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Estimation of Stress-Strength Reliability for Multicomponent System with Rayleigh Data

Author

Listed:
  • Liang Wang

    (School of Mathematics, Yunnan Normal University, Kunming 650500, China
    These authors contributed equally to this work.)

  • Huizhong Lin

    (School of Mathematics, Yunnan Normal University, Kunming 650500, China
    These authors contributed equally to this work.)

  • Kambiz Ahmadi

    (Department of Computer Science, Faculty of Mathematical Sciences, Shahrekord University, Shahrekord 115, Iran
    These authors contributed equally to this work.)

  • Yuhlong Lio

    (Department of Mathematical Sciences, University of South Dakota, Vermillion, SD 57069, USA
    These authors contributed equally to this work.)

Abstract

Inference is investigated for a multicomponent stress-strength reliability (MSR) under Type-II censoring when the latent failure times follow two-parameter Rayleigh distribution. With a context that the lifetimes of the strength and stress variables have common location parameters, maximum likelihood estimator of MSR along with the existence and uniqueness is established. The associated approximate confidence interval is provided via the asymptotic distribution theory and delta method. Meanwhile, alternative generalized pivotal quantities-based point and confidence interval estimators are also constructed for MSR. More generally, when the lifetimes of strength and stress variables follow Rayleigh distributions with unequal location parameters, likelihood and generalized pivotal-based estimators are provided for MSR as well. In addition, to compare the equivalence of different strength and stress parameters, a likelihood ratio test is provided. Finally, simulation studies and a real data example are presented for illustration.

Suggested Citation

  • Liang Wang & Huizhong Lin & Kambiz Ahmadi & Yuhlong Lio, 2021. "Estimation of Stress-Strength Reliability for Multicomponent System with Rayleigh Data," Energies, MDPI, vol. 14(23), pages 1-23, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:23:p:7917-:d:687796
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    References listed on IDEAS

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    4. G. Srinivasa Rao & Muhammad Aslam & Debasis Kundu, 2015. "Burr-XII Distribution Parametric Estimation and Estimation of Reliability of Multicomponent Stress-Strength," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(23), pages 4953-4961, December.
    5. Sanku Dey & Josmar Mazucheli & M. Z. Anis, 2017. "Estimation of reliability of multicomponent stress–strength for a Kumaraswamy distribution," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(4), pages 1560-1572, February.
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    Cited by:

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