6533b871fe1ef96bd12d0f25
RESEARCH PRODUCT
Extropy: Complementary Dual of Entropy
Frank LadGiuseppe SanfilippoGianna Agròsubject
Bregman divergenceFOS: Computer and information sciencesStatistics and ProbabilitySettore MAT/06 - Probabilita' E Statistica MatematicaKullback–Leibler divergenceComputer Science - Information TheoryGeneral MathematicsFOS: Physical sciencesBinary numberMathematics - Statistics TheoryStatistics Theory (math.ST)Kullback–Leibler divergenceBregman divergenceproper scoring rulesGini index of heterogeneityDifferential entropyBinary entropy functionFOS: MathematicsEntropy (information theory)Statistical physicsDual functionAxiomMathematicsdifferential and relative entropy/extropy Kullback- Leibler divergence Bregman divergence duality proper scoring rules Gini index of heterogeneity repeat rate.Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniDifferential and relative entropy/extropyInformation Theory (cs.IT)Probability (math.PR)repeat ratePhysics - Data Analysis Statistics and ProbabilitydualityStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaMathematics - ProbabilityData Analysis Statistics and Probability (physics.data-an)description
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2015-02-01 | Statistical Science |