Hi all, I've stumbled upon some memory limitations for the analysis that I want to run.
I've a matrix of distances between 38000 objects. These distances were calculated outside of R. I want to cluster these objects. For smaller sets (egn=100) this is how I proceed: A<-matrix(scan(file, n=100*100),100,100, byrow=TRUE) ad<-as.dist(A) ahc<-hclust(ad,method="ward",members=NULL) .... However if I try this with the real dataset I end up with memory problems. I've the 64bit version of R installed on a machine with 40Gb RAM (Windows 2003 64bit version). I'm thinking about using only the lower triangle of the matrix but I can't create a distance object for the clustering from the lower.tri Can someone help me with a suggestion for which way to go? Best Regards Bart Thijs -- View this message in context: http://n4.nabble.com/cluster-distance-large-matrix-tp1477237p1477237.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org 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.
