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Rates of convergence of extreme for general error distribution under power normalization

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  • Chen, Shouquan
  • Wang, Chao
  • Zhang, Geng

Abstract

By using the theory of p-max stable laws, we study the rates of convergence of extremes for general error distribution under power normalization. We derived the exact uniform convergence rate of the distribution of maximum to its extreme value limit.

Suggested Citation

  • Chen, Shouquan & Wang, Chao & Zhang, Geng, 2012. "Rates of convergence of extreme for general error distribution under power normalization," Statistics & Probability Letters, Elsevier, vol. 82(2), pages 385-395.
    • Handle: RePEc:eee:stapro:v:82:y:2012:i:2:p:385-395
    DOI: 10.1016/j.spl.2011.10.019
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    References listed on IDEAS

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    1. 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.
    2. Christoph, Gerd & Falk, Michael, 1996. "A note on domains of attraction of p-max stable laws," Statistics & Probability Letters, Elsevier, vol. 28(3), pages 279-284, July.
    3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
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    Cited by:

    1. Liao, Xin & Peng, Zuoxiang & Nadarajah, Saralees & Wang, Xiaoqian, 2014. "Rates of convergence of extremes from skew-normal samples," Statistics & Probability Letters, Elsevier, vol. 84(C), pages 40-47.

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