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.Meys@Ugent.be
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