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Reliability estimation for inverse Pareto lifetime model based on unified hybrid censored data

Author

Listed:
  • Kapil Kumar

    (Central University of Haryana)

  • Shrawan Kumar

    (Kirori Mal College)

  • Renu Garg

    (Ramanujan College)

  • Indrajeet Kumar

    (Central University of South Bihar)

Abstract

Censoring plays an important role in the reliability and life testing trials due to its cost optimality and time reduction properties. The unified hybrid censoring scheme is the combination of the generalized type-I and type-II hybrid censoring schemes. In this paper, our objective is to study the classical and Bayesian estimation methods of the parameter and reliability characteristics from the inverse Pareto lifetime model under the unified hybrid censoring scheme. In the classical estimation methods, the maximum likelihood and associated asymptotic confidence interval estimators are derived. In Bayesian estimation, the Bayes estimators under squared error loss function and the highest posterior density (HPD) credible intervals based on the informative and non-informative priors are developed. For the Bayesian computations, the Markov chain Monte Carlo techniques are used to compute Bayes and HPD credible interval estimates. A quantitative outcome of the objectives has been shown by a Monte Carlo simulation and with the help of a real-life application.

Suggested Citation

  • Kapil Kumar & Shrawan Kumar & Renu Garg & Indrajeet Kumar, 2024. "Reliability estimation for inverse Pareto lifetime model based on unified hybrid censored data," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(6), pages 2473-2482, June.
    • Handle: RePEc:spr:ijsaem:v:15:y:2024:i:6:d:10.1007_s13198-024-02265-3
    DOI: 10.1007/s13198-024-02265-3
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    References listed on IDEAS

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    1. Balakrishnan, N. & Kundu, Debasis, 2013. "Hybrid censoring: Models, inferential results and applications," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 166-209.
    2. Safari, Muhammad Aslam Mohd & Masseran, Nurulkamal & Ibrahim, Kamarulzaman & Hussain, Saiful Izzuan, 2019. "A robust and efficient estimator for the tail index of inverse Pareto distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 431-439.
    3. Bahman Arasteh & Saideh Khosroshahizadeh, 2020. "Software reliability enhancement against hardware transient errors using inherently reliable data structures," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(5), pages 883-898, October.
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