cross-sex genetic correlation

Hi,

The second way is a *much* better way of doing it but should give the 
same answer. However, in both cases the residual covariance is not 
identifiable (no individual is both male and female) and so you should 
use idh rather than us.

The "subscript out of bounds" error is to do with your code that 
post-processes the model output not an issue with MCMCglmm. Probably you 
have used the wrong names for the (co)variance components.

Also, you haven't passed the prior to MCMCglmm, nor is the prior a valid 
one for the problem as it specifies scalar variances rather than 2x2 
covariance matrices. You could try

prior2 <- list(R=list(V=diag(2), nu=0.02), G=list(G1=list(V=diag(2), nu=2, alpha.mu=c(0,0),alpha.V=diag(2)*1000)))

Cheers,

Jarrod

model <- MCMCglmm(W~sex, random=~us(sex):animal, rcov=~us(sex):units,
prior=prior2, pedigree=Ped, data=Data1, nitt=100000, burnin=10000, thin=10)

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