BLUPs from MCMCglmm

Eryn McFarlane <mcfarlas at ...> writes:

Dear list,

I was wondering if anyone knew of a way to estimate BLUPs
 from an MCMCglmm model? I would just like to eyeball
the individuals with high and low BLUPs for my trait to 
see if there are other relationships that I can see
(i.e. year effects, affect of territory). Does this make sense to try to do

from these models?


  I *think* you can just look at the $Liab component of the fit,
which as stated is the posterior distribution of the latent variables --
you need to set pl=TRUE.

  This should get you started (although HPDinterval() isn't
behaving sensibly in this case -- not quite sure why not)

 data(PlodiaPO)  
     model1<-MCMCglmm(PO~1, random=~FSfamily, data=PlodiaPO, 
    verbose=FALSE, pl=TRUE)
str(model1$Liab)
mm <- data.frame(m=colMeans(model1$Liab),HPDinterval(model1$Liab))
plot(mm[order(mm$m),"m")