Hi,
I am running a model with count data and one categorical predictor (simple
model for me to understand it fully), I did in R a glm like this:
glm(Recruitment~Depth, family=poisson). I get the coefficientes and
confidence intervals and all is ok. But then I want to do the same model
with Bayesian stats, here is my code:

model
{ for (i in 1:232)
{
Recruitment[i]~dpois(lambda[i])
log(lambda[i])<-a+b[Depth[i]]*Depth[i]
}
a~dnorm(0,0.000001)
b[1]~dnorm(0,0.000001)
b[2]~dnorm(0,0.000001)
b[3]~dnorm(0,0.0000001)
}
list(a=0, b=c(0,0,0))

I have two problems: 1) the resulting credible intervals for the
coefficients (a, b1, b2 and b3) are HUGE don t make any reasonable sense;
2) Using OpenBugs and Winbugs I get different results,

if anyone can help me I appreciate a lot your time,

thanks

Guillermo

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