var
   tauC,mu[3],mean[3],prec[3,3],tau[3,3], Y[K,n], phi[K,3],theta[K,3],
   sigmaC,sigma[3],x[n], R[3,3], eta[K,n], sigma2[3,3];
model {
   for (i in 1:K) {
      for (j in 1:n) {
         Y[i, j] ~ dnorm(eta[i, j], tauC)
         eta[i, j] <- phi[i, 1] / (1 + phi[i, 2] * exp(phi[i, 3] * x[j]))
      }
      phi[i, 1] <- exp(theta[i, 1])
      phi[i, 2] <- exp(theta[i, 2]) - 1
      phi[i, 3] <- -exp(theta[i, 3])
      theta[i, 1:3] ~ dmnorm(mu, tau)
   }
   mu[1:3] ~ dmnorm(mean, prec)
   tau[1:3,1:3] ~ dwish(R, 3)
   sigma2[1:3,1:3] <- inverse(tau)
   for (i in 1:3) {
      sigma[i] <- sqrt(sigma2[i, i])
   }
   tauC ~ dgamma(1.0E-3, 1.0E-3)
   sigmaC <- 1 / sqrt(tauC)
}