Thank you both, Ted and Joe,

My first (or second) option would be doing what Ted suggested, but it will
require a bit more coding than just using already existing functions. I
will try to do that anyway, and compare the results to those from the
cross-validation on the independent contrasts.

Best,

Diego




On Fri, May 16, 2014 at 2:10 PM, Joe Felsenstein <j...@gs.washington.edu>wrote:

> Diego Bilski --
>
> > I'm wondering if it would be statistically/philosophically correct to use
> > n-fold cross-validation to evaluate a linear regression with independent
> > contrasts. My doubt comes from the fact that when simply dividing the IC
> > dataset in, lets say, 10 folds, some folds will remove the contrasts of
> > internal nodes without necessarily removing an entire clade above that
> > point, producing what can be viewed as two independent clades (a
> graphical
> > example would be, in Felsenstein's seminal paper, fig. 8, remove the
> > contrast at node 13, while keeping those at nodes 9 and/or 10).
>
> and Ted Garland wrote:
>
> Couldn't you also just do this back at the level of the original tree and
> > tip data, creating subsets by pruning the tree before you compute
> contrasts?
> >
>
> Under the model of multivariate normality with Brownian Motion
> change along the phylogeny, the contrasts are i.i.d. so of course
> one can use them as points for cross-validation.  But of course,
> unless the regression is nonlinear, there is already a parametric
> framework for distributions of regression coefficients (and other
> associated phenomena) in that i.i.d. MVN framework.
>
> The issue of what entities should be sampled in cross-validation
> depends on how, at what level, you expect the model to depart from
> multivariate normality with Brownian Motion.  Diego and Ted seem to
> have some such expectation but I can't see what that alternative
> model would be.
>
> Joe
> ----
> Joe Felsenstein         j...@gs.washington.edu
>  Department of Genome Sciences and Department of Biology,
>  University of Washington, Box 355065, Seattle, WA 98195-5065 USA
>
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>
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