My data has three columns Time, Interval, Count. I have a mixture of Poissons that goes like this
mod_string = " model{
for(i in 2:length(Count)){
Count[i] ~ dpois(lambda.hacked[i]*z[i]+0.0001)
z[i] ~dbern(p)
lambda.hacked[i] <- mu[ clust[i] ]
Prob <- p^-(1:i) * (1-p) / p
mu <- (Time[1:i] - Interval[1:i])*lambda
clust[i] ~ dcat( Prob)
}
## Priors
lambda ~ dgamma(0.01,0.02)
p ~ dbeta(1,1)
}"
mu changes size at every iteration. As i grows, the number of clusters also grows.
How can I adapt this?