[R-sig-ME] cross-sex genetic correlation
j.hadfield at ed.ac.uk
Wed Jul 26 14:42:35 CEST 2017
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)))
On 26/07/2017 13:33, Simona Kralj Fiser wrote:
> 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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