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Research Article | Open Access

Reliability analysis for two populations Nadarajah-Haghighi distribution under Joint progressive type-II censoring

Mustafa M. Hasaballah1( )Yusra A. Tashkandy2Oluwafemi Samson Balogun3M. E. Bakr2
Marg Higher Institute of Engineering and Modern Technology, Cairo 11721, Egypt
Department of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
Department of Computing, University of Eastern Finland, Kuopio FI-70211, Finland
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Abstract

In order to evaluate the competitive advantages and dependability of two products in a competitive environment, comparative lifespan testing becomes essential. We examine the inference problems that occur when two product lines follow the Nadarajah-Haghighighi distribution in the setting of joint type-II censoring. In the present study, we derived the maximum likelihood estimates for the Nadarajah-Haghighi population parameters. Additionally, a Fisher information matrix was constructed based on these maximum likelihood estimations. Furthermore, Bayesian estimators and their corresponding posterior risks were calculated, considering both gamma and non-informative priors under symmetric and asymmetric loss functions. To assess the performance of the overall parameter estimators, we conducted a Monte Carlo simulation using numerical methods. Lastly, a real data analysis was carried out to validate the accuracy of the models and methods discussed.

CLC number: 62N05, 62F10

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AIMS Mathematics
Pages 10333-10352

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Cite this article:
Hasaballah MM, Tashkandy YA, Balogun OS, et al. Reliability analysis for two populations Nadarajah-Haghighi distribution under Joint progressive type-II censoring. AIMS Mathematics, 2024, 9(4): 10333-10352. https://doi.org/10.3934/math.2024505

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Received: 08 January 2024
Revised: 23 February 2024
Accepted: 07 March 2024
Published: 15 April 2024
©2024 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)