Dear Carl, Liam, and others,
thanks for your explanation of what went wrong in the fitContinuous
calculations. I set beta to a large number (100) in order to
stop it from reading the maximum value. Then, I got exactly the same
results for lambda with the non-multiplied and the
Hi Emmanuel
I've done as you said but the positions of the branch support values in the
rooted tree remain a problem eg
library(ape)
## original tree
tree - read.tree(text =
Hi Annemarie,
No problem, tried to give some answers below.
On Mon, May 23, 2011 at 8:05 AM, Annemarie Verkerk annemarie.verk...@mpi.nl
wrote:
Dear Carl, Liam, and others,
thanks for your explanation of what went wrong in the fitContinuous
calculations. I set beta to a large number
Hi Annemarie,
The only thing I would add to Carl's comment is that the theoretical
limit of lambda is not 1.0, but can be found (for an ultrametric tree)
by computing:
C-vcv.phylo(tree)
maxLambda-max(C)/max(C[upper.tri(C)])
You can then change the boundary condition for fitContinuous():
Hi Carl, Annemarie-
While it is possible in principle that Annemarie's results reflect true ML
estimate of lambda = 1, I think the practical reason this is occurring is that
the default bounds on lambda in fitContinuous are 1e-7 and 1. Because
optimization in fitContinuous uses a bounded BFGS
