Bayesian Analysis of Exponentiated Pareto Distribution

Modeling and analysis of Survival has been proved a fruitful aspect of statistical work in many fields of science. This paper aims at using Bayesian approach to fitting exponentiated Pareto distribution first introduced by Gupta et al in 1998. A Bayesian approach has been adopted to fit this model as survival model. A real survival data set is used for illustration. Implementation is done using Laplace Approximation, some graphical representations related to the probability density function and hazard function of the exponentiated Pareto are provided. Laplace Approximation codes have been provided to implement censoring mechanism using both optimization and simulation tools.