Bayesian Method of an Estimation for Gamma Distribution Generalized Using Extension of Jeffrey's Prior

Abstract

Several structural characteristics of the Generalized Gamma Distribution (GGD) have been revealed in this work. Under four distinct loss functions, the Bayesian technique of determine has been used to determine the parameters of GGD using the Jeffrey's & extension of Jeffrey's priors. Through the use of simulated studies with various sample sizes and R software, the estimate so derived was compared with the traditional Maximum Likelihood Estimator employing MSE. Jeffrey's prior work has been extended to include the equation for the survival function.