Generalised Measures of Multivariate Information Content

Conor Finn; Joseph T. Lizier

doi:10.3390/e22020216

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arXiv · 1909.12166

Generalised Measures of Multivariate Information Content

Conor Finn·Joseph T. Lizier

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Abstract

The entropy of a pair of random variables is commonly depicted using a Venn diagram. This representation is potentially misleading, however, since the multivariate mutual information can be negative. This paper presents new measures of multivariate information content that can be accurately depicted using Venn diagrams for any number of random variables. These measures complement the existing measures of multivariate mutual information and are constructed by considering the algebraic structure of information sharing. It is shown that the distinct ways in which a set of marginal observers can share their information with a non-observing third party corresponds to the elements of a free distributive lattice. The redundancy lattice from partial information decomposition is then subsequently and independently derived by combining the algebraic structures of joint and shared information content.

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Conor Finn, Joseph T. Lizier. 2019-09-26. Generalised Measures of Multivariate Information Content. https://doi.org/10.3390/e22020216

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