Minimax Estimation of the Parameter of Maxwell Distribution Under Different Loss Functions
American Journal of Theoretical and Applied Statistics
Volume 5, Issue 4, July 2016, Pages: 202-207
Received: May 21, 2016; Accepted: Jun. 6, 2016; Published: Jun. 23, 2016
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Author
Lanping Li, Department of Basic Subjects, Hunan University of Finance and Economics, Changsha, China
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Abstract
The aim of this article is to study the Bayes estimation and minimax estimation of the parameter of Maxwell distribution. Bayes estimators are obtained with non-informative quasi-prior distribution under different loss functions, namely, weighted squared error loss, squared log error loss and entropy loss functions. Then the minimax estimators of the parameter are obtained by using Lehmann’s theorem. Finally, performances of these estimators are compared in terms of risks.
Keywords
Bayes Estimator, Minimax Estimator, Squared Log Error Loss, Entropy Loss, Maxwell Distribution
To cite this article
Lanping Li, Minimax Estimation of the Parameter of Maxwell Distribution Under Different Loss Functions, American Journal of Theoretical and Applied Statistics. Vol. 5, No. 4, 2016, pp. 202-207. doi: 10.11648/j.ajtas.20160504.16
Copyright
Copyright © 2016 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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