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According to ?parCapply: parRapply and parCapply always return a vector. This appears not to be the case in the following minimal reproducible example: > library(parallel) > nslaves <- 2 > cl <- makeCluster(nslaves) > X <- matrix(2,nrow=3,ncol=4) > X <- rbind(c(1,1,0,1),X) > tv <- parCapply(cl,X,FUN=function(x){ +

I've started to use the parallel package and it works very well speeding things up. Thank you for making this easy to do. Should I have expected that parCapply would return a vector when parApply returns a matrix? library(parallel) x <- matrix(rnorm(8), nc = 2) apply(x, 2, function(y) y) [,1] [,2] [1,] -0.9649685 0.91339851 [2,] -1.4313140 0.13457671 [3,] 1.0499248

Hi, Here are the issues I found: Typos ----- (a) Found: It a parallel version of ?evalq?, "is" missing. (b) Found: 'parLapplyLB', 'parSapplyLB' are load-balancing versions, intended for use when applying ?FUN? to 'parLapplyLB' has no 'FUN' arg (more on this below). (c) Found: 'clusterApply' calls 'fun' on the first