ON BAYESIAN-INFERENCE FOR THE INVERSE GAUSSIAN DISTRIBUTION

Bayesian results for the Inverse Gaussian distribution are derived considering a proper prior which enables, under reparametrization in terms of the distribution mean and of the inverse of the squared variation coefficient, of obtaining Bayes estimates of the parameters as well as of their inverses. The complexity of the estimates is shown to be close to the one of the integral of the standard t-distribution.