similar to: object not found with %dopar% when using foreach

Dear R-List member, I have a problem when I'm trying to save two arrays from a foreach-loop. I'm also not sure whether this is possible or just my inexperience. However, this works perferctly fine with a for-loop. Here is an example code - any help is much appreciated!!: ############ n.vpn = 2 n.run= 3 # create to empty matrices sme = matrix(NA,4,n.vpn) test = matrix(NA,4,n.vpn) #

Dear R-list member, I'm using the function pmnorm() (-->library(mnormt)) within a for-loop. Certain parameter values leads to an error message: "(In sqrt(diag(S)) : NaNs produced, In sqrt(1/diag(V)) : NaNs produced, In cov2cor(S) : diag(.) had 0 or NA entries; non-finite result is doubtful)" obviously because "NaNs" were produced. Is it possible to tell R that it

Dear list member, I struggle with the problem, why the probabilities of choosing one of three mutually exclusive alternatives don?t sum up to 1! Let?s assume we have three alternatives X, Y, and Z. Let?s further assume we know their respective utilities: uX, uY, uZ. I?m interested in calculating the probability of choosing X, Y, and Z. Since I assume that the alternatives are mutually

Dear Nik Try the following code loo_predict.mu <- function(model.obj, input.data) { yhat <- foreach(i = 1 : nrow(input.data), .packages="gamlss", .combine = rbind) %dopar% { updated.model.obj <- update(model.obj, data = input.data[-i, ]) predict(updated.model.obj, what = "mu", data = input.data[-i, ], newdata = input.data[i,], type =

Hello Mikis: Thanks a lot, it worked. Could you tell me what the problem was? Regards, Nik ----- Original Message ----- From: r-help-request at r-project.org To: "r-help" Sent: Sunday, March 11, 2018 6:00:02 AM Subject: R-help Digest, Vol 181, Issue 11 Send R-help mailing list submissions to r-help at r-project.org To subscribe or unsubscribe via the World Wide Web, visit

If the code you are running in parallel is complicated, maybe foreach is not sophisticated enough to find all the variables you refer to. Maybe use parallel::clusterExport yourself? But be a aware that passing parameters is much safer than directly accessing globals in parallel processing, so this might just be your warning to not do that anyway. -- Sent from my phone. Please excuse my brevity.

Dear R-SIG-Debian, I am using R version 3.1.2 with rstudio-server 0.98.113 on debian build 3.2.0-4-amd64 #1 SMP Debian 3.2.68-1+deb7u1 x86_64 GNU/Linux. I often use the %dopar% operator in from the foreach package to run code in parallel. However, the only other use on the box seemingly installed a few items and suddenly %dopar% will use far more than the number of cores I am specifying and

Hello all: Please help me with this "can't find object" issue. I'm trying to get leave-one-out predicted values for Beta-binomial regression. It may be the gamlss issue because the code seems to work when %do% is used. I have searched for similar issues, but haven't managed to figure it out. This is on Windows 10 platform. Thanks in advance, Nik #

Hi everyone, I'm working on a script trying to use foreach %dopar% but without success, so I manage to run the code with foreach %do% and looks like this: The code is part of a MCMC model for projects valuation, returning the most important results (VPN, TIR, EVA, etc.) of the simulation. foreach (simx = NsimT, .combine=cbind, .inorder=FALSE, .verbose=TRUE) %do% { MCPVMPA = MCVAMPA[simx]

Hi guys, I was wondering why this piece of code doesn't work: foreach (i = c(1.25,1.50)) %dopar% { assign(paste("test_",i,sep=""),i) } but, this does: foreach (i = c(1.25,1.50)) %do% { assign(paste("test_",i,sep=""),i) } Obviously, the difference is %dopar% vs. %do%. If I use %do%, I get objects test_1.25 and test_1.50, but I don't get these

Hi useRs, I am running a foreach loop and hoped to get a small message when it hits a multiple of 1000, but it does not work. p <- foreach(i=1:10000, .combine='c') %dopar% { if(i%%1000==0) print(i) sqrt(i) } What is the proper way to do it. Thanks everybody. Stephen B [[alternative HTML version deleted]]

All, I am not understanding the scoping used in foreach when it is used inside a function. I keep getting "could not find function" errors for functions that are in memory when I try to use foreach within a function call. I have a simple example below. "testFun" is in memory and works when called by foreach directly, but when I place foreach in a function called

I know this is not a revolution support forum, but as anyone noticed the following? I have a foreach loop to generate random samples. If I run the exact code below in normal r (2.14.1) it works as expected, but if I run it from revolution 4.2.0 each loop returns the same numbers. The only way I can get revolution to give different numbers is using 1 instead of 8 in registerDoSNOW(makeCluster(8,

Hi, I am trying to parallel computing with foreach function, but not able to get the result. I know that in parallel processing, all result is collected in list format, but I am not able to get input there. Any help is really appreciated. esf.m <-foreach (i = 1:n.s, .combine=rbind) %dopar% { EV <- as.data.frame(eig$vectors[,1:n.candid[i]]) colnames(EV) <- paste("EV",

Dear R helpers, I have what another member on this forum described as an embarrassingly parallel problem. I am trying to fit models on subsets of some data based on unique combinations of two id factors in the dataset. Total number of combinations is 30^5, and this takes a long time. So, I would like fit models for each of the datasets produced by subsetting on the unique combinations, splitting

Your code generates an error that has nothing to do with dopar. I have no idea what your function stack is supposed to do; you may be inadvertently calling utils::stack which would produce this kind of error: > stack(1:25, RAT = FALSE) Error in data.frame(values = unlist(unname(x)), ind, stringsAsFactors = FALSE) : arguments imply differing number of rows: 25, 0 HTH, Peter On Wed, Dec 6,

I have used foreach() for parallel computing but in the current problem, it is not working. Given the volume and type of the data involved in the analysis, I will try to give below the complete code without reproducible example. In short, each R environment will draw a set of separate files, perform the analysis and dump in separate folders. splist <- c("juoc", "juos",

Hi all, Within a foreach loop with doSNOW, we cant call functions which come from the non-default package. We need to load(require/library) the package once more within the foreach loop. Anyone knows why would happen like this? Is it caused by the snow package and something happened when "snow" parallelize the job? Other than load the package once more with in the foreach loop, is

Hi there! I have become a big fan of the 'foreach' package allowing me to do a lot of stuff in parallel. For example, evaluating the function f on all elements in a vector x is easily accomplished: foreach(i=1:length(x),.combine=c) %dopar% f(x[i]) Here the .combine=c option tells foreach to combine output using the c()-function. That is, to return it as a vector. Today I discovered the

Dear expeRts, is it possible to carry out calculations between different foreach() calls? As for nested loops, you want to carry out calcuations not depending on the inner loop only once and not for each iteration of the innermost loop. Cheers, Marius library(foreach) foreach(i=1:3) %:% foreach(j=1:2) %do% { i <- i+1 print(paste(i,j)) } foreach(i=1:3) %:% i