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Interval estimation for a Pareto distribution based on a doubly type II censored sample

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  • Wu, Shu-Fei

Abstract

For a complete sample, Chen [Chen, Z., 1996. Joint confidence region for the parameters of a Pareto distribution. Metrika 44, 191-197] proposed an interval estimation of the parameter [theta] and a joint confidence region of two parameters of a Pareto distribution. When the first r lifetimes and the last s lifetimes out of n inspected items are missing, doubly type II censoring has arisen. Since Chen's method cannot be extended to the doubly type II censored sample case, I proposed another joint confidence region for the two parameters of a Pareto distribution. The interval estimation of parameter [nu] is also given for a doubly type II censored sample. Since the complete sample case (r=0) and the right type II censored sample case (r=s=0) are special cases of doubly type II censored samples, the proposed confidence region should also be appropriate for these two special cases, and thus can be compared with Chen's method based on the area of the confidence region. From the simulation results, it can be found that the proposed method is better than Chen's method in obtaining a smaller confidence area. But the difference in area of the two methods becomes very slight when the sample size becomes larger. In this paper, I also proposed the prediction intervals of the future observation and the ratio of the two future consecutive failure times based on the doubly type II censored sample. Finally, an example is given to illustrate the proposed method.

Suggested Citation

  • Wu, Shu-Fei, 2008. "Interval estimation for a Pareto distribution based on a doubly type II censored sample," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3779-3788, March.
  • Handle: RePEc:eee:csdana:v:52:y:2008:i:7:p:3779-3788
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    References listed on IDEAS

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    1. Zhenmin Chen, 1996. "Joint confidence region for the parameters of pareto distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 44(1), pages 191-197, December.
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    Cited by:

    1. Liang Wang & Huizhong Lin & Yuhlong Lio & Yogesh Mani Tripathi, 2022. "Interval Estimation of Generalized Inverted Exponential Distribution under Records Data: A Comparison Perspective," Mathematics, MDPI, vol. 10(7), pages 1-20, March.
    2. Hanieh Panahi, 2019. "Estimation for the parameters of the Burr Type XII distribution under doubly censored sample with application to microfluidics data," 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(4), pages 510-518, August.
    3. Jin Zhang, 2013. "Simplification of joint confidence regions for the parameters of the Pareto distribution," Computational Statistics, Springer, vol. 28(4), pages 1453-1462, August.
    4. Fen Jiang & Junmei Zhou & Jin Zhang, 2020. "Restricted minimum volume confidence region for Pareto distribution," Statistical Papers, Springer, vol. 61(5), pages 2015-2029, October.
    5. Xiao Wang & Xinmin Li, 2021. "Generalized Confidence Intervals for Zero-Inflated Pareto Distribution," Mathematics, MDPI, vol. 9(24), pages 1-9, December.
    6. Volterman, William & Balakrishnan, N. & Cramer, Erhard, 2012. "Exact nonparametric meta-analysis for multiple independent doubly Type-II censored samples," Computational Statistics & Data Analysis, Elsevier, vol. 56(5), pages 1243-1255.
    7. Fernández, Arturo J., 2012. "Minimizing the area of a Pareto confidence region," European Journal of Operational Research, Elsevier, vol. 221(1), pages 205-212.
    8. Cramer, Erhard & Schmiedt, Anja Bettina, 2011. "Progressively Type-II censored competing risks data from Lomax distributions," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1285-1303, March.
    9. Fernández, Arturo J., 2013. "Smallest Pareto confidence regions and applications," Computational Statistics & Data Analysis, Elsevier, vol. 62(C), pages 11-25.

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    2. Jin Zhang, 2013. "Simplification of joint confidence regions for the parameters of the Pareto distribution," Computational Statistics, Springer, vol. 28(4), pages 1453-1462, August.
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