model
   {   
      for(i in 1 : M) {
         for(j in 1 : N) {
            t[i, j] ~ dweib(r, mu[i])C(t.cen[i, j],)
         }
         mu[i] <- exp(beta[i])
         beta[i] ~ dnorm(0.0, 0.001)
         median[i] <- pow(log(2) * exp(-beta[i]), 1/r)
      }
      r ~ dexp(0.001)
      veh.control <- beta[2] - beta[1]
      test.sub <- beta[3] - beta[1]
      pos.control <- beta[4] - beta[1]
   }