A pragmatic entropy and differential entropy estimator for small datasets

Jugurta Montalvão; Romis Attux; Daniel Silva

doi:10.14209/jcis.2014.8

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Published: Jul 28, 2014

DOI: https://doi.org/10.14209/jcis.2014.8

Keywords:

Entropy through coincidence, Small datasets, Discrete and/or continuous variables, Uncomplicated algorithms.

Jugurta Montalvão

Federal Univ. of Sergipe

Romis Attux

University of Campinas

Daniel Silva

University of Brasília

Abstract

A pragmatic approach for entropy estimation is presented, first for discrete variables, then in the form of an extension for handling continuous and/or multivariate ones. It is based on coincidence detection, and its application leads to algorithms with three main attractive features: they are easy to use, can be employed without any a priori knowledge concerning source distribution (not even the alphabet cardinality K of discrete sources) and can provide useful estimates even when the number of samples is small (e.g. less than K, for discrete variables).

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How to Cite

Montalvão, J., Attux, R., & Silva, D. (2014). A pragmatic entropy and differential entropy estimator for small datasets. Journal of Communication and Information Systems, 29(1). https://doi.org/10.14209/jcis.2014.8

Issue

Vol. 29 No. 1 (2014)

Section

Letters

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Received 2013-04-12
Accepted 2014-07-10
Published 2014-07-28

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