Dear all, I want to explore gradual/punctual mode of trait evolution, taking into account phylogenetic uncertainty. Thus, I have 1000 trees from bayesian posterior distribution (each tree with ~150 tips). It's very time-consuming to evaluate kappa in BayesTraits, so I decided to use one of the R packages. Unlike lambda estimation, kappa drove me to a standstill. So, I have two questions. I would be extremely grateful for any help or advice for this problems.
1) In fitContinuous, for example, there are boundaries on the kappa (min=0, max=1), although, according to Pagel, kappa varies from 0 to 3. Can you suggest, how to overcome this obstacle? A "degree" of punctuality/graduality is very critical for my research aims. I tried to induce boundaries by bounds=list(kappa = c(min = 0, max = 3)) The highest value of kappa i received was 1.04 (it's quite questionably). 2) Next, I'm in doubt about testing received values. I tried this for one of trees kappa<-fitContinuous(tree, x, model="kappa", bounds=list(kappa = c(min = 0, max = 3))) kappa0<-fitContinuous(kappaTree(tree, 0), x, model="BM") LRT<-2*(kappa$Trait1$lnl-kappa0$Trait1$lnl) p.value<-pchisq(LRT, df=1) Does it make sense? Is it easier to use another package? Thank you in advance! Cheers, Alice -- Alice O. Vershinina, M.Sc. Department of Karyosystematics, Zoological Institute of Russian Academy of Sciences; Phone: +7(911)758-2794; e-mail: [email protected] http://under-the-trees.blogspot.com/ <http://under-the-trees.blogspot.ru/> [[alternative HTML version deleted]] _______________________________________________ R-sig-phylo mailing list - [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-phylo Searchable archive at http://www.mail-archive.com/[email protected]/
