A pragmatic entropy and differential entropy estimator for small datasets
Keywords:
Entropy through coincidence, Small datasets, Discrete and/or continuous variables, Uncomplicated algorithms.
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).
Published
28-07-2014
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
Section
Letters
Copyright (c) 2014 Jugurta Montalvão, Romis Attux, Daniel Silva
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
___________
