model
   {
      for( i in 1 : N )
      {
      x[i] ~ dlin.fr(alpha, beta)
      }
      
   # Prior distributions of the model parameters   
   
         alpha ~ dgamma(0.001, 0.001)
         beta ~ dunif(0, 1.0)   
   }