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Statistical Analysis Under Geometric Process in Accelerated Life Testing Plans for Generalized Exponential Distribution

Author

Listed:
  • Showkat Ahmad Lone

    (Saudi Electronic University)

  • Intekhab Alam

    (St. Andrews Institute of Technology and Management)

  • Ahmadur Rahman

    (Aligarh Muslim University)

Abstract

The geometric process (GP) is used to conduct a statistical analysis of accelerated life testing under constant stress using type-I censored data for the Generalized Exponential failure distribution. The lifespan of test items forms a GP as stress levels increases. The technique of maximum likelihood estimation is used to estimate the parameters. To determine the asymptotic variance of maximum likelihood estimators, the Fisher information matrix is constructed. This asymptotic variance is then used to provide asymptotic interval estimates for the distribution parameters. Finally, a simulation approach is used to demonstrate the parameters' statistical properties and confidence ranges.

Suggested Citation

  • Showkat Ahmad Lone & Intekhab Alam & Ahmadur Rahman, 2023. "Statistical Analysis Under Geometric Process in Accelerated Life Testing Plans for Generalized Exponential Distribution," Annals of Data Science, Springer, vol. 10(6), pages 1653-1665, December.
    • Handle: RePEc:spr:aodasc:v:10:y:2023:i:6:d:10.1007_s40745-022-00397-6
    DOI: 10.1007/s40745-022-00397-6
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    References listed on IDEAS

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    1. Yeh Lam & Yuan Lin Zhang, 1996. "Analysis of a two‐component series system with a geometric process model," Naval Research Logistics (NRL), John Wiley & Sons, vol. 43(4), pages 491-502, June.
    2. James M. Tien, 2017. "Internet of Things, Real-Time Decision Making, and Artificial Intelligence," Annals of Data Science, Springer, vol. 4(2), pages 149-178, June.
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