BAYESIAN ESTIMATION OF THE SHAPE PARAMETER OF THE GENERALISED EXPONENTIAL DISTRIBUTION UNDER DIFFERENT LOSS FUNCTIONS

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 fun...

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Bibliographic Details
Published in:Pakistan journal of statistics and operation research Vol. 6; no. 2; p. 163
Main Author: DEY, SANKU
Format: Journal Article
Language:English
Published: Lahore University of the Punjab, College of Statistical & Actuarial Science 01.07.2010
Subjects:
Bayesian analysis
Computer simulation
Entropy
Estimators
Germanium
Monte Carlo methods
Risk
Statistics
ISSN:1816-2711, 2220-5810
Online Access:Get full text
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Summary: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.
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ISSN:1816-2711
2220-5810
DOI:10.18187/pjsor.v6i2.147