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<p>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.</p>

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

  • 期刊论文

  • 发表日期：

    2025年3月26日

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  • Chatany Swaroop,
  • Subhankar Dutta,
  • Shubham Saini,
  • Neeraj Tiwari

摘要

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.