Hi everyone, I'd like to get some opinions on why estimates of Bloomberg's k are different using the packages ape and caper in R.
Please see the code below for example, in which I used the same data but got different estimates of k. In my own data, the estimated ks were completely opposite: k=0.0001 in ape, and k=3 in caper. library(ape) library(caper) library(nlme) data(shorebird) # CAPER compdata <- comparative.data(shorebird.tree, shorebird.data, names.col = "Species", vcv.dim=3, vcv = TRUE) caper.model <- pgls(log(Egg.Mass) ~ log(M.Mass) * log(F.Mass), compdata, kappa="ML") summary(caper.model) # k=0.474 # APE gls.model = gls(log(Egg.Mass) ~ log(M.Mass) * log(F.Mass), correlation=corBlomberg(value = 0.1, phy=shorebird.tree), data=shorebird.data, method="ML") summary(gls.model) # k = 0.9079989 Cheers, Solomon Chak [email protected] Virginia Institute of Marine Science College of William and Mary [[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]/
