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Gini characterization of extreme-value statistics
Authors:Iddo I. Eliazar  Igor M. Sokolov
Affiliation:
  • a Department of Technology Management, Holon Institute of Technology, P.O.B. 305, Holon 58102, Israel
  • b Institut für Physik, Humboldt-Universität zu Berlin, Newtonstr. 15, D-12489 Berlin, Germany
  • Abstract:This paper presents a profound connection between Gini’s index and extreme-value statistics. Gini’s index is a quantitative gauge for the evenness of probability laws defined on the positive half-line, and is the common measure of societal egalitarianism applied in Economics and in the Social Sciences. Extreme-value statistics-namely, the Gumbel, Fréchet and Weibull probability laws-are the only possible asymptotic statistics emerging from the extremes of large ensembles of independent and identically distributed random variables. Extreme-value statistics play a major role-all across Science and Engineering-in the analysis of rare and extreme events. Introducing generalizations of Gini’s index, and exploring an elemental Poissonian structure underlying the extreme-value statistics, we establish in this paper a Gini-based characterization of extreme-value statistics.
    Keywords:Gini&rsquo  s index   Extreme-value statistics   Gumbel law   Fré  chet law   Weibull law   Poisson processes   Poissonian populations
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