Table of Contents
Advances in Statistics
Volume 2015 (2015), Article ID 964824, 10 pages
http://dx.doi.org/10.1155/2015/964824
Research Article

Bayesian Estimation of Inequality and Poverty Indices in Case of Pareto Distribution Using Different Priors under LINEX Loss Function

Department of Statistics, Panjab University, Chandigarh 160014, India

Received 29 August 2014; Accepted 7 January 2015

Academic Editor: Karthik Devarajan

Copyright © 2015 Kamaljit Kaur et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Bayesian estimators of Gini index and a Poverty measure are obtained in case of Pareto distribution under censored and complete setup. The said estimators are obtained using two noninformative priors, namely, uniform prior and Jeffreys’ prior, and one conjugate prior under the assumption of Linear Exponential (LINEX) loss function. Using simulation techniques, the relative efficiency of proposed estimators using different priors and loss functions is obtained. The performances of the proposed estimators have been compared on the basis of their simulated risks obtained under LINEX loss function.