Inverse Gaussian



   [invgaussian_ex1]
   
   model
   {
      for( i in 1 : N )
      {
      x[i] ~ dinv.gauss(mu, lambda)
            
      }
      
   # Prior distributions of the model parameters   
   
         mu ~ dunif(0.001, 10.0)
         lambda~ dunif(0.01, 5.0)   
   }




The data set given below represent active repair times (in hours) for an airborne communication transceiver, Chhikara and Folks (1977).

Chhikara R.S, Folks J.L.(1977). The inverse Gaussian distribution as a lifetime model. Technometrics, 19, 461-468.

The MLE's are obtained using 'maxLik' package in R mu = 3.606522    lambda = 1.658853

Data
list( N=46, x = c(0.2, 0.3, 0.5, 0.5, 0.5, 0.5, 0.6, 0.6, 0.7, 0.7, 0.7, 0.8, 0.8, 1.0, 1.0, 1.0, 1.0,
1.1, 1.3, 1.5, 1.5, 1.5, 1.5, 2.0, 2.0, 2.2, 2.5, 2.7, 3.0, 3.0, 3.3, 3.3, 4.0, 4.0, 4.5, 4.7, 5.0, 5.4, 5.4, 7.0, 7.5, 8.8, 9.0, 10.3, 22.0, 24.5))
Inits for chain 1
list(mu=2.0, lambda=1.0)
   
Inits for chain 2
list(mu=5.0, lambda=3.0)



Results

[invgaussian_ex2]

MAP estimates are


[invgaussian_ex3]

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