I have many sets of heteroscedastic data y. I want to normalize each set independently so I can compare across replicates. Within a set, the mean of y = 0 and the slope = 0 as a function of x, and the variance of y varies by x. The range of y is (-1, +1) more or less and The range of x is (.6,10.5) Imagine a looking at a cone sideways. I split the data into range factors using f <- round(x) then calculated the sd for each range using yfsd<-tapply(ma[[10]][,1], A, sd) Now I would like to divide each element of y by yfsd dim(y)=5000 yfsd has 10 values for the 10 factors If I use tapply I get a vector with 10 values. This is not what I want. Any cleaver ideas? Do I need to loop or use a while statement. Thanks, D -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- 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 _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._