[R-sig-ME] zipoisson in MCMCglmm

[Josh Van Buskirk]

Dear all,

Does anyone have experience working with Jarrod Hadfield's MCMCglmm 
package with a zero-inflated Poisson distribution? After fitting the 
model, I'm having trouble obtaining the fixed effect coefficients 
from the logistic (inflated) and Poisson parts of the model. I'm 
interested in estimating how the fixed effects influence both processes.

In this example, many random genotypes are sampled within many random 
populations. There are two fixed effects. The response variable is 
highly zero-inflated.

priors <- list(R=list(V=diag(2),n=2), G=list(G1=list(V=diag(2), n=2), 
G2=list(V=diag(2), n=2)))
model <- MCMCglmm(
         response ~ fixed1 + fixed2 ,
         random = ~idh(trait):Population + idh(trait):Genotype,
         family = "zipoisson",
         prior = priors,
         rcov = ~idh(trait):units,
         data = mydata )

After fitting the model, the object called model$VCV contains 8 
variance components, which makes a little bit of sense: zero-inflated 
and Poisson parts of two random effects (Population and Genotype), 
plus the same for the residual.

However, the object model$Sol contains estimates for three fixed 
effects (intercept, fixed1, fixed2). I expected there to be twice as 
many, because fixed effects can influence both the logistic and 
Poisson parts of the model. In fact, I'm not sure which process these 
estimates refer to (Poisson or logistic).

Any insight here?

Many thanks,

Josh Van Buskirk
University of Zurich
jvb at zool.uzh.ch