Leveraging Loss Functions to Bayesian Estimations of (X-G) distribution

Abstract

         This paper, focused on evaluate the performance of Bayesian estimation for estimating the scale parameter, reliability and hazard functions of X-Gamma (X-G) distribution. Bayesian procedure involving information Gamma and non-information Gamma prior. The Lindley's approximation has been used to calculate Bayes estimates utilizing two different loss functions, namely the squared error and the entropy loss function. The comparisons between the scale parameter estimates were based on values from bias and Mean Square Error and for reliability and hazard functions were integrated mean squared error.