Phylogenetic community structure: PGLMMs

[This article was first published on Recology, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

So, I’ve blogged about this topic before, way back on 5 Jan this year.

Matt Helmus, a postdoc in the Wootton lab at the University of Chicago, published a paper with Anthony Ives in Ecological Monographs this year (abstract here).  The paper addressed a new statistical approach to phylogenetic community structure.

As I said in the original post, part of the power of the PGLMM (phylogenetic generalized linear mixed models) approach is that you don’t have to conduct quite so many separate statistical tests as with the previous null model/randomization approach.

Their original code was written in Matlab.  Here I provide the R code that Matt has so graciously shared with me.  There are four functions and a fifth file has an example use case.  The example and output are shown below.

Look for the inclusion of Matt’s PGLMM to the picante R package in the future.

Here are links to the files as GitHub gists: 
PGLMM.data.R:  https://gist.github.com/1278205
PGLMM.fit.R:  https://gist.github.com/1284284
PGLMM.reml.R:  https://gist.github.com/1284287
PGLMM.sim.R:  https://gist.github.com/1284288
PGLMM_example.R:  https://gist.github.com/1284442

Enjoy!


The example



..and the figures…



To leave a comment for the author, please follow the link and comment on their blog: Recology.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)