model{
  for (j in 1:N){
    DD[j] ~ dnorm(theta[j], tau);
    theta[j] <- p[j] * mu1[j] + (1-p[j]) * mu2[j];
    mu1[j] ~ ddexp(0, tau1);


   latent[j]~dcat(pi[1:L])  # L is the truncation point. We need to put a value for L
   mu2[j] <-theta[latent[j]]
                

     

    #mu2[j] ~ ddexp(0, tau2);


    p[j] ~ dbern(r[j]);
    r[j] ~ dbeta(1, inputp)
   }
  tau ~ dgamma(1, inputs);
  tau1 ~ dgamma(at1, bt1);
  tau2 ~ dgamma(at2, bt2);
}