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

<

[hidden email]> 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

> ______________________________________________

>

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>

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.

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https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide

http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.