You need to re-think. What you said is nonsense. Use an appropriate clustering algorithm. (a can be near b; b can be near c; but a is not near c, using "near" = closer than threshhold)
Cheers, Bert Bert Gunter Genentech Nonclinical Biostatistics (650) 467-7374 "Data is not information. Information is not knowledge. And knowledge is certainly not wisdom." H. Gilbert Welch On Thu, Feb 13, 2014 at 12:00 AM, Dario Strbenac <dstr7...@uni.sydney.edu.au> wrote: > Hello, > > I'm looking for a function that groups elements below a certain distance > threshold, based on a distance matrix. In other words, I'd like to group > samples without using a standard clustering algorithm on the distance matrix. > For example, let the distance matrix be : > > A B C D > A 0 0.03 0.77 1.12 > B 0.03 0 1.59 1.11 > C 0.77 1.59 0 0.09 > D 1.12 1.11 0.09 0 > > Two clusters would be found with a cutoff of 0.1. The first contains A,B. The > second has C,D. Is there an efficient function that does this ? I can think > of how to do this recursively, but am hoping it's already been considered. > > -------------------------------------- > Dario Strbenac > PhD Student > University of Sydney > Camperdown NSW 2050 > Australia > ______________________________________________ > 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. ______________________________________________ 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.
