model
   {
      for( i in 1 : N )
      {
      x[i] ~ dweib3(nu, lambda, x0)      
      }
      
   # Prior distributions of the model parameters
   
       nu~ dunif(0, 5)
         lambda~ dunif(0, 5)   

         
x0 ~ dgamma(0.001, 0.001)