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Nakagami distribution as a reliability model under progressive censoring

Author

Listed:
  • Kapil Kumar

    (University of Delhi)

  • Renu Garg

    (Maharshi Dayanand University)

  • Hare Krishna

    (Ch. Charan Singh University)

Abstract

The Nakagami distribution is widely used in communication engineering. In this article we consider this distribution as a useful life time model in life testing experiments and reliability theory. Some of its distributional properties and reliability characteristics are discussed. In order to reduce cost and time of life testing experiments progressive type II censoring is used. Maximum likelihood (ML) and least square estimators of the unknown parameters and reliability characteristics are derived with progressively type II censored sample from this distribution. Interval estimation and coverage probability based on ML estimates are obtained. Monte Carlo simulation study is performed to compare various estimates developed. Findings are illustrated by three examples, two based on simulated data sets and one consisting of a real data set.

Suggested Citation

  • Kapil Kumar & Renu Garg & Hare Krishna, 2017. "Nakagami distribution as a reliability model under progressive censoring," 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. 8(1), pages 109-122, March.
    • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:1:d:10.1007_s13198-016-0494-3
    DOI: 10.1007/s13198-016-0494-3
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    References listed on IDEAS

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    1. Jacob Schwartz & Ryan T. Godwin & David E. Giles, 2011. "Improved Maximum Likelihood Estimation of the Shape Parameter in the Nakagami Distribution," Econometrics Working Papers 1109, Department of Economics, University of Victoria.
    2. Krishna, Hare & Kumar, Kapil, 2011. "Reliability estimation in Lindley distribution with progressively type II right censored sample," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(2), pages 281-294.
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    Cited by:

    1. Indrajeet Kumar & Kapil Kumar, 2022. "On estimation of $$P(V," 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. 13(1), pages 189-202, February.
    2. Ashish Kumar Shukla & Sakshi Soni & Kapil Kumar, 2023. "An inferential analysis for the Weibull-G family of distributions under progressively censored data," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1488-1524, September.
    3. Kapil Kumar, 2018. "Classical and Bayesian estimation in log-logistic distribution under random censoring," 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. 9(2), pages 440-451, April.

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