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A characterization of the Pareto distribution based on the Fisher information for censored data under non-regularity conditions

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  • George Tzavelas

    (University of Piraeus)

Abstract

It is proved that within a proper class of distributions, the Pareto and the shifted exponential distribution are the only distributions with the property of no loss of information due to type-I censoring and random censoring. The equality of the information before and after censoring it is achieved only when the regularity conditions do not hold.

Suggested Citation

  • George Tzavelas, 2019. "A characterization of the Pareto distribution based on the Fisher information for censored data under non-regularity conditions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(4), pages 429-440, May.
    • Handle: RePEc:spr:metrik:v:82:y:2019:i:4:d:10.1007_s00184-018-0697-5
    DOI: 10.1007/s00184-018-0697-5
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    References listed on IDEAS

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    1. Zheng, Gang & Gastwirth, Joseph L., 2001. "On the Fisher information in randomly censored data," Statistics & Probability Letters, Elsevier, vol. 52(4), pages 421-426, May.
    2. Wang, Yanhua & He, Shuyuan, 2005. "Fisher information in censored data," Statistics & Probability Letters, Elsevier, vol. 73(2), pages 199-206, June.
    3. Gertsbakh, I., 1995. "On the Fisher information in type-I censored and quantal response data," Statistics & Probability Letters, Elsevier, vol. 23(4), pages 297-306, June.
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    Cited by:

    1. James Allison & Bojana Milošević & Marko Obradović & Marius Smuts, 2022. "Distribution-free goodness-of-fit tests for the Pareto distribution based on a characterization," Computational Statistics, Springer, vol. 37(1), pages 403-418, March.

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