On the reliability estimation of multicomponent stress-strength model for Burr XII distribution using progressively first-failure censored samples

• Published in: Journal of statistical computation and simulation Vol. 92; no. 4; pp. 667 - 704
• Main Authors: Saini, Shubham, Tomer, Sachin, Garg, Renu
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 04-03-2022
• Subjects: Bayesian estimator; Burr XII distribution; Monte Carlo simulation; multicomponent stress-strength; point estimation; Progressive first failure censoring
• ISSN: 0094-9655; 1563-5163
• DOI: 10.1080/00949655.2021.1970165

In this article, we consider the classical and Bayesian estimation of the multicomponent stress-strength reliability (MSSR) for the Burr XII distribution based on progressively first-failure censored samples. Both stress and strength random variables follow Burr XII distribution with common first shape parameter. The maximum likelihood estimator, asymptotic, boot-p and boot-t confidence interval of MSSR are studied. The Bayes estimator along with the Bayesian credible and highest posterior density credible intervals are derived. The uniformly minimum variance unbiased estimator of MSSR is discussed. A simulation study is performed to illustrate the proposed censoring and different estimation methods. At the end, two different real data sets are analysed for comparing different censoring schemes and estimation methods.