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Analysis of Burr Type-XII Distribution Under Step Stress Partially Accelerated Life Tests with Type-I and Adaptive Type-II Progressively Hybrid Censoring Schemes

Author

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  • M. Nassar

    (Zagazig University)

  • S. G. Nassr

    (Sinai University)

  • S. Dey

    (St. Anthony’s College)

Abstract

In this paper, we investigate the maximum likelihood estimation of the unknown parameters of the Burr Type-XII distribution and the acceleration factor based on two different progressively hybrid censoring schemes, namely, Type-I progressive hybrid censoring scheme (T-I PHCS) proposed by Kundu and Joarder (Comput Stat Data Anal 50:2509–2528, 2006) and adaptive Type-II progressive hybrid censoring scheme (AT-II PHCS) introduced by Ng et al. (Nav Res Logist 56:687–698, 2009) under step-stress partially accelerated life test model. The observed Fisher information matrix is obtained to construct an approximate confidence interval for the unknown parameters. The performances of the estimators of the model parameters using the above mentioned progressively hybrid censoring schemes are evaluated and compared in terms of the mean squared errors and relative errors through a Monte Carlo simulation study.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:aodasc:v:4:y:2017:i:2:d:10.1007_s40745-017-0101-8
    DOI: 10.1007/s40745-017-0101-8
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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. 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.
    3. Abdel-Hamid, Alaa H., 2009. "Constant-partially accelerated life tests for Burr type-XII distribution with progressive type-II censoring," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2511-2523, May.
    4. Balakrishnan, N. & Kundu, Debasis, 2013. "Hybrid censoring: Models, inferential results and applications," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 166-209.
    5. N. Balakrishnan, 2007. "Rejoinder on: 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 290-296, August.
    6. Morris H. Degroot & Prem K. Goel, 1979. "Bayesian estimation and optimal designs in partially accelerated life testing," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 26(2), pages 223-235, June.
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    Cited by:

    1. Refah Alotaibi & Ehab M. Almetwally & Qiuchen Hai & Hoda Rezk, 2022. "Optimal Test Plan of Step Stress Partially Accelerated Life Testing for Alpha Power Inverse Weibull Distribution under Adaptive Progressive Hybrid Censored Data and Different Loss Functions," Mathematics, MDPI, vol. 10(24), pages 1-24, December.
    2. 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.

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