Estimation and prediction of modified progressive hybrid censored data from inverted exponentiated Rayleigh distribution

• Published in: Quality technology & quantitative management Vol. ahead-of-print; no. ahead-of-print; pp. 1 - 23
• Main Authors: Wang, Liang, Wu, Shuo-Jye, Tripathi, Yogesh Mani, Dey, Sanku
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 03.07.2024
• Subjects: Generalized estimation; Inverted exponentiated Rayleigh distribution; Maximum likelihood estimates; Modified progressive hybrid censoring; prediction; remaining useful life
• ISSN: 1684-3703; 1684-3703
• DOI: 10.1080/16843703.2023.2219556

In this paper, statistical inference of an inverted exponentiated Rayleigh model is studied when the failure times are obtained under a modified progressive hybrid censoring. The maximum likelihood estimators of the model parameters together with associated existence and uniqueness are established, and approximate confidence intervals are constructed based on asymptotic theory. Alternatively, generalized point and interval estimates for unknown parameters are also constructed based on the proposed pivotal quantities for comparison. In addition, predictive intervals of remaining useful life from the inverted exponentiated Rayleigh distribution are also constructed under classical and generalized inferential approaches, respectively. Finally, extensive simulation studies are carried out to compare the performance of the proposed methods, and two real-life examples are analyzed for illustration. The numerical results indicate that both traditional likelihood and generalized inferential methods work satisfactorily, and that our proposed generalized approach appears much more appealing and are superior to classical results.