BAYESIAN INFERENCE FOR THE PARAMETER OF THE POWER DISTRIBUTION

  • Tanveer Kifayat Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan
  • Muhammad Aslam Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan
  • Sajid Ali Department of Decesion Sciences, Bocconi University, Milan, Italy
Keywords: Bayes Factor, Bayes Posterior Risk, Elicitation, Hyperparameter

Abstract

This study provides Bayesian analysis of the power model using two informative (gamma and Rayleigh) priors and two non-informative (Jeffreys and uniform) priors. The prior predictive distribution is used to elicit the values of the hyperparameters of the prior distribution. The priors are compared using Bayes point and interval estimates, posterior variances, coefficients of skewness and coefficients of kurtosis. Bayes factors and Bayes posterior risks are also used for the comparison of informative and non-informative priors.

 

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Published
2012-06-17
Section
Articles