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Reliability estimation in multicomponent stress–strength model for generalized inverted exponential distribution

  • Mathematical methods in data science
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Abstract

The problem reliability estimation of multicomponent stress–strength system is studied in this paper, when the strength components and stress component follow generalized inverted exponential distributions under progressive first failure censored data. Point estimate of reliability in a multicomponent stress–strength model is derived by using maximum likelihood and Bayes methods. We construct the asymptotic confidence interval and highest posterior density credible interval. Two bootstrap confidence intervals are proposed. The performances of the different estimation algorithms are assessed by the Monte Carlo simulations. Carbon fiber strength data and data on water capacity of the Shasta reservoir have been analyzed for the purpose of illustration.

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Acknowledgements

Basic Scientific Research Expenses Program of Universities directly under Inner Mongolia Autonomous Region (Grant No. JY20220165; JY20220083; JY20220087).

Funding

The work was funded by the National Natural Science Foundation of China (Grant No. 11861049; 81860605), Natural Science Foundation of Inner Mongolia (Grant No. 2020LH01002), and Inner Mongolia University of Science and Technology (Grant No. BS2020029).

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Authors and Affiliations

  1. Science College, Inner Mongolia University of Technology, Hohhot, 010051, People’s Republic of China

    Junmei Jia, Zaizai Yan & Haohao Song

  2. Institute of Mathematics and Statistics, Wuhan University, Wuhan, 430072, People’s Republic of China

    Yan Chen

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  1. Junmei Jia
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  2. Zaizai Yan
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  3. Haohao Song
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  4. Yan Chen
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Correspondence to Zaizai Yan.

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Jia, J., Yan, Z., Song, H. et al. Reliability estimation in multicomponent stress–strength model for generalized inverted exponential distribution. Soft Comput 27, 903–916 (2023). https://doi.org/10.1007/s00500-022-07628-1

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