A computationally efficient estimator for mutual information

Evans, Dafydd 2008. A computationally efficient estimator for mutual information. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 464 (2093) , pp. 1203-1215. 10.1098/rspa.2007.0196

Full text not available from this repository.

Abstract

Mutual information quantifies the determinism that exists in a relationship between random variables, and thus plays an important role in exploratory data analysis. We investigate a class of non-parametric estimators for mutual information, based on the nearest neighbour structure of observations in both the joint and marginal spaces. Unless both marginal spaces are one-dimensional, we demonstrate that a well-known estimator of this type can be computationally expensive under certain conditions, and propose a computationally efficient alternative that has a time complexity of order (N log N) as the number of observations N→∞.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Computer Science & Informatics Schools > Mathematics
Subjects:	Q Science > QA Mathematics
Uncontrolled Keywords:	mutual information; nearest neighbour analysis; non-parametric estimation
Publisher:	Royal Society
ISSN:	1364-5021
Last Modified:	04 Jun 2017 02:57
URI:	https://orca.cardiff.ac.uk/id/eprint/14279

Citation Data

Cited 22 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item