The question I believe you are asking is if there is a way to have 2B-PLS work
for n-dimensional data (n rows in your data matrix) when you have a
s-dimensional phylogenetic covariance matrix (s x s dimensions for s species
covariances) and s < n. The phylo-integration function will work if you find a
way to generalize your s x s species covariance matrix to an n x n specimen
covariance matrix. The n x n matrix would be certainly singular (if that is a
concern) but not pose any computational hindrance on the phylo,integration
Doing this is not trivial. Every cell of the n x n matrix would have to
correspond to the species-species match in the s x s matrix.
There might also be a solution that involves centering specimen vectors, based
on fitted values for a PGLS model with just a mean (i.e., phylo-mean-centering)
and using standard 2B-PLS (without a covariance matrix input).
I offer these possible solutions as something one CAN do but do not wish to
suggest this is something one SHOULD do. I think this is sailing into
unchartered waters with respect to statistical properties.
> On Jan 9, 2018, at 3:19 PM, Pena, Angela <angiep...@gwu.edu> wrote:
> I am interested in using integration methods such as 2B-PLS on 3DGM data from
> 4 different taxa with intraspecific variation. I was able to successfully run
> 2B-PLS in geomorph considering all data points as independent. But I am
> wondering if there is a way to consider that my taxonomic groups might be
> following different patterns of integration. I know you can use the
> phylo.integration function in geomorph for this, but this summarizes each
> group to a species mean, and I am interested in the intraspecific variation.
> Is there another way to do this without summarizing each group to a mean? Any
> help would be greatly appreciated!
> MORPHMET may be accessed via its webpage at http://www.morphometrics.org
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