AbstractThe averaged shifted histogram or ASH is a nonparametric probability density estimator derived from a collection of histograms. The ASH enjoys several advantages compared with a single histogram: better visual interpretation, better approximation, and nearly the same computational efficiency. The ASH provides a bridge between the histogram and advanced kernel methods; moreover, the ASH provides a method of choice for kernel implementation. Copyright © 2009 John Wiley & Sons, Inc.This article is categorized under: Statistical and Graphical Methods of Data Analysis > Density Estimation