Research Article | OPEN ACCESS
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
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,
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.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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