Dear all,
I'm using ape function chronos to produce a chronogram from a ML tree and
I'm running into optimization problems. Using the 'discrete' model, the
likelihood of the 'clock' model (a single rate) is much higher than models
with more rates, which shouldn't be the case since models with more rate
should fit the data better (the multiple-rate trees also look highly
'distorted').
For the 'correlates' and 'relaxed' models I get an error:
"Error in nlminb(start.para, f, g, control = opt.ctrl, lower = LOW, upper =
UP) :
NA/NaN gradient evaluation"
The tree as 240 species and branch lengths were optimized by ML in PAML.
I suspect it is a matter of tweaking the optimization control parameters.
Let me know if you have any suggestions.
Santiago
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