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/
