一类位置不变的Pickands型估计量

A Location Invariant Pickands-Type Estimator

  • 摘要: 当极值指标大于0时, 本文提出了一种位置不变的Pickands型估计量, 证明了该估计量的强弱相合性, 给出了其渐近展式和强收敛速度, 并对k_2的最优选择进行了讨论, 最后利用自适应性方法对该估计量和其它Pickands型估计量进行随机模拟分析, 比较该估计量的优越性.

     

    Abstract: In this paper, the author proposes a location invariant Pickands-type estimator as the extreme index is positive. Its weak and strong convergence are proved. Asymptotical representation and strong convergence rate are derived, and the optimal choice of k_2 is found. At last simulation and comparison of this new kind of Pickands-type estimator with other known Pickands-type estimators are considered by using the adaptive algorithm.

     

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