"Jim Brennan" <[EMAIL PROTECTED]> writes: > Yes you are right I guess this works only for normal data. Free advice > sometimes comes with too little consideration :-)
Worth every cent... > Sorry about that and thanks to Spencer for the correct way. Hmm, but is it? Or rather, what is the relation between the correlation of the normals and that of the transformed variables? Looks nontrivial to me. Incidentally, here's a way that satisfies the criteria, but in a rather weird way: N <- 10000 rho <- .6 x <- runif(N, -.5,.5) y <- x * sample(c(1,-1), N, replace=T, prob=c((1+rho)/2,(1-rho)/2)) -- O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
