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Statistical Inference of the Rayleigh Distribution Based on Progressively Type II Censored Competing Risks Data

Department of Mathematics, Beijing Jiaotong University, Beijing 100044, China
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Author to whom correspondence should be addressed.
Symmetry 2019, 11(7), 898; https://doi.org/10.3390/sym11070898
Received: 12 June 2019 / Revised: 5 July 2019 / Accepted: 6 July 2019 / Published: 10 July 2019
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Abstract

A competing risks model under progressively type II censored data following the Rayleigh distribution is considered. We establish the maximum likelihood estimation for unknown parameters and compute the observed information matrix and the expected Fisher information matrix to construct the asymptotic confidence intervals. Moreover, we obtain the Bayes estimation based on symmetric and non-symmetric loss functions, that is, the squared error loss function and the general entropy loss function, and the highest posterior density intervals are also derived. In addition, a simulation study is presented to assess the performances of different methods discussed in this paper. A real-life data set analysis is provided for illustration purposes. View Full-Text
Keywords: competing risks; progressive censoring; Rayleigh distribution; maximum likelihood estimation; Bayes estimation competing risks; progressive censoring; Rayleigh distribution; maximum likelihood estimation; Bayes estimation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Liao, H.; Gui, W. Statistical Inference of the Rayleigh Distribution Based on Progressively Type II Censored Competing Risks Data. Symmetry 2019, 11, 898.

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