Bayesian and non-Bayesian analysis with MCMC algorithm of stress-strength for a new two parameters lifetime model with applications
A parallel system is one of the special redundant systems that industrial systems frequently use to increase reliability and prevent unexpected failures. In this paper, a new two-parameter model called the Poisson Rayleigh distribution (PRD) is studied. Some of its statistical properties are given....
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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AIP Publishing LLC
2023-09-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0167295 |
| _version_ | 1797663105850802176 |
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| author | Najwan Alsadat Ehab M. Almetwally Mohammed Elgarhy Hijaz Ahmad Ghareeb A. Marei |
| author_facet | Najwan Alsadat Ehab M. Almetwally Mohammed Elgarhy Hijaz Ahmad Ghareeb A. Marei |
| author_sort | Najwan Alsadat |
| collection | DOAJ |
| description | A parallel system is one of the special redundant systems that industrial systems frequently use to increase reliability and prevent unexpected failures. In this paper, a new two-parameter model called the Poisson Rayleigh distribution (PRD) is studied. Some of its statistical properties are given. Particularly, we emphasize the study of the stress–strength (SS) reliability parameter, R = p(Y < X), when X and Y have a PRD. Maximum likelihood, maximum product spacing, and Bayesian strategies are utilized to estimate the parameters. Maximum likelihood, maximum product spacing, and Bayesian techniques for R are computed. To assess how each estimation method performs, a simulation study is conducted. In order to demonstrate the adaptability of the suggested model, its goodness of fit for the PRD comparison with other models is demonstrated by application to real datasets. Finally, the SS model for the PRD was applied with two applications of real data depicting the failure times for two types of electrical insulators and pertaining to customer wait times at two banks. |
| first_indexed | 2024-03-11T19:09:47Z |
| format | Article |
| id | doaj.art-04c06cf6b99f4573b89be646281f7827 |
| institution | Directory Open Access Journal |
| issn | 2158-3226 |
| language | English |
| last_indexed | 2024-03-11T19:09:47Z |
| publishDate | 2023-09-01 |
| publisher | AIP Publishing LLC |
| record_format | Article |
| series | AIP Advances |
| spelling | doaj.art-04c06cf6b99f4573b89be646281f78272023-10-09T20:09:21ZengAIP Publishing LLCAIP Advances2158-32262023-09-01139095203095203-2010.1063/5.0167295Bayesian and non-Bayesian analysis with MCMC algorithm of stress-strength for a new two parameters lifetime model with applicationsNajwan Alsadat0Ehab M. Almetwally1Mohammed Elgarhy2Hijaz Ahmad3Ghareeb A. Marei4Department of Quantitative Analysis, College of Business Administration, King Saud University, P.O. Box 71115, Riyadh 11587, Saudi ArabiaDepartment of Statistics, Faculty of Business Administration, Delta University for Science and Technology, Gamasa 11152, EgyptMathematics and Computer Science Department, Faculty of Science, Beni-Suef University, Beni-Suef 62521, EgyptSection of Mathematics, International Telematic University Uninettuno, Corso Vittorio Emanuele II, 39,00186 Roma, ItalyHigher Institute for Computers & Information Technology, ElShorouk, Cairo, EgyptA parallel system is one of the special redundant systems that industrial systems frequently use to increase reliability and prevent unexpected failures. In this paper, a new two-parameter model called the Poisson Rayleigh distribution (PRD) is studied. Some of its statistical properties are given. Particularly, we emphasize the study of the stress–strength (SS) reliability parameter, R = p(Y < X), when X and Y have a PRD. Maximum likelihood, maximum product spacing, and Bayesian strategies are utilized to estimate the parameters. Maximum likelihood, maximum product spacing, and Bayesian techniques for R are computed. To assess how each estimation method performs, a simulation study is conducted. In order to demonstrate the adaptability of the suggested model, its goodness of fit for the PRD comparison with other models is demonstrated by application to real datasets. Finally, the SS model for the PRD was applied with two applications of real data depicting the failure times for two types of electrical insulators and pertaining to customer wait times at two banks.http://dx.doi.org/10.1063/5.0167295 |
| spellingShingle | Najwan Alsadat Ehab M. Almetwally Mohammed Elgarhy Hijaz Ahmad Ghareeb A. Marei Bayesian and non-Bayesian analysis with MCMC algorithm of stress-strength for a new two parameters lifetime model with applications AIP Advances |
| title | Bayesian and non-Bayesian analysis with MCMC algorithm of stress-strength for a new two parameters lifetime model with applications |
| title_full | Bayesian and non-Bayesian analysis with MCMC algorithm of stress-strength for a new two parameters lifetime model with applications |
| title_fullStr | Bayesian and non-Bayesian analysis with MCMC algorithm of stress-strength for a new two parameters lifetime model with applications |
| title_full_unstemmed | Bayesian and non-Bayesian analysis with MCMC algorithm of stress-strength for a new two parameters lifetime model with applications |
| title_short | Bayesian and non-Bayesian analysis with MCMC algorithm of stress-strength for a new two parameters lifetime model with applications |
| title_sort | bayesian and non bayesian analysis with mcmc algorithm of stress strength for a new two parameters lifetime model with applications |
| url | http://dx.doi.org/10.1063/5.0167295 |
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