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 ______________________________________________ [email protected] 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.
