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 O'Meara wrote:
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 related methods (it's a property of the likelihood surface for these
models). You can just plot the alpha values vs likelihood to get a sense of
this surface for your dataset (ideally, estimating the other parameters for
each fixed alpha, which is possible, though the kludge of holding the other
parameters at their MLE and just varying alpha will give you a sense of the
surface, though it's a bit non-conservative). We had code in OUwie to do a
contour plot of the likelihood surface but took it out (a small licensing
difference between akima (university license) and OUwie (GPL) led to OUwie
being pulled from CRAN by the CRAN maintainers until we resolved the
difference).
Brian
_______________________________________
Brian O'Meara
Assistant Professor
Dept. of Ecology & Evolutionary Biology
U. of Tennessee, Knoxville
http://www.brianomeara.info
Students wanted: Applications due Dec. 15, annually
Postdoc collaborators wanted: Check NIMBioS' website
Calendar: http://www.brianomeara.info/calendars/omeara
On Tue, Oct 29, 2013 at 10:21 AM, sandra goutte <gou...@mnhn.fr> wrote:
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 Marguerite Butler <mbutler...@gmail.com>
Dear Sandra,
You might also want to look at the papers that go along with slouch,
ouch,
and ouwie. Here are some pdfs, along with some tutorials.
On my Rcompstart, the ouch stuff starts around page 165
Let me know if you need help with ouch.
Marguerite
On Oct 24, 2013, at 7:03 AM, sandra goutte <gou...@mnhn.fr> wrote:
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
*chi*square distribution with the difference of parameters in the
models as
degree of freedom. Now, how to compare two models with the same number of
optimum changes but at different nodes?
I am having a hard time understanding the details of the function with
regards to Hansen's (1997) paper. What is the relationship between the
deviance and the RSS from Hansen (1997)? Is it possible to calculate the
RSS from the output of compar.ou ?
I would appreciate any advice or insight on the subject!
Sandra.
--
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Muséum National d'Histoire Naturelle
Département Systématique et Évolution
USM 601 / UMR 7205 Origine, Structure et Évolution de la Biodiversité
Reptiles & Amphibiens - Case Postale 30
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____________________________________________
Marguerite A. Butler
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University of Hawaii
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--
Cecile Ane
Departments of Statistics and of Botany
University of Wisconsin - Madison
www.stat.wisc.edu/~ane/
CALS statistical consulting lab:
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