A Google search on "lapply vs for r" or "lapply vs loop r" might have saved you some trouble. Many people have debunked this myth. Strangely they all start out with "everyone knows" or "it is commonly said that." I'm sure someone must have said it, but no one seems to be able to provide an authoritative citation before proceeding to demonstrate that it is false.
------------------------------------- David L Carlson Department of Anthropology Texas A&M University College Station, TX 77840-4352 -----Original Message----- From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Jesús Para Fernández Sent: Monday, August 7, 2017 9:30 AM To: r-help@r-project.org Subject: [R] Has For bucle be impooved in R Hi! I am doing a lapply and for comparaison and I get that for is faster than lapply. What I have done: n<-100000 set.seed(123) x<-rnorm(n) y<-x+rnorm(n) rand.data<-data.frame(x,y) k<-100 samples<-split(sample(1:n),rep(1:k,length=n)) res<-list() t<-Sys.time() for(i in 1:100){ modelo<-lm(y~x,rand.data[-samples[[i]]]) prediccion<-predict(modelo,rand.data[samples[[i]],]) res[[i]] <- (prediccion - rand.data$y[samples[[i]]]) } print(Sys.time()-t) Which takes 8.042 seconds and using Lapply cv.fold.fun <- function(index){ fit <- lm(y~x, data = rand.data[-samples[[index]],]) pred <- predict(fit, newdata = rand.data[samples[[index]],]) return((pred - rand.data$y[samples[[index]]])^2) } t<-Sys.time() nuevo<-lapply(seq(along = samples),cv.fold.fun) print(Sys.time()-t) Which takes 9.56 seconds. So... has been improved the FOR loop on R??? Thanks! [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
