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Estimation of stress–strength reliability for the generalized inverted exponential distribution based on improved adaptive Type-II progressive censoring

Author

Listed:
  • Chatany Swaroop

    (Soban Singh Jeena University)

  • Subhankar Dutta

    (Maulana Azad National Institute of Technology)

  • Shubham Saini

    (Chaudhary Charan Singh University)

  • Neeraj Tiwari

    (Soban Singh Jeena University)

Abstract

This study aims to estimate the reliability of a stress–strength system using the generalized inverted exponential distribution (GIED). We achieve this by employing an improved adaptive Type-II progressive censoring scheme and utilizing various estimation techniques. The techniques used include maximum likelihood estimation through the EM algorithm and Bayesian inference. We use Markov chain Monte Carlo (MCMC) methods and TK approximation in the Bayesian framework. We compute various intervals, such as asymptotic confidence, arcsin transformed, Bayesian credible, and higher posterior density confidence intervals. To guide the estimation process, we use a generalized entropy loss function. Additionally, we conduct a comprehensive simulation analysis to validate the method’s performance and rigorously assess its applicability through real-life data analysis.

Suggested Citation

  • Chatany Swaroop & Subhankar Dutta & Shubham Saini & Neeraj Tiwari, 2025. "Estimation of stress–strength reliability for the generalized inverted exponential distribution based on improved adaptive Type-II progressive censoring," Computational Statistics, Springer, vol. 40(7), pages 3781-3817, September.
    • Handle: RePEc:spr:compst:v:40:y:2025:i:7:d:10.1007_s00180-025-01612-7
    DOI: 10.1007/s00180-025-01612-7
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    References listed on IDEAS

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    1. Subhankar Dutta & Sanku Dey & Suchandan Kayal, 2024. "Bayesian survival analysis of logistic exponential distribution for adaptive progressive Type-II censored data," Computational Statistics, Springer, vol. 39(4), pages 2109-2155, June.
    2. Kundu, Debasis & Joarder, Avijit, 2006. "Analysis of Type-II progressively hybrid censored data," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2509-2528, June.
    3. Hon Keung Tony Ng & Debasis Kundu & Ping Shing Chan, 2009. "Statistical analysis of exponential lifetimes under an adaptive Type‐II progressive censoring scheme," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(8), pages 687-698, December.
    4. Ng, H. K. T. & Chan, P. S. & Balakrishnan, N., 2002. "Estimation of parameters from progressively censored data using EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 39(4), pages 371-386, June.
    5. Subhankar Dutta & Suchandan Kayal, 2023. "Inference of a competing risks model with partially observed failure causes under improved adaptive type-II progressive censoring," Journal of Risk and Reliability, , vol. 237(4), pages 765-780, August.
    6. Joby K. Jose & M. Drisya, 2020. "Time-dependent stress–strength reliability models based on phase type distribution," Computational Statistics, Springer, vol. 35(3), pages 1345-1371, September.
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