Inferences for stress-strength reliability of Burr Type X distributions based on ranked set sampling

• Published in: Communications in statistics. Simulation and computation Vol. 51; no. 6; pp. 3324 - 3340
• Main Authors: Akgül, Fatma Gül, Şenoğlu, Birdal
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 03.06.2022; Taylor & Francis Ltd
• Subjects: Asymptotic methods; Burr Type X distribution; Confidence intervals; Efficiency; Iterative methods; Maximum likelihood estimators; Modified maximum likelihood; Random sampling; Random variables; Ranked set sampling; Reliability; Resampling; Stress-strength reliability
• ISSN: 0361-0918; 1532-4141
• DOI: 10.1080/03610918.2020.1711949

In this study, we consider the point and interval estimation of the stress-strength reliability based on ranked set sampling when the stress and the strength are both independent Burr Type X random variables. In the context of point estimation, we obtain the maximum likelihood (ML) estimator of using iterative methods. We also use Mehrotra and Nanda's modified maximum likelihood methodology, which gives explicit estimator of as an alternative to the ML methodology. In view of interval estimation, we construct the asymptotic confidence interval of In addition, the bootstrap confidence intervals of are constructed based on two different resampling methods. The performance of the proposed estimators (both point and interval) is compared with their simple random sampling counterparts. A real data set from an agricultural experiment is analyzed to show the implementation of the proposed methodologies.