I want to do something like this in R. If I have three vectors> a1[1] 1 2 3> a2[1] 4 5 6> a3[1] 9 10 7 I want to compute 1. A vector that is the mean at each serial position of a1, a2, and a3. so in this example it would have the contents 4.667, 5.667, 5.333333 2. A vector that is the SD at each serial position of a1, a2, and a3. so in this example it would have the contents 4.041452, 4.041452, 2.081666 Can anyone tell me a good way to do this in R? The only thing I can come up with is meanvec<-function(a1,a2,a3) { temp<-numeric(3) for(i in 1:3) temp[i]<-mean(c(a1[i],a2[i], a3[i])) return(temp) } sdvec<-function(a1,a2,a3) { temp<-numeric(3) for(i in 1:3) temp[i]<-sd(c(a1[i],a2[i], a3[i])) return(temp) } If this simple-minded approach is the way to go, I wonder how to modify these functions so I don't need to know the number of vectors ahead of time. That is, make the same function do mean on 3 vectors, 10 vectors, etc--just include all the vectors in the function call. Thanks very much for any help. Bill Simpson -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
I think "apply" is what you're looking for ...
apply(rbind(a1,a2,a3),2,mean)
apply(rbind(a1,a2,a3),2,sd)
or making it into a function:
tmpf _ function(...) {
x _ rbind(...)
list(mean=apply(x,2,mean),sd=apply(x,2,sd))
}
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On Fri, 16 Oct 1998, Bill Simpson wrote:> I want to do something like this in R. If I have three vectors > > a1 > [1] 1 2 3 > > a2 > [1] 4 5 6 > > a3 > [1] 9 10 7 > > I want to compute > 1. A vector that is the mean at each serial position of a1, a2, and a3. > so in this example it would have the contents > 4.667, 5.667, 5.333333 > > 2. A vector that is the SD at each serial position of a1, a2, and a3. > so in this example it would have the contents > 4.041452, 4.041452, 2.081666 > > Can anyone tell me a good way to do this in R? The only thing I can come > up with isUse apply(): cbind(a1,a2,a3) makes matrix apply(cbind(a1,a2,a3),1,mean) computes the mean of each row of the matrix In general you can do meanvec<-function (...) apply(cbind(...), 1, mean) and then R> a1<-1:10 R> a2<-2:11 R> a3<-3:12 R> meanvec(a1,a2,a3) [1] 2 3 4 5 6 7 8 9 10 11 This doesn't check that all the vectors are the same length. A more sophisticated version is meanvec<-function (...) { if (length(unique(sapply(list(...),length)))!=1) stop("not all same length") apply(cbind(...), 1, mean) } R> meanvec(a1,a2,a3) [1] 2 3 4 5 6 7 8 9 10 11 R> a4<-1:3 R> meanvec(a1,a2,a3,a4) Error: not all same length Thomas Lumley ------------------------------------------------------+------ Biostatistics : "Never attribute to malice what : Uni of Washington : can be adequately explained by : Box 357232 : incompetence" - Hanlon's Razor : Seattle WA 98195-7232 : : ------------------------------------------------------------ -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
>>>>> "Bill" == Bill Simpson <wsimpson at uwinnipeg.ca> writes:: I want to do something like this in R. If I have three vectors : > a1 : [1] 1 2 3 : > a2 : [1] 4 5 6 : > a3 : [1] 9 10 7 : : I want to compute : 1. A vector that is the mean at each serial position of a1, a2, and a3. : so in this example it would have the contents : 4.667, 5.667, 5.333333 : : 2. A vector that is the SD at each serial position of a1, a2, and a3. : so in this example it would have the contents : 4.041452, 4.041452, 2.081666 These are the "parallel mean" and "parallel standard deviation" functions that should be part of standard R. There is already a "parallel maximum" function, pmax(...), for example. In fact there should be quite a few of these available, such as psum, pprod, pcumsum, pdiff, ..., so if anyone has the time, feel free. Here are two versions of pmean(). The first should be good enough if the entire structure fits into memory; the second, pmean.large() might be better when dealing with truly huge vectors. pstddev() is left as an exercise... "pmean" <- function (..., na.rm = FALSE) { args <- do.call("cbind", list(...)) nargs <- ncol(args) if (na.rm) { OK <- !is.na(args) args[!OK] <- 0 n <- as.vector(matrix(as.numeric(OK), nrow(args), nargs) %*% rep(1, nargs)) } else n <- nargs as.vector(args %*% rep(1, nargs))/n } "pmean.large" <- function (..., na.rm = FALSE) { elts <- list(...) k <- max(unlist(lapply(elts, length))) total <- rep(as.vector(elts[[1]]), length = k) if (na.rm) { n <- !is.na(total) total[!n] <- 0 } else { n <- length(elts) } for (each in elts[-1]) { work <- rep(as.vector(each), length = k) if (na.rm) { m <- is.na(work) work[m] <- 0 n <- n + !m } total <- total + work } total/n } -- _________________________________________________________________ Bill Venables, Head, Dep't of Statistics, Tel.: +61 8 8303 5418 The University of Adelaide, Fax.: +61 8 8303 3696 South AUSTRALIA. 5005. Email: Bill.Venables at adelaide.edu.au -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._