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Inference on stress-strength reliability for the two-parameter exponential distribution based on generalized order statistics

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  • Ali Akbar Jafari
  • Saeede Bafekri

Abstract

Stress-strength reliability is a measure to compare the lifetimes of two systems. It is inferred for the two-parameter exponential distribution using generalized order statistics first without constraint on the location and scale parameters, second when the scale parameters are equal. A generalized confidence interval, bootstrap confidence intervals, a Bayesian interval, and a highest posterior density interval are computed for the stress-strength parameter. A Monte Carlo simulation shows that generalized confidence intervals provide more accurate average lengths of confidence intervals and higher probabilities to contain the true value of the parameter. Application: Confidence intervals for the time to remission of 20 leukemic patients treated with one of two drugs are approximately the same in most generalized statistical models. In addition, the time to remission for patients with the first drug is tested to be shorter than for patients with the second drug.

Suggested Citation

  • Ali Akbar Jafari & Saeede Bafekri, 2021. "Inference on stress-strength reliability for the two-parameter exponential distribution based on generalized order statistics," Mathematical Population Studies, Taylor & Francis Journals, vol. 28(4), pages 201-227, October.
    • Handle: RePEc:taf:mpopst:v:28:y:2021:i:4:p:201-227
    DOI: 10.1080/08898480.2021.1872230
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    Cited by:

    1. Weizhong Tian & Chengliang Tian & Sha Li & Yunchu Zhang & Jiayi Han, 2024. "Fuzzy Stress and Strength Reliability Based on the Generalized Mixture Exponential Distribution," Mathematics, MDPI, vol. 12(17), pages 1-15, August.

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