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Minimax Estimation of the Parameter of ЭРланга Distribution Under Different Loss Functions
Science Journal of Applied Mathematics and Statistics
Volume 4, Issue 5, October 2016, Pages: 229-235
Received: Aug. 31, 2016; Accepted: Sep. 12, 2016; Published: Oct. 8, 2016
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 estimation of the parameter of ЭРланга distribution based on complete samples. The Bayes estimators of the parameter of ЭРланга distribution are obtained under three different loss functions, namely, weighted square error loss, squared log error loss and entropy loss functions by using conjugate prior inverse Gamma distribution. Then the minimax estimators of the parameter are derived by using Lehmann’s theorem. Finally, performances of these estimators are compared in terms of risks which obtained under squared error loss function.
Keywords
Bayes Estimator, Minimax Estimator, Squared Log Error Loss Function, Entropy Loss Function
Lanping Li, Minimax Estimation of the Parameter of ЭРланга Distribution Under Different Loss Functions, Science Journal of Applied Mathematics and Statistics. Vol. 4, No. 5, 2016, pp. 229-235. doi: 10.11648/j.sjams.20160405.16
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