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February 2015 Extropy: Complementary Dual of Entropy
Frank Lad, Giuseppe Sanfilippo, Gianna Agrò
Statist. Sci. 30(1): 40-58 (February 2015). DOI: 10.1214/14-STS430

Abstract

This article provides a completion to theories of information based on entropy, resolving a longstanding question in its axiomatization as proposed by Shannon and pursued by Jaynes. We show that Shannon’s entropy function has a complementary dual function which we call “extropy.” The entropy and the extropy of a binary distribution are identical. However, the measure bifurcates into a pair of distinct measures for any quantity that is not merely an event indicator. As with entropy, the maximum extropy distribution is also the uniform distribution, and both measures are invariant with respect to permutations of their mass functions. However, they behave quite differently in their assessments of the refinement of a distribution, the axiom which concerned Shannon and Jaynes. Their duality is specified via the relationship among the entropies and extropies of course and fine partitions. We also analyze the extropy function for densities, showing that relative extropy constitutes a dual to the Kullback–Leibler divergence, widely recognized as the continuous entropy measure. These results are unified within the general structure of Bregman divergences. In this context they identify half the $L_{2}$ metric as the extropic dual to the entropic directed distance. We describe a statistical application to the scoring of sequential forecast distributions which provoked the discovery.

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Frank Lad. Giuseppe Sanfilippo. Gianna Agrò. "Extropy: Complementary Dual of Entropy." Statist. Sci. 30 (1) 40 - 58, February 2015. https://doi.org/10.1214/14-STS430

Information

Published: February 2015
First available in Project Euclid: 4 March 2015

zbMATH: 1332.62027
MathSciNet: MR3317753
Digital Object Identifier: 10.1214/14-STS430

Rights: Copyright © 2015 Institute of Mathematical Statistics

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Vol.30 • No. 1 • February 2015
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