30 Scientific Journal of Pure and Applied Sciences (2012) 1(1) 30-39 Bayesian analysis of exponentiated gamma distribution under type II censored samples N. Feroze a, *, M. Aslam b a Department of Mathematics and Statistics, AIOU, Islamabad, Pakistan. b Department of and Statistics, Quaid-i-Azam University, Islamabad, Pakistan. * Corresponding author: Department of Mathematics and Statistics, AIOU, Islamabad, Pakistan. A R T I C L E I N F O Article history: Received 28 September 2012 Accepted 08 October 2012 Available online 30 October 2012 Keywords: Posterior distributions Loss functions Bayes estimators Posterior risks A B S T R A C T The paper is concerned with posterior analysis of exponentiated gamma distribution for type II censored samples. The expressions for Bayes estimators and associated risks have been derived under different priors. The entropy and quadratic loss functions have been assumed for estimation. The posterior predictive distributions have been obtained and corresponding intervals have been constructed. The study aims to find out a suitable estimator of the parameter of the distribution. The findings of the study suggest that the performance of estimators under gamma prior using entropy loss function is the best. © 2012 Sjournals. All rights reserved. 1. Introduction The exponential distribution has been widely used in time to failure data analysis and is preferred for situations where hazard rate is constant. In case of monotonic hazard rate, a number of distributions have been suggested but Weibull and gamma distributions are mostly used. The gamma distribution has a major constraint that its distribution function and survival function cannot be expressed in nice closed forms which create difficulties for further mathematical manipulations. The distribution function, the survival function or the hazard function for the distribution are often evaluated numerically. This is one of the vital reasons that made the gamma distribution unpopular in comparison to the Weibull distribution. Although Weibull distribution has a nice closed form for hazard and survival function, but it has its own disadvantages. For example, Bain and Engelhardt (1991) Contents lists available at Sjournals Journal homepage: www.Sjournals.com Original article