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Bayesian Prediction Bounds for the Exponential-type Distribution Based on Generalized Progressive Hybrid Censoring Scheme

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  • Kotb Mohammed S.

    (Department of Mathematics, Faculty of Science, Al-Azhar University, Nasr City, Cairo11884, Egypt; and Department of Mathematics, Al-Baha University, Saudi Arabia)

Abstract

This paper deals with predicting censored data in a general form for the underlying distribution based on generalized progressive hybrid censoring scheme. A conjugate prior is used and the predictive reliability function is obtained in the one-sample case. The special case of linear exponential distributed observations is considered and completed with numerical results.

Suggested Citation

  • Kotb Mohammed S., 2018. "Bayesian Prediction Bounds for the Exponential-type Distribution Based on Generalized Progressive Hybrid Censoring Scheme," Stochastics and Quality Control, De Gruyter, vol. 33(2), pages 93-101, December.
    • Handle: RePEc:bpj:ecqcon:v:33:y:2018:i:2:p:93-101:n:3
    DOI: 10.1515/eqc-2018-0012
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    References listed on IDEAS

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    1. Kundu, Debasis & Joarder, Avijit, 2006. "Analysis of Type-II progressively hybrid censored data," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2509-2528, June.
    2. Arnab Koley & Debasis Kundu, 2017. "On generalized progressive hybrid censoring in presence of competing risks," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(4), pages 401-426, May.
    3. Lin, Chien-Tai & Chou, Cheng-Chieh & Huang, Yen-Lung, 2012. "Inference for the Weibull distribution with progressive hybrid censoring," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 451-467.
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