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Statistical Inference and Optimum Life Testing Plans Under Type-II Hybrid Censoring Scheme

Author

Listed:
  • Tanmay Sen

    (Indian Institute of Technology Patna)

  • Yogesh Mani Tripathi

    (Indian Institute of Technology Patna)

  • Ritwik Bhattacharya

    (Centro de Investigación en Matemáticas (CIMAT))

Abstract

This article considers estimation of unknown parameters and prediction of future observations of a generalized exponential distribution based on Type-II hybrid censored data. Bayes point and HPD interval estimates of the unknown parameters are obtained under the assumption of independent gamma priors. Different classical and Bayesian point predictors and prediction intervals are obtained in two-sample situation against squared error loss function. The optimum censoring schemes are computed under various optimality criteria. Monte Carlo simulations are performed to compare different methods and two data sets are analyzed for illustrative purposes.

Suggested Citation

  • Tanmay Sen & Yogesh Mani Tripathi & Ritwik Bhattacharya, 2018. "Statistical Inference and Optimum Life Testing Plans Under Type-II Hybrid Censoring Scheme," Annals of Data Science, Springer, vol. 5(4), pages 679-708, December.
    • Handle: RePEc:spr:aodasc:v:5:y:2018:i:4:d:10.1007_s40745-018-0158-z
    DOI: 10.1007/s40745-018-0158-z
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    References listed on IDEAS

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    1. Park, Sangun & Balakrishnan, N., 2009. "On simple calculation of the Fisher information in hybrid censoring schemes," Statistics & Probability Letters, Elsevier, vol. 79(10), pages 1311-1319, May.
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    4. Biswabrata Pradhan & Debasis Kundu, 2009. "On progressively censored generalized exponential distribution," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(3), pages 497-515, November.
    5. A. Childs & B. Chandrasekar & N. Balakrishnan & D. Kundu, 2003. "Exact likelihood inference based on Type-I and Type-II hybrid censored samples from the exponential distribution," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(2), pages 319-330, June.
    6. M. Nassar & S. G. Nassr & S. Dey, 2017. "Analysis of Burr Type-XII Distribution Under Step Stress Partially Accelerated Life Tests with Type-I and Adaptive Type-II Progressively Hybrid Censoring Schemes," Annals of Data Science, Springer, vol. 4(2), pages 227-248, June.
    7. Manoj Rastogi & Yogesh Tripathi, 2013. "Inference on unknown parameters of a Burr distribution under hybrid censoring," Statistical Papers, Springer, vol. 54(3), pages 619-643, August.
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    1. Ahmed Elshahhat & Osama E. Abo-Kasem & Heba S. Mohammed, 2023. "Survival Analysis of the PRC Model from Adaptive Progressively Hybrid Type-II Censoring and Its Engineering Applications," Mathematics, MDPI, vol. 11(14), pages 1-26, July.
    2. Samir K. Ashour & Ahmed A. El-Sheikh & Ahmed Elshahhat, 2022. "Inferences and Optimal Censoring Schemes for Progressively First-Failure Censored Nadarajah-Haghighi Distribution," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 885-923, August.
    3. Devendra Kumar & M. Nassar & Sanku Dey, 2023. "Progressive Type-II Censored Data and Associated Inference with Application Based on Li–Li Rayleigh Distribution," Annals of Data Science, Springer, vol. 10(1), pages 43-71, February.

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