This article introduces a general statistical modeling principle called ``Density Sharpening'' and applies it to the analysis of discrete count data. The underlying foundation is based on a new theory of nonparametric approximation and smoothing methods for discrete distributions which play a useful role in explaining and uniting a large class of applied statistical methods. The proposed modeling framework is illustrated using several real applications, from seismology to healthcare to physics.

翻译：本条引入了称为“密度锐化”的一般统计模型原则,并将其应用于分析离散计数数据,其基础基础是离散分布的非参数近似和平滑方法的新理论,这种理论在解释和统一一大批应用统计方法方面发挥了有益的作用。 拟议的模型框架用从地震学到保健到物理学等多种实际应用加以说明。