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May 2020 Reliability estimation in a multicomponent stress-strength model for Burr XII distribution under progressive censoring
Raj Kamal Maurya, Yogesh Mani Tripathi
Braz. J. Probab. Stat. 34(2): 345-369 (May 2020). DOI: 10.1214/18-BJPS426

Abstract

We consider estimation of the multicomponent stress-strength reliability under progressive Type II censoring under the assumption that stress and strength variables follow Burr XII distributions with a common shape parameter. Maximum likelihood estimates of the reliability are obtained along with asymptotic intervals when common shape parameter may be known or unknown. Bayes estimates are also derived under the squared error loss function using different approximation methods. Further, we obtain exact Bayes and uniformly minimum variance unbiased estimates of the reliability for the case common shape parameter is known. The highest posterior density intervals are also obtained. We perform Monte Carlo simulations to compare the performance of proposed estimates and present a discussion based on this study. Finally, two real data sets are analyzed for illustration purposes.

Citation

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Raj Kamal Maurya. Yogesh Mani Tripathi. "Reliability estimation in a multicomponent stress-strength model for Burr XII distribution under progressive censoring." Braz. J. Probab. Stat. 34 (2) 345 - 369, May 2020. https://doi.org/10.1214/18-BJPS426

Information

Received: 1 March 2018; Accepted: 1 November 2018; Published: May 2020
First available in Project Euclid: 4 May 2020

zbMATH: 07232933
MathSciNet: MR4093263
Digital Object Identifier: 10.1214/18-BJPS426

Rights: Copyright © 2020 Brazilian Statistical Association

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Vol.34 • No. 2 • May 2020
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