Dear all,
Following up this conversation; Using OUwie, i get reasonable values for
theta under several models for all my traits, but one. In this case, this
is a trait which can only take positive values and i get negative theta
values for all the different models, including BM and OU1. the
Often if you have a trait constrained to be positive, it's appropriate to
log-transform it, which has the happy effect of making the theta for the
trait when converted back to a non-log scale constrained to be positive (as
well as probably being more appropriate for how your trait evolves).
You
Thank you Marguerite. Looking at OUwie and OUCH/SLOUCH, i see that alpha is
estimated along the other parameters, whereas in Hansen 1997 and other
papers it is suggested that this would lead to very large standard errors.
Is that problem resolved in these functions?
Best,
Sandra.
2013/10/26
In at least the OUwie paper we spent a lot of time doing simulations to
determine this empirically (this may have been examined in other papers,
too, though none come to mind). Alpha can be estimated, but sometimes with
scarily large standard errors (but not always). This property should hold
for
FYI, we have some theory to explain why alpha has large standard errors
and in which conditions. As Brian says, it comes with a flat likelihood
with respect with alpha.
http://dx.doi.org/10.1214/13-AOS1105 or
http://www.stat.wisc.edu/~ane/publis/2013HoAne_AoS.pdf
On 10/29/2013 09:46 AM, Brian
Hi Sandra and others,
You can also assess confidence using parametric bootstrap, a procedure which we
generally recommend for all users. ouch has built-in facilities to do so (the
bootstrap() and simulate() functions in addition to update() ). I think there
are examples in my tutorial. If
Hi Sandra,
I don't know about compar.ou but my mvSLOUCH package (returns RSS and allows
you to have measurement error and missing data) and Butler King's ouch
package return you a lot of stastics that you can use for model comparison.
Maybe in your case the AIC.C would be more appropriate?
You can also use OUwie for a variety of models (OU with different means
and/or different variances and/or different attraction values), but it
returns AIC and lnL scores but not RSS. It sounds, though, that mvSLOUCH
might be the best option in your case.
Best,
Brian
Thank you both for your answers, i will look into those packages.
Best,
Sandra.
2013/10/25 Brian O'Meara bome...@utk.edu
You can also use OUwie for a variety of models (OU with different means
and/or different variances and/or different attraction values), but it
returns AIC and lnL scores
Dear list,
My aim is to compare the fit of models for which *theta* is allowed to
change at different nodes (different combinations of 1 ,2 or 3 nodes). I
don't really understand the calculation of the deviance, but if i'm not
mistaken the difference between the deviances of 2 models follows a
Dear list,
When running compar.ou example from APE package documentation (v.
23-11-09), I've got couple of error messages.
What might be the reason for them:
compar.ou(rnorm(23), bird.orders, alpha = 0.1)
$deviance
[1] 57.60627
$para
estimatestderr
sigma2 0.71937096 0.1500408
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