Averaged shifted histogram | Zendy

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Averaged shifted histogram

Author(s) -

Scott David W.

Publication year - 2010

Publication title -

wiley interdisciplinary reviews: computational statistics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.693

H-Index - 38

eISSN - 1939-0068

pISSN - 1939-5108

DOI - 10.1002/wics.54

Subject(s) - histogram , kernel density estimation , estimator , balanced histogram thresholding , kernel (algebra) , histogram matching , multivariate kernel density estimation , nonparametric statistics , mathematics , density estimation , computer science , adaptive histogram equalization , statistics , artificial intelligence , kernel method , histogram equalization , variable kernel density estimation , support vector machine , image (mathematics) , combinatorics

The 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

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