论文标题
极端价值与牙龈分布的信息理论收敛
Information-theoretic convergence of extreme values to the Gumbel distribution
论文作者
论文摘要
我们展示了如何以信息理论的意义理解在极值设置中与牙龈分布的融合。我们引入了一种新型的分数功能，该功能在最大操作下表现良好，这意味着熵和相对熵的简单表达式。我们表明，假设冯·米塞斯表示的某些特性，可以在强烈的相对熵意义上证明与牙龈的收敛。
We show how convergence to the Gumbel distribution in an extreme value setting can be understood in an information-theoretic sense. We introduce a new type of score function which behaves well under the maximum operation, and which implies simple expressions for entropy and relative entropy. We show that, assuming certain properties of the von Mises representation, convergence to the Gumbel can be proved in the strong sense of relative entropy.
