[R-sig-ME] zipoisson in MCMCglmm
Josh Van Buskirk
jvb at zool.uzh.ch
Mon May 11 20:32:08 CEST 2009
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
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