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Classical and Bayesian estimation in log-logistic distribution under random censoring

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  • Kapil Kumar

    (Central University of Haryana)

Abstract

This article deals with the classical and Bayesian estimation of the parameters of log-logistic distribution using random censorship model. The maximum likelihood estimators and the asymptotic confidence intervals based on observed Fisher information matrix of the parameters are derived. Bayes estimators of the parameters under generalized entropy loss function using independent gamma priors are obtained. For Bayesian computation, Tierney–Kadane’s approximation and Markov chain Monte Carlo (MCMC) methods are used. Also, the highest posterior credible intervals of the parameters based on MCMC method are constructed. A Monte Carlo simulation study is carried out to compare the behavior of various estimators developed in this article. Finally, a real data analysis is performed for illustration purposes.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:ijsaem:v:9:y:2018:i:2:d:10.1007_s13198-017-0688-3
    DOI: 10.1007/s13198-017-0688-3
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    References listed on IDEAS

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    1. Muhammad Danish & Muhammad Aslam, 2013. "Bayesian estimation for randomly censored generalized exponential distribution under asymmetric loss functions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(5), pages 1106-1119.
    2. M. Ghitany, 2001. "A compound Rayleigh survival model and its application to randomly censored data," Statistical Papers, Springer, vol. 42(4), pages 437-450, October.
    3. Ameraoui, Abdelkader & Boukhetala, Kamal & Dupuy, Jean-François, 2016. "Bayesian estimation of the tail index of a heavy tailed distribution under random censoring," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 148-168.
    4. R. R. L. Kantam & K. Rosaiah & G. Srinivasa Rao, 2001. "Acceptance sampling based on life tests: Log-logistic model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(1), pages 121-128.
    5. R. R. L. Kantam & G. Srinivasa Rao & B. Sriram, 2006. "An economic reliability test plan: Log-logistic distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(3), pages 291-296.
    6. Arnold, Barry C. & Press, S. James, 1983. "Bayesian inference for pareto populations," Journal of Econometrics, Elsevier, vol. 21(3), pages 287-306, April.
    7. 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.
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    Cited by:

    1. Rajni Goel & Hare Krishna, 2024. "A study of accidental breakages in progressively type-ii censored lifetime experiments," 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 2105-2119, June.
    2. 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.
    3. Kousik Maiti & Suchandan Kayal, 2023. "Estimating Reliability Characteristics of the Log-Logistic Distribution Under Progressive Censoring with Two Applications," Annals of Data Science, Springer, vol. 10(1), pages 89-128, February.
    4. Hanieh Panahi, 2019. "Estimation for the parameters of the Burr Type XII distribution under doubly censored sample with application to microfluidics 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. 10(4), pages 510-518, August.
    5. Hare Krishna & Rajni Goel, 2024. "Inferences Based on Correlated Randomly Censored Gumbel’s Type-I Bivariate Exponential Distribution," Annals of Data Science, Springer, vol. 11(4), pages 1185-1207, August.
    6. Indrajeet Kumar & Shishir Kumar Jha & Kapil Kumar, 2023. "On Some Estimation Methods for the Inverse Pareto Distribution," Annals of Data Science, Springer, vol. 10(4), pages 1035-1068, August.

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