一种选择阈值的不同方法

A. Verster, Lizanne Raubenheimer Department of Mathematical Statistics, Actuarial Science, U. State, Bloemfontein, S. Africa, School of Mathematical, Statistical Sciences, North-West University, Potchefstroom
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引用次数: 4

摘要

在极值方法中,阈值的选择对于有效地模拟超过阈值的观测值起着重要的作用。必须选择足够高的阈值以确保无偏极值指数,但选择过高的阈值会导致不受控制的方差。本文研究了一个可以帮助选择γ正域中最优阈值的广义模型。通过推导未知广义参数的后验分布来考虑贝叶斯方法。利用后验分布的特性,可以在没有目测的情况下选择最佳阈值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Different Approach for Choosing a Threshold in Peaks over Threshold
In Extreme Value methodology the choice of threshold plays an important role in efficient modelling of observations exceeding the threshold. The threshold must be chosen high enough to ensure an unbiased extreme value index but choosing the threshold too high results in uncontrolled variances. This paper investigates a generalized model that can assist in the choice of optimal threshold values in the γ positive domain. A Bayesian approach is considered by deriving a posterior distribution for the unknown generalized parameter. Using the properties of the posterior distribution allows for a method to choose an optimal threshold without visual inspection.
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