Journal Article

PreJuSER-19793

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Lower bounds on mutual information

Foster, D. V. ; Grassberger, P.FZJ*

2011
APS College Park, Md.

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Please use a persistent id in citations: http://hdl.handle.net/2128/9268  doi:10.1103/PhysRevE.83.010101

Abstract: We correct claims about lower bounds on mutual information (MI) between real-valued random variables made by Kraskov et al., Phys. Rev. E 69, 066138 (2004). We show that non-trivial lower bounds on MI in terms of linear correlations depend on the marginal (single variable) distributions. This is so in spite of the invariance of MI under reparametrizations, because linear correlations are not invariant under them. The simplest bounds are obtained for Gaussians, but the most interesting ones for practical purposes are obtained for uniform marginal distributions. The latter can be enforced in general by using the ranks of the individual variables instead of their actual values, in which case one obtains bounds on MI in terms of Spearman correlation coefficients. We show with gene expression data that these bounds are in general nontrivial, and the degree of their (non) saturation yields valuable insight.

Keyword(s): J

Note: Record converted from VDB: 12.11.2012

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Contributing Institute(s):

1. Jülich Supercomputing Centre (JSC)

Research Program(s):

1. Scientific Computing (FUEK411) (FUEK411)
2. 411 - Computational Science and Mathematical Methods (POF2-411) (POF2-411)

Appears in the scientific report 2011

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Database coverage:
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