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     Research Journal of Applied Sciences, Engineering and Technology


Bayes Estimation of Shape Parameter of Minimax Distribution under Different Loss Functions

Lanping Li
Department of Basic Subjects, Hunan University of Finance and Economics, Changsha 410205, China
Research Journal of Applied Sciences, Engineering and Technology  2015  10:830-833
http://dx.doi.org/10.19026/rjaset.9.2631  |  © The Author(s) 2015
Received: November ‎10, ‎2014  |  Accepted: January ‎8, ‎2015  |  Published: April 05, 2015

Abstract

The object of this study is to study the Bayes estimation of the unknown shape parameter of Minimax distribution. The prior distribution used here is the non-informative quasi-prior of the parameter. Bayes estimators are derived under squared error loss function and three asymmetric loss functions, which are the LINEX loss, precaution loss and entropy loss functions. Monte Carlo simulations are performed to compare the performances of these Bayes estimates under different situations. Finally, we summarize the result and give the conclusion of this study.

Keywords:

Bayes estimator, entropy loss, LINEX loss, minimax distribution, precautionary loss, squared error loss,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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