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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