[R-sig-ME] Covariance matrix specification in MCMCglmm
Alexandre Courtiol
alexandre.courtiol at gmail.com
Sun Mar 13 12:22:43 CET 2016
Dear all,
I am trying to figure out the syntax required to constrain a covariance
matrix in a particular way with MCMCglmm.
I have a multivariate problem, so let's say my response variables are "y1"
and "y2".
I have a fixed effect coding a treatment called "treatment" with "A" or "B".
I want the covariance matrix characterizing individual variation for each
trait.
So I wrote something along:
model <- MCMCglmm(
fixed = cbind(y1, y2) ~ trait:treatment,
random = ~ us(trait:treatment):individuals,
rcov = ~ us(trait):units, ...)
and in the VCV object of the model, I can find something like:
|sigmaA1A1, sigmaA1A2, sigmaA1B1, sigmaA1B2|
|sigmaA2A1, sigmaA2A2, sigmaA2B1, sigmaA2B2|
|sigmaB1A1, sigmaB1A2, sigmaB1B1, sigmaB1B2|
|sigmaB2A1, sigmaB2A2, sigmaB2B1, sigmaB2B2|
which is almost what I want.
The only problem is that my individuals are never in both treatments, so I
would like to constrain the previous matrix to be:
|sigmaA1A1, sigmaA1A2, 0, 0|
|sigmaA2A1, sigmaA2A2, 0, 0|
| 0, 0, sigmaB1B1, sigmaB1B2|
| 0, 0, sigmaB2B1, sigmaB2B2|
instead.
In practice the covariances that I would rather not to estimate are close
to zero, which makes sense, so I could stick to my solution... but I could
gain a bit of extra power if I could constrain those to be exactly zero and
it would look a bit cleaner.
Any idea would be appreciated.
Thanks,
Alex
--
Alexandre Courtiol
http://sites.google.com/site/alexandrecourtiol/home
*"Science is the belief in the ignorance of experts"*, R. Feynman
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