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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

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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
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

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