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The evaluation of bivariate normal probabilities for failure of parallel systems

Author

Listed:
  • Yuge Dong

    (Hefei University of Technology)

  • Qingtong Xie

    (Hefei University of Technology)

  • Shuguang Ding

    (Hefei University of Technology)

  • Liangguo He

    (Hefei University of Technology)

  • Hu Wang

    (Hefei University of Technology)

Abstract

A method for computing the joint failure probability of a parallel system consisting of two linear limit state equations is given to indirectly obtain the value of the integral of the standard bivariate normal distribution by using the conclusion that the joint failure probability of the parallel system is equal to the value of the double integral. In the two-dimensional standard normal coordinate system, some circles whose centres are all at the coordinate origin are used to divide the two-dimensional standard sample space into a number of pairwise disjoint sub-sample spaces and obtain a number of pairwise disjoint sub-failure domains. According to the probability theory, the probability of any sub-failure domain can be expressed by using a sub-sample space probability and a conditional probability. Based on the total probability formula, the joint failure probability can be obtained by the sum of the probabilities of the sub-failure domains because the sub-sample spaces or the sub-failure domains are pairwise disjoint. By introducing a random variable obeying the Rayleigh distribution, it is possible to compute probabilities of the sub-sample spaces accurately. The formulae of computing the conditional probability are derived. The main parameters related to the computation of the joint failure probability, such as the minimum and maximum radii, and the number of the dividing circles, are discussed to make the computation process easy and the computed result meet a required precision. Examples show that it is possible and significant for the method in the paper to complete the computation of the standard bivariate normal distribution integral with high accuracy.

Suggested Citation

  • Yuge Dong & Qingtong Xie & Shuguang Ding & Liangguo He & Hu Wang, 2022. "The evaluation of bivariate normal probabilities for failure of parallel systems," Statistical Papers, Springer, vol. 63(5), pages 1585-1614, October.
  • Handle: RePEc:spr:stpapr:v:63:y:2022:i:5:d:10.1007_s00362-021-01282-9
    DOI: 10.1007/s00362-021-01282-9
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    References listed on IDEAS

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    1. J. C. Young & Ch. E. Minder, 1974. "An Integral Useful in Calculating Non‐Central T and Bivariate Normal Probabilities," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 23(3), pages 455-457, November.
    2. Albers, W. & Kallenberg, W. C. M., 1994. "A Simple Approximation to the Bivariate Normal Distribution with Large Correlation Coefficient," Journal of Multivariate Analysis, Elsevier, vol. 49(1), pages 87-96, April.
    3. Yuge Dong & Haimeng Zhang & Liangguo He & Can Wang & Minghui Wang, 2019. "The computation of standard normal distribution integral in any required precision based on reliability method," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(6), pages 1517-1528, March.
    4. Kim, Jongphil, 2013. "The computation of bivariate normal and t probabilities, with application to comparisons of three normal means," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 177-186.
    5. D. J. Daley, 1974. "Computation of Bi‐ and Tri‐Variate Normal Integrals," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 23(3), pages 435-438, November.
    6. Vijverberg, Wim P. M., 1997. "Monte Carlo evaluation of multivariate normal probabilities," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 281-307.
    7. Ajit Kumar Verma & Srividya Ajit & Durga Rao Karanki, 2016. "Reliability and Safety Engineering," Springer Series in Reliability Engineering, Springer, edition 2, number 978-1-4471-6269-8, March.
    8. Davaadorjin Monhor, 2011. "A new probabilistic approach to the path criticality in stochastic PERT," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 19(4), pages 615-633, December.
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