MCMC prior issues
David Bradley <bradleyd at ...> writes:
I am trying to use the MCMCglmm package to run a bivariate plasticity model to assess plasticity in the timing of egg laying and the relationship with reproductive success. The issue I am having is with the prior specification, which keep returning errors. #The prior I am using is a flat prior: prior.bi<-list(R = list(V = diag(2), nu = 0.002), G = list(G1 = list(V = diag(4), nu = 0.002)))
[snip]
*Error in MCMCglmm(cbind(savg.nf, sld) ~ trait - 1 + trait:st1 + trait:factor(min.age) + :ill-conditioned G/R structure: use proper priors if you haven't or rescale data if you have*
I thought that I was using a proper prior, and I have already scaled the data. What is the meaning of "ill-conditioned G/R structure"?
I'm not sure (a reproducible example would be nice), but have you tried increasing nu to something larger and seeing if that fixes the problem? That may not necessarily make you happy -- you might prefer a flatter prior -- but that would indicate that your structure is OK, but your priors are too flat ...