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- W3121026600 abstract "In this paper, we propose using the q-Weibull distribution to directly model the failure time of a series system composed of dependent components, discuss the connection between the q-Weibull distribution and the Clayton copula, and show that their parameters are equivalent. Moreover, we propose a Nonhomogeneous Poisson Process with q-Weibull as the underlying time to first failure distribution for reliability analysis of a series system composed of dependent components. The proposed model has fewer parameters and is an approximation to the Clayton copula approach. The maximum likelihood estimators are developed for the parameters of the proposed model. Confidence intervals based on the maximum likelihood asymptotic theory are also developed. The results of simulation experiments demonstrate the accuracy of the proposed model; moreover, estimating the parameters of the proposed model does not require information about which components failed, which is necessary for accurately estimating the parameters of the Clayton model. The procedure is applied to a data set of real failure times for a load-haul-dump machine that is characterized by a bathtub-shaped hazard rate." @default.
- W3121026600 created "2021-01-18" @default.
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- W3121026600 date "2021-06-01" @default.
- W3121026600 modified "2023-10-16" @default.
- W3121026600 title "Modeling dependent series systems with q-Weibull distribution and Clayton copula" @default.
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- W3121026600 doi "https://doi.org/10.1016/j.apm.2020.12.042" @default.
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