get an error message that a number of the functions aren't recognized (even though the functions should be defined). For example: library(foreach) library(doSMP) library(survival) # Create the