[exppower_ex0] Exponential Power Model

   [exppower_ex1]
   
   model
   {
      for( i in 1 : N )
      {
      x[i] ~ dexp.power(alpha, lambda)
      }
      
   # Prior distributions of the model parameters   
   
         alpha ~ dunif(0, 20.0)
         lambda~ dunif(0, 1.0)      
   }

Simulated data set with alpha = 2.5 and lambda = 0.25
The MLEs are alpha = 2.5920853 and lambda = 0.2042697

Data ( click to open )


Inits for chain 1        Inits for chain 2     ( click to open )

Results


      mean   sd   MC_error   val2.5pc   median   val97.5pc   start   sample
   alpha   2.581   0.3843   0.001915   1.875   2.564   3.38   1001   50000
   lambda   0.2034   0.008843   4.204E-5   0.1857   0.2035   0.2207   1001   50000
   
   

   Dbar   Dhat   DIC   pD   
x   107.9   105.9   109.9   1.993
total   107.9   105.9   109.9   1.993


[exppower_ex2][exppower_ex3]

[exppower_ex4][exppower_ex5]

[exppower_ex6][exppower_ex7]