On ancestral state reconstructions. I've recently started using Ziheng
Yang's terminology - of referring to reconstructions, derived from ML
transition rates and equilibrium frequencies, as 'empirical Bayes'
reconstructions. I believe this to be the most useful way to describe
these methods.
My
Daniel Barker wrote:
On ancestral state reconstructions. I've recently started using Ziheng
Yang's terminology - of referring to reconstructions, derived from ML
transition rates and equilibrium frequencies, as 'empirical Bayes'
reconstructions. I believe this to be the most useful way to
Hi,
Thanks for the Allman Rhodes paper, it is very nice. For me at least
it confirms my suspicions, but made me realise that claims of
asymmetric transition rates are only suspicious if you are unprepared
to make some (strong?) assumptions. If anyone disagrees with what I
have written
Hi folks-
I still think there is a difference between (i) parameter identifiability,
which may or may not be a problem here, and (ii) strong support for the wrong
model, which clearly appears to be occurring here (e.g., Type I error rates
0.75). I don't think non-identifiability of a
Hi all,
I brought up the non-identifiability of the rich forms of the covarion model
only because that is the source for my intuition that it will be really hard to
distinguish the 1-binary-character threshold from the covarion. I agree with
Dan, that the non-identifiability is not causing
Hi,
I see the problem: the threshold model is symmetric but NOT in the
sense used in the ARD model. In the threshold model it is natural to
think about evolution of the probabilty of being in one state versus
the other. If the probability at the root was 0.2 and evolution was
very slow
Hi,
I have been helping someone with some analyses and came across some
routines to estimate asymmetric transition rates between discrete
characters. This surprised me because its fairly straightforward to
prove that asymmetric transition rates cannot be identified using data
collected
Hi,
I have had a few replies off-list which have made me try and clarify
what I mean. I think the distinction needs to be made between two
types of probability: the probability that an outcome is 0 or 1 Pr(y|
\theta) and the probability density of \theta, Pr(\theta | \gamma),
indexed
HI Jarrod-
It isn't immediately obvious to me why the exercise below reflects something
problematic. In the first scenario, you have a random binary state but with
strong differences in frequency. Because there is effectively no phylogenetic
signal (as data are simply random), this suggests a
Jarrod and Dan,
While I see what Dan is saying and I agree that evaluating this with
non-phylogenetic data is not entirely useful, I think you have stumbled
upon a known issue but one that is not widely appreciated.
While the MK model is a useful model for discrete characters in many ways,
it
Dear Jarrod,
It's not R, but I think very helpful - this is from the Mesquite
documentation at
http://mesquiteproject.org/mesquite_folder/docs/mesquite/CharacterEvolution
/AncestralStates.html -
As of version 1.1 of Mesquite, the AsymmMk model has two options
for the handling
Hi,
I can see that there is information when the rates depend on
speciation, because there is variation in the number of speciation
events the species have experienced in their evolutionary history
(from the root). However, if it is a purely time based process there
is no variation in
Hi All-
This is an interesting discussion. I think there is clearly something going on.
I do not get catastrophic Type I error rates from this exercise (only
'elevated') with discrete char simulations (an equal rates markov process) -
see below. However, Jarrod's latent model seems reasonable
Hi all,
apologies for the long email
I'm a bit more concerned with Dan's elevated Type-1 error rates than Jarrod's
example.
With respect to Jarrod's simulations, I have a few thoughts:
1. I don't understand the claim (in the original email) that its
fairly straightforward to
Mark Holder wrote:
With respect to Jarrod's simulations, I have a few thoughts:
1. I don't understand the claim (in the original email) that its
fairly straightforward to prove that asymmetric transition rates
cannot be identified using data collected on the tips of a
phylogeny It seems
Hi all-
A couple of points. I am actually less concerned about the Type I error rates I
gave in that previous message for the equal rates markov process, even though I
think they are real (e.g., I can corroborate them using Diversitree). I don't
think it is an issue of ascertainment bias, but
Hey all,
This has been a really fantastic discussion. Mark, you make some really
excellent points in response to my earlier comments. I think you are
correct in this.
The question that arises out of Jarrod and Dan's simulations (which I have
just run) is whether a model selection criteria would
correction: the last sentence should have read
I wonder how that would work in this case. I think these are important
questions going forward.
On Thu, Aug 16, 2012 at 11:00 PM, Matt Pennell mwpenn...@gmail.com wrote:
Hey all,
This has been a really fantastic discussion. Mark, you make some
Hi,
I agree that model testing between ARD vs MK models is going to be misleading
when the process is really described by a threshold model (and sorry for
ignoring that set of simulations by Jarrod previously; somehow I misfiled that
email and didn't see it).
The threshold model has nice ways
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