This article proposes a non-parametric tail classifier to aid tail classification among discrete thick-tail distributions. Theoretical results in this article show that certain distributional tail types can be identified among a sequence of plots based on the tail profile. Such distributional tails include power, sub-exponential, near-exponential, and exponential or thinner decaying tails. The proposed method does not hypothesize the distribution parameters values for classification. The method can be used practically as a preliminary tool to narrow down possible parametric models for refined statistical analysis with the unbiased estimators of the tail profile. Besides, simulation studies suggest that the proposed classification method performs well under various situations.
翻译:本条提议采用非参数尾矿分类法,以帮助对离散厚尾矿分布物进行尾矿分类。本条的理论结果表明,某些分布尾矿类型可以在以尾矿分布图为基础的一系列地块中确定。这种分布尾矿包括动力、亚耗能、近耗能和指数或稀薄的衰减尾矿。拟议方法并不假定分类的分布参数值。该方法实际上可以用作一种初步工具,缩小与对尾矿分布图进行精确统计分析的可能参数模型。此外,模拟研究表明,拟议的分类方法在不同情况下运作良好。