model
{
 for(i in 1:N){
     p[i] <- 1/N
     }
   for( i in 1:N){ 
       y[i] ~ dpois(mu[i]) }
  for(i in 1:N)
   {mu[i] <- theta*step(K-i) + lambda*(1-step(K-i)) }
   theta ~ dgamma(1.0,1.0)
   lambda ~ dgamma(1.0,1.0)
   K ~ dcat(p[ ])
  }

list(y=c(4,5,4,1,0,4,3,4,0,6,3,3,4,0,2,6,3,3,5,4,5,3,1,4,4,1,5,5,3,4,2,5,2,2,3,4,2,1,3,2,2,1,1,1,1,3,0,0,1,0,1,1,0,0,3,1,0,3,2,2,0,1,1,1,0,1,0,1,0,0,0,2,1,0,0,0,1,1,0,2,3,3,1,1,2,1,1,1,1,2,4,2,0,0,0,1,4,0,0,0,1,0,0,0,0,0,1,0,0,1,0,1), N=112)