On Estimation of Stress-Strength Reliability Using Lower Record Values from Proportional Reversed Hazard Family

Ajit Chaturvedi; Ananya Malhotra ORCID logo; (2020) On Estimation of Stress-Strength Reliability Using Lower Record Values from Proportional Reversed Hazard Family. American Journal of Mathematical and Management Sciences, 39 (3). pp. 234-251. ISSN 0196-6324 DOI: 10.1080/01966324.2020.1722299
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In this article, a study on the stress-strength parameter (Formula presented.) based on lower record values from one parameter proportional reversed hazard family (PRHF) has been conducted. The classical and Bayesian results of Khan and Arshad (UMVU Estimation of Reliability Function and Stress-Strength Reliability from Proportional Reversed Hazard Family Based on Lower Records. American Journal of Mathematical and Management Sciences, 35(2), 171–181) and Condino et al. (Likelihood and Bayesian estimation of P(Y < X) using lower record values from a general class of distributions. Statistical Papers), when the strength (Formula presented.) and stress (Formula presented.) variables belong to different family of distributions from PRHF have been generalized. Uniformly minimum variance unbiased estimator (UMVUE), maximum likelihood estimator (MLE) and Bayes estimator (BE) are obtained for the powers of the parameter and reliability functions (Formula presented.) and (Formula presented.) The estimators of three parametric functions, namely, powers of parameter, (Formula presented.) and (Formula presented.) are interrelated, whereas, in the literature, researchers have handled the three estimation problems separately. Moreover, it is has been shown that the expressions for (Formula presented.) and (Formula presented.) are not required to estimate them. In this article, the technique of obtaining estimators of (Formula presented.) and (Formula presented.) is simpler as it does not require Rao-Blackwellization. Simulation studies have been performed for analyzing the behavior of the proposed estimators. An example using real data has also been considered as an illustration.

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