[R] Calculation time of isoMDS and the optimal number of dimensions
michael.denslow at gmail.com
Wed May 26 05:32:41 CEST 2010
On Tue, May 25, 2010 at 1:00 PM, Joris Meys <jorismeys at gmail.com> wrote:
> 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...
Seems like a long time, I have a 100x100 matrix that takes about 40
secs to run with k=10. What is the wrapper function doing?
> 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?
You might want to look at the nmds.min() function in the ecodist
package, which seeks to minimize stress. Out of curiosity, do you
often use 10 dimensional solutions in your field of study?
Hope this helps,
> I use metaMDS from the vegan package, although it's not really meant to be
> used on these data.
> Joris Meys
> Statistical Consultant
> Ghent University
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