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Statistical Inference for Multicomponent System Stress-Strength Model with Bounded Strengths

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Abstract

In this paper, the statistical inference for system stress-strength reliability with bounded strength is discussed. When the stress and strength variables follow the three-parameter Exponentiated-Weibull distributions with unequal scale and shape parameters, the maximum likelihood estimator (MLE) and bootstrap-p confidence interval for system reliability are derived. In addition, combining the score equations which are got by taking the first derivative of the log-likelihood function with respect to the model parameters, the modified generalized pivotal quantity for the system reliability is obtained. After that, two point estimators and a modified generalized confidence interval based on the modified generalized pivotal quantity for the system reliability are derived. Monte Carlo simulations are performed to compare the performances of the proposed point estimators and confidence intervals. Finally, a real data analysis is provided to illustrate the proposed procedures.

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Authors and Affiliations

  1. School of Economics and Management, Xidian University, Xi’an, 710126, China

    Xuchao Bai & Jian Chai

  2. School of Mathematics, Northwest University, Xi’an, 710127, China

    Jieqiong Zhang

Authors
  1. Xuchao Bai
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  2. Jieqiong Zhang
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  3. Jian Chai
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Corresponding authors

Correspondence to Xuchao Bai, Jieqiong Zhang or Jian Chai.

Additional information

This research was supported by the National Natural Science Foundation of China under Grant Nos. 12101475, 12101476, 11901134, 12061091, the Soft Science Project of Xi’an under Grant No. 22RKYJ0065, the Natural Science Basic Research Program of Shaanxi under Grant Nos. 2021JQ-186, 2020JQ-285, the Fundamental Research Funds for the Central Universities under Grant Nos. XJS210603, JGYB2222.

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Bai, X., Zhang, J. & Chai, J. Statistical Inference for Multicomponent System Stress-Strength Model with Bounded Strengths. J Syst Sci Complex 36, 755–770 (2023). https://doi.org/10.1007/s11424-023-1137-9

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  • DOI: https://doi.org/10.1007/s11424-023-1137-9

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