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pca or nmds (with which normalization and distance ) for abundance data ?

Gavin Simpson
On Fri, 2012-12-14 at 06:22 -0600, Stephen Sefick wrote:
<snip />
By k-D PCA I meant that in nMDS you need to state the dimensionality; in
metaMDS() we start the process from a Principal Coordinates of the data
(PCoA == PCA when Euclidean distances used). I meant that nMDS for say
2d solutions can optimise the configuration arising from the first two
PCA axes.

I don't see the unique solution of PCA as an implicit advantage of that
method. It has a unique solution because the possible solutions are
constrained by the approach; linear combinations of the variables which
best approximate the Euclidean distances between samples. NMDS
generalises this idea extensively into a problem of best preserving the
mapping of the dissimilarities. As such it can do a better job of
drawing the map but that comes at a price.

Again though; horses for courses.
I meant in the sense that PCA is special case of Principal Coordinates
and that nMDS generalises Principal coordinates.

I don't get the point of saying one method is "better" than any other.
Each has uses etc. I certainly don't think any one method "means" more
than the other.

G

Thread (9 messages)

claire della vedova pca or nmds (with which normalization and distance ) for abundance data ? Dec 13 stephen sefick pca or nmds (with which normalization and distance ) for abundance data ? Dec 13 Alan Haynes pca or nmds (with which normalization and distance ) for abundance data ? Dec 13 Jari Oksanen pca or nmds (with which normalization and distance ) for abundance data ? Dec 14 Jari Oksanen pca or nmds (with which normalization and distance ) for abundance data ? Dec 14 Gavin Simpson pca or nmds (with which normalization and distance ) for abundance data ? Dec 14 stephen sefick pca or nmds (with which normalization and distance ) for abundance data ? Dec 14 Gavin Simpson pca or nmds (with which normalization and distance ) for abundance data ? Dec 14 stephen sefick pca or nmds (with which normalization and distance ) for abundance data ? Dec 14