Dear R-sig phylo
I’ve been running a few discrete character Mk type models using phytool's
SIMMAP — and I had the idea that it might be useful to try model averaging
across posterior probabilities for node states.
Might this make sense to do, to avoid problems associated with model ranking
via AIC? Ie, average the node state probabilities based on AIC weights? Is
there some fundamental problem with this?
I could imagine generating some code to generate all possible transition models
given a set of N states, and then rather than ranking with AIC, model averaging
for parameter estimates (though now that I think about it, not sure how one
might reasonably average a symmetrical rate and an asymmetrical rate).
Best,
Jake
[[alternative HTML version deleted]]
_______________________________________________
R-sig-phylo mailing list - R-sig-phylo@r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
Searchable archive at http://www.mail-archive.com/r-sig-phylo@r-project.org/
