Apologies for not letting this thread rest in peace. The small script
######################################################### set.seed(1234) x <- rnorm(20) y <- rnorm(20) goodcls <- apply(mtxcomb , 2, function(idx) all( dist( cbind( x[idx], y[idx]) ) > 0.9)) mycomb <- mtxcomb [ , goodcls] ######################################################### is perfect to detects groups of 5 points whose distances to each other are always above 0.9. However, in my practical case I have about 500 points and I am looking for subset of several tens of points whose distance is above a given threshold. Unfortunately, the approach above does not scale, so I wonder if anybody is aware of an alternative approach. Many thanks Lorenzo ______________________________________________ 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.
