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.%当极值指标大于0时,本文提出了一种位置不变的Pickapids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.
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