Here are two ways:
f1 <- function(i) weighted.mean(X[i,1], X[i,2]) aggregate(list(wmean = 1:nrow(X)), as.data.frame(X[,3:5]), f1) f2 <- function(x) data.frame(wmean = weighted.mean(x[,1], x[,2]), x[1, 3:5]) do.call(rbind, by(X, as.data.frame(X[,3:5]), f2)) Also you check out the na.rm= argument in ?weighted.mean which may or may not be relevant to you. On 10/10/06, Young Cho <[EMAIL PROTECTED]> wrote: > HI, > > I am trying to figure out an efficient way to calculate group means and > associate each entry with it. I made up an example: > > A = rep(rep(0:1,each=2),3) > B = rep(rep(0:1,4),3) > C = rep(rep(c(0,0,1,1),2),3) > X =cbind(rnorm(24,0,1),runif(24,0,1),A,B,C) > A B C > [1,] -1.92926469 0.32213127 0 0 0 > [2,] -0.83935617 0.77794096 0 1 0 > [3,] -1.27799751 0.26276934 1 0 1 > > Suppose I want to compute a weighted mean of X[,1] by for each group, which > is defined by unique vector (A,B,C) with weights are X[,2]. And then add a > column for the weighted group mean. How can I do this ? My matrix is fairly > large (few thousands) but, luckily, I have only a few factors (<10). > > Thanks a lot, > > Young. > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > 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@stat.math.ethz.ch mailing list 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.