similar to: LaplacesDemon.hpc parallel prosessing problem

Hi all, I am trying to use snow package to do a parallel MCMC. I have read a few guides and articles, the following is that I came up with. When I run it I got the error message: Error in checkForRemoteErrors(lapply(cl, recvResult)) : 4 nodes produced errors; first error: could not find function "ui.Next" The data is a longitudinal data with few repeated readings on a number of

Greetings, I am having an interesting problem and I wonder if anyone else has seen this behavior. I am running R 2.11.1 with SNOW 0.3-3 on a Dell cluster running CentOS 5.5. I create my cluster using: cluster<- makeCluster(nodes,type="SOCK",port=10191) # nodes is a vector of compute nodes I then wrap a loop around clusterApplyLB to evaluate my function multiple times, with

Hi, Henrik Singmann et al.: ????? Thanks for the suggestions.? I tried again to pull "https://github.com/sbgraves237/Ecdat" from R-Forge, with the same "Error 500" as before.? Then I tried pulling from "https://github.com/rforge/ecdat", which seemed to work ... AND the copy I pulled was at the latest revisions I had posted to R-Forge (520), so that makes it

Hello, I'm trying to run a code that uses the snowfall package. Here is the structure of my code. sfInit(parallel=T, cpus = 5, slaveOutfile="ErrorMessage.txt") sfExportAll() sfLibrary(rgdal) sfLibrary(raster) sfLibrary(sp) sfLibrary(rgeos) sfLibrary(snowfall) system.time( sfClusterApplyLB(1:10, function(k) { sfCat(paste("Iteration ", k),

Henrik's advice is all good. I would say his idea of the final commit of a README pointer is better than deleting things at R-forge; there is likely old information out there somewhere pointing to R-forge as a location for Ecdat development, and any bug reports or discussion on R-forge will not have been copied over to Github. Duncan Murdoch On 28/06/2019 4:14 a.m., Henrik Singmann

Whereas it is true that one has to contact GitHub to detach a GitHub repository, it really is no problem (or at least was no problem in 2016). I wanted to do so when I took over the maintainer role of LaplacesDemon which only remained on GitHub as a fork on some other person's private account. So I forked and then contacted GitHub support and simply asked them to remove the "forked

Re your point 3: Because you have managed to create a GitHub version of your repository that is not a fork of https://github.com/rforge/ecdat, but its own independent repository, contacting GitHub support might not be the right way forward. Note that https://github.com/rforge is simply a read-only mirror of the complete R-Forge repository (and at least to me it is unclear of whether GitHub itself

Hi everybody, I'm looking into replacing the linked lists in tinc with balanced trees. Using balanced trees will greatly improve performance for medium to large VPNs. As I see it, there are several options: 1) Use tsearch()/twalk()/etc functions from glibc. + It is in a very standard library - It relies solely on callback functions, which sometimes results in ugly, awkward code (I

Here is the code, assuming 8 cores in the cpu. library('modeest') library('snow') cl = makeCluster(rep('localhost', 8), 'SOCK') x = vector(length=50) x = sapply(x, function(i) i=sample(c(1,0), 1)) pastK = function(n, x, k) { if (n>k) { return(x[(n-k):(n-1)]) } else {return(NA)} } predR = function(x, k) { pastList = lapply(1:length(x), function(n)

Hello, I have a program that used to run well in October, it uses library snow. Since then, one change has ocurred (snow library has been updated) and another could have ocurred (I've unadvertently modified something). Anyway, now when I make the call: parallel.model.results <- clusterApply(cl,processors.struct,MCexe) exactly as I used to do, where MCexe is my function and

I'm working with snow and created a local cluster. So far, the same code has always worked (please see below). However, now I receive a message that the connection with the nodes cannot be opened. I restarted my workstation but that didn't help. Is there a known solution for this problem? Thanks a lot for any help. bram foubert library(snow) cl =

Hi R-Core, i am using nnet and DEoptim, Xcc=matrix(rnorm(100,0.5,0.08),50,2) Ycr=matrix(rnorm(50,0.2,0.05),50,1) pred_regm1 <- function(A) { A1=A[1] A2=A[2] A3=A[3] regm1 <- nnet(Xcc,Ycr,entropy=T,size=A1,decay=A2,maxit=2000,trace=F,Hess=T,rang=A3,skip=T) dif=sum((predict(regm1,Xcc)-Ycr)^2) return(dif) } somar=DEoptim(pred_regm1,c(1,0.00001,0.01), c(25,0.999,0.95),

Dear All, I have a question of how to export S4 class specification to clusters/workers in parallel computing. The package I used is snowfall. The problem is reproducible as follows. Any hint is greatly appreciated. Edwin Sun === begin =========== library(snowfall) sfInit(parallel = TRUE, cpus = 2) setClass("catt", representation(aa = "numeric")) setClass("dogg",

Hi, The following function use to work, but now it doesn't giving the error "> CallSnow(, 100) Using snow package, asking for 2 nodes 2 slaves are spawned successfully. 0 failed. Error in checkForRemoteErrors(val) : 2 nodes produced errors; first error: no applicable method for 'lapply' applied to an object of class "list" ". Where this is the

Dear R Users, I am attempting to use snow with rmpi. My configuration is: - R Version 2.7.2, rmpi - RMPI 0.5-6 - DeinoMPI 1.1.0 - Windows Xp SP2 I can sucessfully create a cluster and execute simple commands but for some reason, I cannot change the working directory in my nodes. > noclusters<-2 > cl <- makeCluster(noclusters, type = "MPI") 2 slaves are spawned

Hello I would like to use SNOW to parallelise some computations to be made on columns of a data frame, using different parameter values for each SNOW "worker". I gather(?) clusterMap() is the appropriate SNOW function to do something like this. I suspect the problem lies in the fact that I am only supplying one data frame argument for the flow.dat function argument yet the a, b, and x

Dear R-listers, I have been using Snowfall (version 1.84) for parallel computing on a quad-PC running Windows 7 for a month or so without much problem. I started having problems runnnig R with Snowfall over our network when a new Novell client was installed for Windows 7. I experinenced network mapping problem with this new client. Our network colleague provided a fix which worked but a little

Hi, This is my first message to this list. It would be great if people here could help me with the following problem (self-contained code example below): I have a list of matrices and would like to apply a summary function to the matrices in the list. The matrices represent social networks, therefore I need to apply some specialized summary functions provided by the ergm package. These

Hello all, I am re-posting my previous question with a simpler, more transparent, commented code. I have been ramming my head against this problem, and I wondered if anyone could lend a hand. I want to make parallel a bootstrap of a linear mixed model on my 8-core mac. Below is the process that I want to make parallel (namely, the boot.out<-boot(dat.res,boot.fun, R = nboot) command).

People of R(th), I have been ramming my head against this problem, and I wondered if anyone could lend a hand. I want to parallelize a bootstrap of a linear model on my 8-core mac. Below is the process that I want to parallelize (namely, the m2.ph.rlm.boot<-boot(m2.ph,m2.ph.fun, R = nboot) command). This is an extension of the bootstrapping linear models example in Venables and Ripley to