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Restricted minimum volume confidence region for Pareto distribution

Author

Listed:
  • Fen Jiang

    (Yunnan University)

  • Junmei Zhou

    (Hainan Normal University)

  • Jin Zhang

    (Yunnan University)

Abstract

Under some restriction, we establish the minimum volume confidence region for parameters of Pareto distribution, which can be applied to complete samples and, as well as left, right or doubly censored samples. It is not only computationally convenient, but also almost as accurate as the best confidence region in the literature, the computation of which is difficult in the double or left censoring case.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:stpapr:v:61:y:2020:i:5:d:10.1007_s00362-018-1018-9
    DOI: 10.1007/s00362-018-1018-9
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    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Reed, William J., 2003. "The Pareto law of incomes—an explanation and an extension," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 319(C), pages 469-486.
    4. 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.
    5. Seal, Hilary L., 1980. "Survival Probabilities Based on Pareto Claim Distributions," ASTIN Bulletin, Cambridge University Press, vol. 11(1), pages 61-71, June.
    6. Howlader, Hatem A. & Hossain, Anwar M., 2002. "Bayesian survival estimation of Pareto distribution of the second kind based on failure-censored data," Computational Statistics & Data Analysis, Elsevier, vol. 38(3), pages 301-314, January.
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