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One- and two-sample Bayesian prediction intervals based on progressively Type-II censored data

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  • M. El-Din
  • A. Shafay

Abstract

In this article, one- and two-sample Bayesian prediction intervals based on progressively Type-II censored data are derived. For the illustration of the developed results, the exponential, Pareto, Weibull and Burr Type-XII models are used as examples. Some of the previous results in the literature such as Dunsmore (Technometrics 16:455–460, 1974 ), Nigm and Hamdy (Commun Stat Theory Methods 16:1761–1772, 1987 ), Nigm (Commun Stat Theory Methods 18:897–911, 1989 ), Al-Hussaini and Jaheen (Commun Stat Theory Methods 24:1829–1842, 1995 ), Al-Hussaini (J Stat Plan Inference 79:79–91, 1999 ), Ali Mousa (J Stat Comput Simul 71: 163–181, 2001 ) and Ali Mousa and Jaheen (Stat Pap 43:587–593, 2002 ) can be achieved as special cases of our results. Finally, some numerical computations are presented for illustrating all the proposed inferential procedures. Copyright Springer-Verlag 2013

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  • M. El-Din & A. Shafay, 2013. "One- and two-sample Bayesian prediction intervals based on progressively Type-II censored data," Statistical Papers, Springer, vol. 54(2), pages 287-307, May.
    • Handle: RePEc:spr:stpapr:v:54:y:2013:i:2:p:287-307
    DOI: 10.1007/s00362-011-0426-x
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    References listed on IDEAS

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    1. N. Balakrishnan, 2007. "Progressive censoring methodology: an appraisal," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(2), pages 211-259, August.
    2. Shuo‐Jye Wu & Dar‐Hsin Chen & Shyi‐Tien Chen, 2006. "Bayesian inference for Rayleigh distribution under progressive censored sample," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 22(3), pages 269-279, May.
    3. Balakrishnan, N. & Childs, A. & Chandrasekar, B., 2002. "An efficient computational method for moments of order statistics under progressive censoring," Statistics & Probability Letters, Elsevier, vol. 60(4), pages 359-365, December.
    4. M. Mousa & Z. Jaheen, 2002. "Bayesian prediction for progressively censored data from the Burr model," Statistical Papers, Springer, vol. 43(4), pages 587-593, October.
    5. Basak, Indrani & Basak, Prasanta & Balakrishnan, N., 2006. "On some predictors of times to failure of censored items in progressively censored samples," Computational Statistics & Data Analysis, Elsevier, vol. 50(5), pages 1313-1337, March.
    6. Zeinab Amin, 2008. "Bayesian inference for the Pareto lifetime model under progressive censoring with binomial removals," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(11), pages 1203-1217.
    7. Raqab, Mohammad Z. & Asgharzadeh, A. & Valiollahi, R., 2010. "Prediction for Pareto distribution based on progressively Type-II censored samples," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1732-1743, July.
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    Cited by:

    1. Lasanthi C. R. Pelawa Watagoda & David J. Olive, 2021. "Comparing six shrinkage estimators with large sample theory and asymptotically optimal prediction intervals," Statistical Papers, Springer, vol. 62(5), pages 2407-2431, October.
    2. Uoseph Hamdi Salemi & Esmaile Khorram & Yuancheng Si & Saralees Nadarajah, 2020. "Sensitivity analysis of censoring schemes in progressively type-II right censored order statistics," OPSEARCH, Springer;Operational Research Society of India, vol. 57(1), pages 163-189, March.
    3. Essam AL-Hussaini & Alaa Abdel-Hamid & Atef Hashem, 2015. "One-sample Bayesian prediction intervals based on progressively type-II censored data from the half-logistic distribution under progressive stress model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(7), pages 771-783, October.
    4. M. M. Mohie El-Din & A. R. Shafay & M. Nagy, 2018. "Statistical inference under adaptive progressive censoring scheme," Computational Statistics, Springer, vol. 33(1), pages 31-74, March.
    5. Kotb, M.S. & Raqab, M.Z., 2019. "Statistical inference for modified Weibull distribution based on progressively type-II censored data," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 162(C), pages 233-248.
    6. M. M. Mohie El-Din & M. Nagy & M. H. Abu-Moussa, 2019. "Estimation and Prediction for Gompertz Distribution Under the Generalized Progressive Hybrid Censored Data," Annals of Data Science, Springer, vol. 6(4), pages 673-705, December.
    7. David J. Olive, 2018. "Applications of hyperellipsoidal prediction regions," Statistical Papers, Springer, vol. 59(3), pages 913-931, September.
    8. Uoseph Hamdi Salemi & Sadegh Rezaei & Saralees Nadarajah, 2019. "A-optimal and D-optimal censoring plans in progressively Type-II right censored order statistics," Statistical Papers, Springer, vol. 60(4), pages 1349-1367, August.

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