Hello,
I'm running some precursor models in corHMM to understand the evolution of a discrete binary character. Some example code using data(primates) below, but what happens is the internal nodes are not being estimated ($States = NaN). Also, when I unclass(precursor2.primates), the internal Node labels are all "NA". Still solves the optimization, but I can't plot the reconstruction! library(corHMM) data(primates) #write precursor matrix (Marazzi et al., 2012): precursor2.matrix <- matrix(data = c(NA, NA, 2, NA, NA, NA, NA, NA, 1, NA, NA, 4, NA, NA, 3, NA ), nrow = 4, ncol = 4, byrow = TRUE ) rownames(precursor2.matrix) <- c("(0,R1)", "(1,R1)", "(0,R2)", "(1,R2)") rownames(precursor2.matrix) colnames(precursor2.matrix) <- c("(0,R1)", "(1,R1)", "(0,R2)", "(1,R2)") colnames(precursor2.matrix) #running the precursor-2 model: precursor2.primates <- corHMM(primates$tree,primates$trait,rate.cat =2,rate.mat=precursor2.matrix,node.states="marginal",diagn=FALSE) unclass(precursor2.primates) Am I neglecting something in the corHMM() function, or is there something else going on? I run into the same NaN when running the precursor matrices Beaulieu wrote into the corHMM notes. Any help is appreciated! Thank you! , Michael Foisy MSc. Student University of Toronto michael.fo...@mail.utoronto.ca [[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/