Hi MCMCglmm users 

To the best of my knowledge, the predict.MCMCglmm has not yet been completed. I've been working with the package (really cool!) in a multi-response data set with family=rep("exponential",2) and want to get prediction intervals (random effects marginalized) for a part of my data "by hand". For Poisson and Binomial mixed models (with logit link), the CourseNotes has some approximations, but there is no way to tackle exponential density. Here is my code: 



dtprior<-list(R= list(V = diag(2)/3, n = 2), G = list(G1 = list(V = diag(2)/3, n = 2), G2 = list(V = diag(2)/3, n = 2))) 



m1<-MCMCglmm(cbind(PCRVU, NonPCRVU)~trait:age+trait:ins+trait:dist+trait:los-1, 
random = ~us(trait):facility+us(trait):team, rcov = ~us(trait):units, 
prior=dtprior, family=rep("exponential",2), nitt=60000, burnin=10000, 
thin=25, data=test, verbose=TRUE, pr=TRUE, pl=TRUE) 





Any hints would be appreciative! 
Thanks! 


Isaac 



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