Bayes Estimation of Parameter of Laplace Distribution Under a New LINEX-Based Loss Function
International Journal of Data Science and Analysis
Volume 3, Issue 6, December 2017, Pages: 85-89
Received: Oct. 27, 2017; Accepted: Nov. 29, 2017; Published: Dec. 26, 2017
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Author
Lanping Li, School of Mathematics and Statistics, Hunan University of Finance and Economics, Changsha, China
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Abstract
Loss function is one of the most topics in Bayesian analysis. The aim of this paper is to study the estimation of the shape parameter of Laplace distribution using Bayesian technique under a new loss function, which is a compound function of LINEX function. The Bayes estimator of the parameter is derived under the prior distribution of the parameter based on Gamma prior distribution. Furthermore, Monte Carlo statistical simulations illustrate that the Bayes estimators obtained under LINEX-based loss function is affected by the prior parameter and the value of the shape parameter of the LINEX-based loss function. But when the sample size is large, they have less influence on the estimation result.
Keywords
Laplace Distribution, Bayes Estimation, LINEX-Based Loss Function, Prior Distribution
To cite this article
Lanping Li, Bayes Estimation of Parameter of Laplace Distribution Under a New LINEX-Based Loss Function, International Journal of Data Science and Analysis. Vol. 3, No. 6, 2017, pp. 85-89. doi: 10.11648/j.ijdsa.20170306.14
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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