论文标题
广义极值分布的最大似然估计器的独特性和全球最优性
Uniqueness and global optimality of the maximum likelihood estimator for the generalized extreme value distribution
论文作者
论文摘要
三参数广义的极值分布来自经典的单变量极值理论，并常用于分析观察到的现象的远端。奇怪的是，在此标准模型下基于可能性的估计的重要渐近特性尚未确定。在本文中，我们正式证明了最大似然估计量是全局且独特的。有趣的次要结果需要在形状参数的紧密邻域中一类极限关系的统一一致性。
The three-parameter generalized extreme value distribution arises from classical univariate extreme value theory and is in common use for analyzing the far tail of observed phenomena. Curiously, important asymptotic properties of likelihood-based estimation under this standard model have yet to be established. In this paper, we formally prove that the maximum likelihood estimator is global and unique. An interesting secondary result entails the uniform consistency of a class of limit relations in a tight neighborhood of the shape parameter.
