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 |
Official URL: http://dx.doi.org/10.1098/rspa.2007.0196
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: | Computer Science & Informatics 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 |