[R-sig-ME] blocked diagonal R structures model convergence

[Jarrod Hadfield]

Hi Rob,

The chain is not mixing because many of the parameters in the residual 
structure are not identifiable in the likelihood. The two R matrices 
should be 2x2 not 4x4; at the moment you are estimating all the residual 
covariances between all the traits twice (i.e 20 parameters rather than 
the 6 that are identifiable). The correct syntax is

us(at.level(trait, 1:2)):units+us(at.level(trait, 3:4)):units

However, this is quite an inefficient way of setting up the model. 
Better to have the two responses as traits and then have sex as a 
categorical predictor. The model would then be:

mod1 <- MCMCglmm(cbind(g,p) ~ trait-1 + trait:sex
trait:r1:sex + trait:r2:sex,
random   = ~us(trait:sex):animal + us(trait:sex):dam,
rcov = ~us(trait:at.level(sex, "1")):units+us(trait:at.level(sex,
"2")):units,
family = c("gaussian", "poisson")

This should run faster and mix better because half the data aren't missing.

Cheers,

Jarrod


On 24/11/2017 14:49, Robert Griffin wrote:
> family = c("gaussian", "poisson", "gaussian", "poisson")


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