Dear all, I'm running a set of nonparametric MDS analyses, using a wrapper for isoMDS, on a 800x800 distance matrix. I noticed that setting the parameter k to larger numbers seriously increases the calculation time. Actually, with k=10 it calculates already longer than for k=2 and k=5 together. It's now calculating for 6 hours, and counting...
There is quite a difference between the results using k=2 or k=5 when looking at the first 2 dimensions (logically...). I suspect the same when k=10. Yet, I start asking myself whether this makes sense if I'm only using the first 2 dimensions. And I can't think of a formal method to check in a nMDS framework how much dimensions are enough. Anybody an idea? I use metaMDS from the vegan package, although it's not really meant to be used on these data. Cheers Joris -- Joris Meys Statistical Consultant Ghent University Faculty of Bioscience Engineering Department of Applied mathematics, biometrics and process control Coupure Links 653 B-9000 Gent tel : +32 9 264 59 87 joris.m...@ugent.be ------------------------------- Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php [[alternative HTML version deleted]] ______________________________________________ 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.
