[R-sig-ME] How to obtain a posterior predictive distribution in MCMCglmm, and constrain it to non-negative values?

[Fiona Scarff]

In MCMCglmm, how can I obtain a posterior predictive distribution? I
have two random effects; individuals from which observations have been
obtained, and a measurement error. I would like to marginalise only
over the individual random effect, and supply a single trivially small
measurement error for the prediction, so as to get the predicted
distribution of the true (rather than measured) response in any
unspecified individual.

Can I further specify this in such a way as to constrain the
prediction to non-negative values? Naively, I could impose a
distribution like log-normal or poisson when fitting the glmm. But the
model fit needs to be able to handle negative values in the response,
which arise purely due to measurement error.

Many thanks for your time and any suggestions!

Fiona Scarff
Murdoch University