Dear Theodore,
Thanks for your reply but I fear I am not skilled enough in stats for
considering your alternative... I have a look at the paper published by
Jombart et al. (2010, Putting phylogeny into the analysis of biological
traits: a methodological approach. J Theor Biol 264: 693) and it seems they
have only considered the first global and/or first local components and
this even if the second global or local components seemed to explain a
certain amount of the total variance.
Franck
2012/8/23 Theodore Garland Jr theodore.garl...@ucr.edu
That seems like it would be OK, at least if you think it is OK for
nonphylogenetic PCA.
An alternative is to simulate data along your phylogeny, analyze it the
same way, do it a couple thousand times, then make an empirical null
distribution of, say, the eigenvalues when the data have no correlation on
average but increased variance in the values of correlations caused by the
phylogenetic hierarchy.
This is discussed in our very old PHYLOGR package.
However, you will need to make some decisions about the branch lengths
to use for your individuals within species, represented by a bunch of
mini-star phylogenies.
Cheers,
Ted
Theodore Garland, Jr.
Professor
Department of Biology
University of California, Riverside
Riverside, CA 92521
Office Phone: (951) 827-3524
Facsimile: (951) 827-4286 = Dept. office (not confidential)
Email: tgarl...@ucr.edu
http://www.biology.ucr.edu/people/faculty/Garland.html
http://scholar.google.com/citations?hl=enuser=iSSbrhwJ
Experimental Evolution: Concepts, Methods, and Applications of Selection
Experiments. 2009.
Edited by Theodore Garland, Jr. and Michael R. Rose
http://www.ucpress.edu/book.php?isbn=9780520261808
(PDFs of chapters are available from me or from the individual authors)
From: r-sig-phylo-boun...@r-project.org [r-sig-phylo-boun...@r-project.org]
on behalf of Franck Stefani [fopstef...@gmail.com]
Sent: Wednesday, August 22, 2012 3:50 PM
To: r-sig-phylo@r-project.org
Subject: [R-sig-phylo] pPCA - global and local components
Hi,
Among the graphical outputs of the pPCA, there is the scree plot showing
the global and local components. I would like to know what are the criteria
to define the number of GPC or LPC to interpret ? Can we use a broken stick
model?
Cheers,
Franck
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