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Expansions on extremes from logarithmic general error distribution under power normalization

Author

Listed:
  • Geng Yang

    (Southwest University)

  • Tingting Li

    (Southwest University)

Abstract

In this short note, under power normalization we establish the higher-order expansions of probability density function and cumulative distribution function of maximum from logarithmic general error distribution.

Suggested Citation

  • Geng Yang & Tingting Li, 2016. "Expansions on extremes from logarithmic general error distribution under power normalization," Statistical Papers, Springer, vol. 57(3), pages 781-793, September.
    • Handle: RePEc:spr:stpapr:v:57:y:2016:i:3:d:10.1007_s00362-015-0679-x
    DOI: 10.1007/s00362-015-0679-x
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    References listed on IDEAS

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    1. W. J. Hall & Jon A. Wellner, 1979. "The rate of convergence in law of the maximum of an exponential sample," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 33(3), pages 151-154, September.
    2. Subramanya, U. R., 1994. "On max domains of attraction of univariate p-max stable laws," Statistics & Probability Letters, Elsevier, vol. 19(4), pages 271-279, March.
    3. H. Barakat & E. Nigm & Magdy El-Adll, 2010. "Comparison between the rates of convergence of extremes under linear and under power normalization," Statistical Papers, Springer, vol. 51(1), pages 149-164, January.
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