Main Article Content
Abstract
The generalized exponential (GE) distribution proposed by Gupta and Kundu (1999) is an important lifetime distribution in survival analysis. In this article, we propose to obtain Bayes estimators and its associated risk based on a class of non-informative prior under the assumption of three loss functions, namely, quadratic loss function (QLF), squared log-error loss function (SLELF) and general entropy loss function (GELF). The motivation is to explore the most appropriate loss function among these three loss functions. The performances of the estimators are, therefore, compared on the basis of their risks obtained under QLF, SLELF and GELF separately. The relative efficiency of the estimators is also obtained. Finally, Monte Carlo simulations are performed to compare the performances of the Bayes estimates under different situations.
Keywords
Article Details
Authors who publish with this journal agree to the following License
CC BY: This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.