[R] isoMDS vs. other non-metric non-R routines

[Jari Oksanen]

philip.leifeld at uni-konstanz.de wrote:
> This was my initial call:
> 
> mds <- isoMDS(dist, y = cmdscale(dist, k = 2), k=2, tol = 1e-3, maxit 
> = 500)
> 
> I played around a little bit with tol and maxit (adding some 
> zeros...) and increased the number of dimensions, but it did not 
> change the results significantly. Using initMDS did not improve the 
> result either. Unfortunately, my data set is too large to be 
> displayed here. Any other ideas? My stress value is still 1.5 as much 
> as in other implementations of NMDS.
> 
It is really difficult to believe that isoMDS would work so completely
differently from other implementations. I guess you already tried
tol=1e-7? After this, a radical trick is to give the Minissa result as
the starting configuration, and see if you stay there and  get the same
stress as Minissa reported. You should. In particular, if you iterate
away from the starting configuration, then the starting configuration
was not as good as you assumed.  If this happens, it would be time to
check the data. I assume you have read in dissimilarities from external
files, and surprises do happen (it makes sense to check the data
anyway).

Increasing the number of dimensions should not get you into a similar
solution as with some other implementation using a lower number of
dimensions.

About the problems Christian Hennig mentioned: My interpretation of his
message was that he was not concerned about isoMDS in particular but
about NMDS in general (but he will correct me if my interpretation was
wrong). I can imagine cases where non-metric solution works badly, in
particular with small data sets. However, that should concern all
implementations similarly, and probably it should be visible in Shepard
plots (see isoMDS help). 

Cheers, Jari Oksanen