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Estimation based on lower record values from exponentiated Pareto distribution
Journal of the Korean Data & Information Science Society 2017;28:1205-15
Published online September 30, 2017
© 2017 Korean Data & Information Science Society.

Sanggyeong Yoon1 · Youngseuk Cho2 · Kyeongjun Lee3

12Department of Statistics, Pusan National University
3Department of Computer Science and Statistics, Daegu University, Daegu University & Institute of Basic Science, Deagu University
Correspondence to: Kyeongjun Lee
Assistant professor, Department of Computer Science and Statistics, Daegu University, Gyeongsan 38453, Korea. E-mail: leekj@daegu.ac.kr
Received September 4, 2017; Revised September 19, 2017; Accepted September 21, 2017.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
In this paper, we aim to estimate two scale-parameters of exponentiated Pareto distribution (EPD) based on lower record values. Record values arise naturally in many real life applications involving data relating to weather, sport, economics and life testing studies. We calculate the Bayesian estimators for the two parameters of EPD based on lower record values. The Bayes estimators of two parameters for the EPD with lower record values under the squared error loss (SEL), linex loss (LL) and entropy loss (EL) functions are provided. Lindley's approximate method is used to compute these estimators. We compare the Bayesian estimators in the sense of the bias and root mean squared estimates (RMSE).
Keywords : Bayesian estimation, balanced loss function, exponentiated Pareto distribution, Lindley's approximation, lower record values