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 ______________________________________________ R-help@stat.math.ethz.ch 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.
