Reliability Class Testing and Hypothesis Specification: NBRULC−t∘ Characterizations with Applications for Medical and Engineering Data Modeling

• Published in: Axioms 2023-04, Vol.12 (5), p.414
• Main Authors: Alqifari, Hana, Eliwa, Mohamed S., Etman, Walid B. H., El-Morshedy, Mahmoud, Al-Essa, Laila A., EL-Sagheer, Rashad M.
• Format: Article
• Language: English
• Subjects: Aging; Airplane engines; Cancer; convolution; Critical point; Domains; Failure; Failure rates; Hypotheses; Hypothesis testing; increasing convex order; Jet engines; Laplace transforms; mixture; Queuing theory; Random variables; Reliability analysis; Statistical analysis; statistical model; U-statistic
• ISSN: 2075-1680; 2075-1680
• DOI: 10.3390/axioms12050414

Due to the complexity of the data being generated day in and day out in many practical domains, as a result of the development of scales for rating the success or failure of reliability, a new domain of reliability called the classes of life and determinant probability distributions has been presented. This article introduces novel statistical probability models for the reliability class of life test under different reliability processes in the age range t∘. Several probabilistic properties and features were derived and rigorously screened to test the new reliability class. According to the U-statistic, a novel hypothesis test was created to evaluate the exponentiality property. The comparative efficiency of the test according to Pitman’s asymptotic efficiency was examined and compared with other reliability classes. To prove the superiority of the new reliability class, some probability models were utilized, including the Weibull, Makeham, gamma, and linear failure rate models. Moreover, critical point simulations of the null Monte Carlo distribution and some applications of the censored and uncensored data were implemented to validate the class test listed by the reliability analysis.