Stress-strength reliability estimation for bivariate copula function with rayleigh marginals

A. James, N. Chandra () and Nicy Sebastian
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A. James: Ramanujan School of Mathematical Sciences, Pondicherry University
N. Chandra: Ramanujan School of Mathematical Sciences, Pondicherry University
Nicy Sebastian: St Thomas College

International Journal of System Assurance Engineering and Management, 2023, vol. 14, issue 1, No 13, 196-215

Abstract: Abstract In the classical stress-strength reliability model, the majority of the contributions focus on estimating system reliability with independent assumptions of stress and strength. In many real applications, such an assumption is violated because more or less dependence relations exist. Therefore, attempting dependent stress-strength reliability modelling is interesting. In this article, we assume stress and strength are linked by Fralie–Gumble–Morgenstern copula with Rayleigh marginals as the underlying distribution. The estimates of reliability and dependence parameters are obtained by using maximum likelihood estimation, inference function margin, and semi-parametric methods. In addition, the length of confidence interval and coverage probability of the dependence parameter are also reported. The performance of the proposed methods is shown by using Monte-Carlo simulation as well as three distinct real-life data sets.

Keywords: Dependence stress-strength reliability; Rayleigh distribution; Fralie–Gumble–Morgenstern copula; Maximum likelihood estimation; Inference function margins; Semi-parametric method; 62H20; 62H05 (search for similar items in EconPapers)
JEL-codes: C13 C61 C63 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s13198-022-01836-6

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