Next Article in Journal
Poincaré and Log–Sobolev Inequalities for Mixtures
Previous Article in Journal
Parallel Lives: A Local-Realistic Interpretation of “Nonlocal” Boxes
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle

Symmetries among Multivariate Information Measures Explored Using Möbius Operators

Pacific Northwest Research Institute, 720 Broadway, Seattle, WA 98122, USA
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(1), 88; https://doi.org/10.3390/e21010088
Received: 7 November 2018 / Revised: 9 January 2019 / Accepted: 16 January 2019 / Published: 18 January 2019
  |  
PDF [2879 KB, uploaded 18 January 2019]
  |  

Abstract

Relations between common information measures include the duality relations based on Möbius inversion on lattices, which are the direct consequence of the symmetries of the lattices of the sets of variables (subsets ordered by inclusion). In this paper we use the lattice and functional symmetries to provide a unifying formalism that reveals some new relations and systematizes the symmetries of the information functions. To our knowledge, this is the first systematic examination of the full range of relationships of this class of functions. We define operators on functions on these lattices based on the Möbius inversions that map functions into one another, which we call Möbius operators, and show that they form a simple group isomorphic to the symmetric group S3. Relations among the set of functions on the lattice are transparently expressed in terms of the operator algebra, and, when applied to the information measures, can be used to derive a wide range of relationships among diverse information measures. The Möbius operator algebra is then naturally generalized which yields an even wider range of new relationships. View Full-Text
Keywords: information; entropy; interaction-information; multi-information; Möbius inversion; lattices; multivariable dependence; symmetric group; MaxEnt; networks information; entropy; interaction-information; multi-information; Möbius inversion; lattices; multivariable dependence; symmetric group; MaxEnt; networks
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Galas, D.J.; Sakhanenko, N.A. Symmetries among Multivariate Information Measures Explored Using Möbius Operators. Entropy 2019, 21, 88.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top