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Entropy Estimation of Inverse Weibull Distribution under Adaptive Type-II Progressive Hybrid Censoring Schemes

by Rong Xu and Wenhao Gui *
Department of Mathematics, Beijing Jiaotong University, Beijing 100044, China
*
Author to whom correspondence should be addressed.
Symmetry 2019, 11(12), 1463; https://doi.org/10.3390/sym11121463
Received: 31 October 2019 / Revised: 21 November 2019 / Accepted: 25 November 2019 / Published: 28 November 2019
This paper discusses entropy estimations for two-parameter inverse Weibull distributions under adaptive type-II progressive hybrid censoring schemes. Estimations of entropy derived by maximum likelihood estimation method and Bayes estimation method are both considered. Different Bayes estimators using squared loss function, Linex loss function, general entropy loss function, and balanced loss function are derived. Numerical results are derived by Lindley’s approximation method. Especially, the interval estimation of entropy is derived through maximum likelihood estimation method. To test the effectiveness of the estimations, simulation studies are conducted. These entropy estimation methods are illustrated and applied to analyze a real data set. View Full-Text
Keywords: entropy; adaptive type-II progressive hybrid censoring scheme; inverse Weibull distribution; maximum likelihood estimation; Bayes estimation; Lindley’s approximation entropy; adaptive type-II progressive hybrid censoring scheme; inverse Weibull distribution; maximum likelihood estimation; Bayes estimation; Lindley’s approximation
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Xu, R.; Gui, W. Entropy Estimation of Inverse Weibull Distribution under Adaptive Type-II Progressive Hybrid Censoring Schemes. Symmetry 2019, 11, 1463.

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