Equitability, mutual information, and the maximal information coefficient

Cold Spring Harbor Laboratory

PubMed
Indexed inarxivcrossrefpubmed

Abstract

How should one quantify the strength of association between two random variables without bias for relationships of a specific form? Despite its conceptual simplicity, this notion of statistical "equitability" has yet to receive a definitive mathematical formalization. Here we argue that equitability is properly formalized by a self-consistency condition closely related to Data Processing Inequality. Mutual information, a fundamental quantity in information theory, is shown to satisfy this equitability criterion. These findings are at odds with the recent work of Reshef et al. [Reshef DN, et al. (2011) Science 334(6062):1518-1524], which proposed an alternative definition of equitability and introduced a new…

Citation impact

672
total citations
FWCI
137.72
Percentile
100%
References
59
Citations per year

Authors

2

Topics & keywords

Keywords
  • Mutual information
  • Statistic
  • Consistency (knowledge bases)
  • Mathematics
  • Information theory
  • Odds
  • Statistics
  • Econometrics
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