  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.
