Dear Phil, I don't have experiences with Minissa but I know that isoMDS is bad in some situations. I have even seen situations with non-metric dissimilarities in which the classical MDS was preferable.
Some alternatives that you have: 1) Try to start isoMDS from other initial configurations (by default, it starts from the classical solution). 2) Try sammon mapping (command should be "sammon"). 3) Have a look at XGvis/GGvis (which may be part of XGobi/GGobi). These are not directly part of R but have R interfaces. They allow you to toy around quite a lot with different algorithms, stress functions (the isoMDS stress is not necessarily what you want) and initial configurations so that you can find a better solution and understand your data better. Unfortunately I don't have the time to give you more detail, but google for it (or somebody else will tell you more). Best, Christian On Tue, 13 Feb 2007, Philip Leifeld wrote: > Dear useRs, > > last week I asked you about a problem related to isoMDS. It turned > out that in my case isoMDS was trapped. Nonetheless, I still have > some problems with other data sets. Therefore I would like to know if > anyone here has experience with how well isoMDS performs in > comparison to other non-metric MDS routines, like Minissa. > > I have the feeling that for large data sets with a high stress value > (e.g. around 0.20) in cases where the intrinsic dimensionality of the > data cannot be significantly reduced without considerably increasing > stress, isoMDS performs worse (and yields a stress value of 0.31 in > my example), while solutions tend to be similar for better fits and > lower intrinsic dimensionality. I tried this on another data set > where isoMDS yields a stress value of 0.19 and Minissa a stress value > of 0.14. > > Now the latter would still be considered a fair solution by some > people while the former indicates a poor fit regardless of how strict > your judgment is. I generally prefer using R over mixing with > different programs, so it would be nice if results were of comparable > quality... > > Cheers > > Phil > > ______________________________________________ > 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. > *** --- *** Christian Hennig University College London, Department of Statistical Science Gower St., London WC1E 6BT, phone +44 207 679 1698 [EMAIL PROTECTED], www.homepages.ucl.ac.uk/~ucakche ______________________________________________ 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.