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

[stevenmh at muohio.edu]

Hi Phil,
Are you using metaMDS in the vegan package? This allows you to determine
the number of random starts, and selects the best. It might help.
Hank Stevens
> 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
>>
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>
> *** --- ***
> Christian Hennig
> University College London, Department of Statistical Science
> Gower St., London WC1E 6BT, phone +44 207 679 1698
> chrish at stats.ucl.ac.uk, www.homepages.ucl.ac.uk/~ucakche
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>