  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.
