Cody,

Have you taken care to scale your data so that they have approximately the
same means and variances?  Sometimes numerical issues arise due to a
mismatch of scales?  What are your variables?  If you plot one against the
other, what do you see?

Regarding the interpretations: a good deal depends on just what the
variables are.  The conclusion: significant off-diagonal elements ->
coevolution is overly simplistic, but that is the general idea, yes.

Aaron

On Tue, May 5, 2015 at 5:17 PM, Cody Dey <[email protected]> wrote:

> Hi all,
>
> I have a large dataset (~6000 species) including two traits of interest. I
> am hoping to test whether the extant patterns are more consistent with each
> trait evolving independently under OU processes (with 1 regime per trait)
> or if the traits have co-evolved in some manner (i.e. the traits influence
> one another's optima).
>
> I have been trying to use mvMORPH and mvSLOUCH to fit two models (one of
> independent evolution, and one of dependent evolution) using the code
> below. My plan was then to compare AIC values from the two models. From
> what I gather, the off-diagonal elements of the alpha and sigma matrix
> determine whether there is co-evolution of the trait optima, and the
> stochastic element of the OU processes, respectively.
>
> ##in mvMORPH
>
> independ.evolv<-mvOU(tree, data, model="OU1",
> param=list(alpha="constraint", sigma="constraint"))
> depend.evolv<-mvOU(tree, data, model="OU1", param=list(alpha=NULL,
> sigma=NULL))
>
> ##and a similar thing in mvSLOUCH
> independ.evolv<-ouchModel(tree, data, regimes=NULL, Atype="Diagonal",
> Syytype="Diagonal")
> depend.evolv<-ouchModel(tree, data, regimes=NULL, Atype="DecomposableReal",
> Syytype="UpperTri")
>
> My questions are:
>
> 1. Is my interpretation of these models correct? Specifically I am
> concerned about the interpretation of the alpha matrix. I am somewhat
> confused as to how the off-diagonal alpha elements influence the OU process
> when I have specified 1 regime per trait.
>
> 2. I am frequently encountering errors during model fitting in mvMORPH of
> the type"Error in loglik_mvmorph(dat, matEstim$V, matEstim$W, n, p, error =
> error,  :   the leading minor of order 5833 is not positive definite". I
> gather this has to do with a problem in the matrix decomposition, but is
> there a practical solution?  I have tried some of the other 'decomp'
> options but this does not seem to help.
>
> 3. I had a few emails with Krzysztof Bartoszek (author of mvSLOUCH) and he
> suggested that such a large dataset would be problematic. Would this be an
> issue for mvMORPH as well? If so, is there a generally acceptable
> work-around for reducing the size of comparative data sets to accommodate
> models like this?
>
> Many thanks in advance
>
>
> ____________________________________________________________________________
>
> Cody Dey
> [email protected]
> McMaster University
> Department of Biology
>
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>
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-- 
Aaron A. King, Ph.D.
Ecology & Evolutionary Biology
Mathematics
Center for the Study of Complex Systems
University of Michigan
GPG Public Key: 0x15780975

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