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Inference for Weibull distribution under generalized order statistics

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  • Aboeleneen, Z.A.

Abstract

Based on generalized order statistics from Weibull distribution the approach of Bayesian and non-Bayesian estimation are discussed. We present a simple and efficient simulational algorithm for generating a generalized order statistics sample from any continuous distribution. Specializations to Bayesian and non-Bayesian estimators, some lifetime parameters and confidence intervals of progressive II censoring and record values are obtained and compared with the existing results. Two examples are given to illustrate the proposed estimators and the simulation algorithm.

Suggested Citation

  • Aboeleneen, Z.A., 2010. "Inference for Weibull distribution under generalized order statistics," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(1), pages 26-36.
    • Handle: RePEc:eee:matcom:v:81:y:2010:i:1:p:26-36
    DOI: 10.1016/j.matcom.2010.06.013
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    References listed on IDEAS

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    1. Soliman, Ahmed A. & Al-Aboud, Fahad M., 2008. "Bayesian inference using record values from Rayleigh model with application," European Journal of Operational Research, Elsevier, vol. 185(2), pages 659-672, March.
    2. Mohamed Habibullah & M. Ahsanullah, 2000. "Estimation of parameters of a pareto distribution by generalized order statistics," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 29(7), pages 1597-1609, January.
    3. Soliman, Ahmed A. & Abd Ellah, A.H. & Sultan, K.S., 2006. "Comparison of estimates using record statistics from Weibull model: Bayesian and non-Bayesian approaches," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 2065-2077, December.
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    Cited by:

    1. Mohammad Vali Ahmadi & Jafar Ahmadi & Mousa Abdi, 2019. "Evaluating the lifetime performance index of products based on generalized order statistics from two-parameter exponential model," 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(2), pages 251-275, April.
    2. Mansoor Rashid Malik & Devendra Kumar, 2019. "Generalized Pareto Distribution Based On Generalized Order Statistics And Associated Inference," Statistics in Transition New Series, Polish Statistical Association, vol. 20(3), pages 57-79, September.
    3. El-Adll, Magdy E., 2011. "Predicting future lifetime based on random number of three parameters Weibull distribution," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(9), pages 1842-1854.
    4. Shah, Imtiyaz A. & Barakat, H.M. & Khan, A.H., 2020. "Characterizations through generalized and dual generalized order statistics, with an application to statistical prediction problem," Statistics & Probability Letters, Elsevier, vol. 163(C).
    5. Malik Mansoor Rashid & Kumar Devendra, 2019. "Generalized Pareto Distribution Based On Generalized Order Statistics And Associated Inference," Statistics in Transition New Series, Polish Statistical Association, vol. 20(3), pages 57-79, September.
    6. repec:exl:29stat:v:20:y:2019:i:3:p:57-80 is not listed on IDEAS
    7. Mohammad Vali Ahmadi & Mahdi Doostparast & Jafar Ahmadi, 2015. "Statistical inference for the lifetime performance index based on generalised order statistics from exponential distribution," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(6), pages 1094-1107, April.

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