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Estimation of $$ P[Y

Author

Listed:
  • Dipak D. Patil

    (Haribhai V. Desai College)

  • U. V. Naik-Nimbalkar

    (Savitribai Phule Pune University)

  • M. M. Kale

    (Savitribai Phule Pune University)

Abstract

The stress–strength model is a basic tool used in evaluating the reliability $$ R = P(Y

Suggested Citation

  • Dipak D. Patil & U. V. Naik-Nimbalkar & M. M. Kale, 2024. "Estimation of $$ P[Y," Annals of Data Science, Springer, vol. 11(4), pages 1303-1340, August.
    • Handle: RePEc:spr:aodasc:v:11:y:2024:i:4:d:10.1007_s40745-023-00487-z
    DOI: 10.1007/s40745-023-00487-z
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    References listed on IDEAS

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    1. James M. Tien, 2017. "Internet of Things, Real-Time Decision Making, and Artificial Intelligence," Annals of Data Science, Springer, vol. 4(2), pages 149-178, June.
    2. Friedrich Schmid & Rafael Schmidt, 2007. "Nonparametric inference on multivariate versions of Blomqvist’s beta and related measures of tail dependence," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 66(3), pages 323-354, November.
    3. Thomas Xavier & Joby K. Jose, 2022. "Stress–strength reliability estimation involving paired observation with ties using bivariate exponentiated half-logistic model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 49(5), pages 1049-1064, April.
    4. Filippo Domma & Sabrina Giordano, 2013. "A copula-based approach to account for dependence in stress-strength models," Statistical Papers, Springer, vol. 54(3), pages 807-826, August.
    Full references (including those not matched with items on IDEAS)

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