Dear list. I'm going to make a general pitch for model averaging ancestral state reconstruction -- without solving Rafa's problem that this is not yet implemented in /corHMM/.
Setting aside, for a moment, hidden-rate models -- imagine a set of standard M/k/ model for a binary trait. There are (reasonably) four such models: an ER model, an ARD model, a 0 → 1 model, and a 1 → 0 model. Now imagine further an unlikely, but possible, scenario in which all of our weight of evidence fell on the 0 → 1 and a 1 → 0 models, but 51% landed on the former and 49% on the latter. In the former model our marginal reconstruction at the root will be unambiguously 0 (assuming both 0 & 1 are observed at the tips). Clearly, however, the chances that the root node is 0 or 1 are closer to 50:50 than 100:0 (since under our nearly equally well-supported 1 → 0 model the same node is unambiguously 1). The same dilemma holds for more realistic scenarios -- indeed, I've seen it in empirical data! Lastly, here's a suggestion on how to do model averaging with hidden states: first "merge" hidden levels, and then model-average using Akaike weights (or whatever your preferred approach is to model averaging). That is, if a node has a marginal scaled likelihood of "0A" of 0.4 and "0B" of 0.3 (for observed states 0/1 and hidden levels A/B), then the total probability that that node was in observed state "0" is just 0.4 + 0.3 = 0.7. This is implemented natively in /phytools::ancr/; however, I don't recall if I built it to support hidden states. (For ancestral state reconstruction of a/"fitHRM"/ object in /phytools/, however, it is possible to "hide" hidden states after reconstruction, then model-averaging, including across hidden & "non-hidden" state models becomes quite easy.) Hope this is helpful. Best wishes. Liam Liam J. Revell Professor of Biology, University of Massachusetts Boston Web: http://faculty.umb.edu/liam.revell/ Book: Phylogenetic Comparative Methods in R <https://press.princeton.edu/books/phylogenetic-comparative-methods-in-r> (/Princeton University Press/, 2022) On 11/14/2024 1:19 PM, O'Meara, Brian C via R-sig-phylo wrote: > CAUTION: EXTERNAL SENDER > > Hi, Rafa. > > One thing to look at is whether the models are effectively identical; if the > 3 state is 2 AICc worse than the 2 state it could be that it’s just adding a > single extra parameter with no improvement (i.e, the likelihoods might be the > same). In some of our other software we now have code to detect functionally > redundant models and remove this redundancy, but I don’t remember whether > it’s in corHMM yet. > > Assuming the models are somewhat different, much as I like model averaging > I’d use the one with lower AICc for ancestral state reconstruction (and yep, > glad you brought up all the uncertainties with anc recon). With hisse, with > model averaging one can basically model the turnover, net diversification, > and other diversification-flavored rates: this edge is 0A in this model, and > 0C in that model, but one can still just take the turnover rate from each. > It’s partly a benefit from hisse’s relative inattention to the variation in > transition rates. But corHMM is all about the transition rates: in one model, > we have rates 0A->1A, 0B->1B, while in the other we have 0A->1A, 0B->1B, and > 0C->1C: it’s not that the overall rate of 0->1 is the unweighted mean of the > 0*->1* rates in each model, as state B might be really rare in one model and > common in another. One can think about what happens at equilibrium with the > estimated rate matrix, or use the simmap functionality in corHMM to look at > empirical frequencies of going from 0->1, but it’s an area where I think we > need to think a bit more about how to summarize and present results (for one > thing, I think summarizing by wait times (reciprocal of rates) rather than > rates can be a better way to summarize, so an ephemeral state with a high > outgoing rate that a species is expected to occupy for only a short time does > not have a huge impact on the average parameter). > > I hope this helps; I’m CCing Jeremy Beaulieu and James Boyko in case they’re > not seeing R-sig-phylo posts. > > Best, > Brian > > _________________________________________ > > Brian O’Meara > He/Him > Professor, Dept. of Ecology & Evolutionary Biology > University of Tennessee, Knoxville > > > From: R-sig-phylo<r-sig-phylo-boun...@r-project.org> on behalf of Rafael S > Marcondes<raf.marcon...@gmail.com> > Date: Thursday, November 14, 2024 at 12:11 PM > To: r-sig-phylo<r-sig-phylo@r-project.org> > Subject: [R-sig-phylo] Model-averaging corHMM models? > Hi all, > > I have two corHMM models within 2 AICc units of each other. They differ in > the number of hidden states (2 versus 3). I'm trying to decide how to > proceed from here and wondering if model-averaging would be the way to go. > I'm interested in drawing biological conclusions based on > the parameter estimates, and in doing ancestral character estimation > (strictly for visualization purposes only--I'm well aware of the caveats of > over-interpreting ACE states). > > corHMM doesn't seem to have an in-built model averaging utility. But by > analogy with the one in hisse (modelAveRates), it seems as if it's just a > matter of averaging the parameter estimates based on model AIC weights. Is > it really that simple? How would I deal with the param present in one model > and not the other (related to the additional hidden state)? And then would > it be appropriate to run ACE using the averaged rate parameters? Or would > it be more appropriate to perform ACE separately for each model and then > average the node likelihoods instead? > > Thanks, > > -Rafa > > *--* > *Rafael S. Marcondes, Ph.D. (he/him)* > (The R in Rafael is pronounced like the h in "hat") > *https://www.rafaelmarcondes.com/ <https://www.rafaelmarcondes.com/>* > Faculty Fellow in EEB > Department of BioSciences > Rice University > Houston TX 77005 > > > *"Eu quase que nada não sei. Mas desconfio de muita coisa"* > *"I almost don't know nothing. But I suspect many things"* > -João Guimarães Rosa, Brazilian novelist > (Portuguese original and free English translation by me) > > [[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 athttp://www.mail-archive.com/r-sig-phylo@r-project.org/ > > [[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 athttp://www.mail-archive.com/r-sig-phylo@r-project.org/ [[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/
