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Bayesian inference for Poisson-inverse exponential distribution under progressive type-II censoring with binomial removal

Author

Listed:
  • Manoj Kumar

    (Central University of Haryana)

  • Sanjay Kumar Singh

    (Banaras Hindu University)

  • Umesh Singh

    (Banaras Hindu University)

Abstract

This paper proposes a Poisson-inverse exponential distribution (PIED) as a lifetime model with initially increasing then decreasing failure model. Its statistical characteristics and important distributional properties are discussed along with its reliability and failure rate function. The maximum likelihood estimators (MLEs) and Bayes estimators of parameters of PIED under symmetric and asymmetric loss functions for progressive type-II censored data with binomial removals have been obtained. The MLEs and corresponding Bayes estimators are compared in terms of their simulated risks. The proposed methodology is illustrated through a real data set of bladder cancer.

Suggested Citation

  • Manoj Kumar & Sanjay Kumar Singh & Umesh Singh, 2018. "Bayesian inference for Poisson-inverse exponential distribution under progressive type-II censoring with binomial removal," 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(6), pages 1235-1249, December.
    • Handle: RePEc:spr:ijsaem:v:9:y:2018:i:6:d:10.1007_s13198-018-0704-2
    DOI: 10.1007/s13198-018-0704-2
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    References listed on IDEAS

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    1. Cancho, Vicente G. & Louzada-Neto, Franscisco & Barriga, Gladys D.C., 2011. "The Poisson-exponential lifetime distribution," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 677-686, January.
    2. Francisco Louzada-Neto & Vicente G. Cancho & Gladys D.C. Barriga, 2011. "The Poisson--exponential distribution: a Bayesian approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(6), pages 1239-1248, April.
    3. Ng, H. K. T. & Chan, P. S. & Balakrishnan, N., 2002. "Estimation of parameters from progressively censored data using EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 39(4), pages 371-386, June.
    4. Barreto-Souza, Wagner & Cribari-Neto, Francisco, 2009. "A generalization of the exponential-Poisson distribution," Statistics & Probability Letters, Elsevier, vol. 79(24), pages 2493-2500, December.
    5. Kus, Coskun, 2007. "A new lifetime distribution," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4497-4509, May.
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    Citations

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    Cited by:

    1. Kousik Maiti & Suchandan Kayal, 2019. "Estimation for the generalized Fréchet distribution under progressive censoring scheme," 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(5), pages 1276-1301, October.
    2. Anurag Pathak & Manoj Kumar & Sanjay Kumar Singh & Umesh Singh & Manoj Kumar Tiwari & Sandeep Kumar, 2022. "Bayesian inference for Maxwell Boltzmann distribution on step-stress partially accelerated life test under progressive type-II censoring with binomial removals," 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(4), pages 1976-2010, August.
    3. 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.

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    Keywords

    PIED; PT-II CBRs; SELF; GELF;
    All these keywords.

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