Log-Weibull model



[logweibull_ex1]
   
   
   model
   {
      for( i in 1 : N )
      {
            x[i] ~ dlog.weib(mu, sigma)
      }
      
   # Prior distributions of the model parameters   

   # Uniform Prior      
         mu ~ dunif(0, 5)
         sigma~ dunif(0.05, 2)   
               
   }

The data set is taken from Murthy et al. (2004, pp. 119).

Murthy, D. N. P., Xie, M., Jiang, R. (2004), Weibull Models, Wiley-Interscience.

MLE's are mu = 2.36573, sigma.= 0.49440

Data
list(N=20, x=c(0.481, 1.196, 1.438, 1.797, 1.811, 1.831, 1.885, 2.104, 2.133, 2.144,
2.282, 2.322, 2.334, 2.341, 2.428, 2.447, 2.511, 2.593, 2.715, 3.218))
Inits for chain 1
list(mu=1.0, sigma=0.1)
   
Inits for chain 2
list(mu=5.0, sigma=1.2)



Results

[logweibull_ex2]

MAP estimates are
[logweibull_ex3]

   

On this page