[R-sig-ME] MCMCglmm rcov specifications

[Ryan King]

Hi list,
If I want to specify heterogeneous variances proportional to a known
factor in MCMCglmm, it seems like mev is the correct option, but
looking at the code it appears to add person-level random effects with
variance fixed at the specified value:

random = ~us(leg(MCMC_mev, -1, FALSE)):MCMC_meta
prior$G<-list(G1=list(V=as.matrix(1), nu=1, fix=1))

I've used the same trick to specify a known co-variance function.
However, the updates for this specification seem to go slowly and
induce bad mixing in my binary outcomes problem. The unidentified
residual variance certainly isn't helping. Is there a trick to
directly specify a matrix R and avoid inducing the identification
headache and slow MME solving?

Thanks,
Ryan King