Dear all,

I would like to know when I use NMDS stead PCA or CA analyses? Up to I know, I use PCA (or PCoA) for condense the great part of vaciance on the firsts axis, and CA (or DCA) when I would like to identify the structure/composition of data inside a matrix. 

But I have seem that nowadays many ecologists are using NMDS to dimension reduction on data matrices, and interpret the axis (1, 2 etc) like they do on CA or DCA. My question is if I can use the axis of NMDS output on regression like I can do when with PCA, PCoA, CA and/or DCA axis. 

What is the "stress" effect on the usage of NMDS axis on regression?

Another question is if are there a good PDF text about MDS and NMDS available on the web. 

I know that on "vegan" library (Thanks Oksanen!!) there are same fuctions which deal with MDS, metaMDS. Are there other packages that also works with MDS/NMDS/isoMDS on R? What are the similarity/difference on them?

All comments are very welcome!

Kind regards,

Miltinho
Brazil


       
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