Quantifying high-order interdependencies via multivariate extensions of the mutual information
作者： Fernando E. Rosas , Pedro A. M. Mediano , Michael Gastpar , Henrik J. Jensen
DOI: 10.1103/PHYSREVE.100.032305
关键词: Interdependence 、 Multivariate statistics 、 Relevance (information retrieval) 、 Key (cryptography) 、 Metric (mathematics) 、 Proof of concept 、 Mutual information 、 Computer science 、 Statistical mechanics 、 Theoretical computer science
摘要: This paper introduces a model-agnostic approach to study statistical synergy, a form of emergence in which patterns at large scales are not traceable from lower scales. Our framework leverages various multivariate extensions of Shannon's mutual information, and introduces the O-information as a metric that is capable of characterizing synergy-and redundancy-dominated systems. The O-information is a symmetric quantity, and can assess intrinsic properties of a system without dividing its parts into “predictors” and “targets.” We …
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