Flexible Weibull model



   [flexibleweibull_ex1]
   
   model
   {
      for( i in 1 : N )
      {
      x[i] ~ dflex.weib(alpha, beta)
      }   
      # Prior distributions of the model parameters      
         
         alpha ~ dunif(0.001, 10)
         beta ~ dunif(0.001, 10)            
   }

The data set is taken from Bebbington et al.(2007).

Bebbington, M., Lai, C.D. and Zitikis, R. (2007) A flexible Weibull extension. Reliability Engineering and System Safety, 92, 719-726.

The MLE's are alpha = 0.0207    beta = 0.25875

Data
list(N=23, x=c(2.160, 0.746, 0.402, 0.954, 0.491, 6.560, 4.992, 0.347, 0.150, 0.358, 0.101, 1.359, 3.465, 1.060, 0.614, 1.921, 4.082, 0.199, 0.605, 0.273, 0.070, 0.062, 5.320))
Inits for chain 1
list(alpha=0.1, beta= 0.2)
   
Inits for chain 2
list(alpha=0.2, beta= 5.0)



Results


[flexibleweibull_ex2]

MAP estimates are

[flexibleweibull_ex3]

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