Power-Laws as Statistical Mixtures

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Researchers

  • M. Patriarca
  • E. Heinsalu
  • L. Marzola
  • A. Chakraborti
  • Kimmo Kaski

Research units

  • University of Tartu
  • Jawaharlal Nehru University
  • National Institute of Chemical Physics and Biophysics, Tallinn

Abstract

Many complex systems are characterized by power-law distributions. In this article, we show that for various examples of power-law distributions, including the two probably most popular ones, the Pareto law for the wealth distribution and Zipf's law for the occurrence frequency of words in a written text, the power-law tails of the probability distributions can be decomposed into a statistical mixture of canonical equilibrium probability densities of the subsystems. While the interacting units or subsystems have canonical distributions at equilibrium, as predicted by canonical statistical mechanics, the heterogeneity of the shapes of their distributions leads to the appearance of a power-law.

Details

Original languageEnglish
Title of host publicationProceedings of ECCS 2014
Subtitle of host publicationEUROPEAN CONFERENCE ON COMPLEX SYSTEMS
EditorsS Battiston, F DePellegrini, G Caldarelli, E Merelli
Publication statusPublished - 2016
MoE publication typeA4 Article in a conference publication
EventEuropean Conference on Complex Systems - Lucca, Italy
Duration: 22 Sep 201426 Sep 2014

Publication series

NameSpringer Proceedings in Complexity
PublisherSPRINGER
ISSN (Electronic)2213-8684

Conference

ConferenceEuropean Conference on Complex Systems
Abbreviated titleECCS
CountryItaly
CityLucca
Period22/09/201426/09/2014

    Research areas

  • KINETIC EXCHANGE MODELS, WEALTH DISTRIBUTION, SAVING PROPENSITY, DISTRIBUTIONS, SUPERSTATISTICS, INCOME, MONEY, GIBBS

ID: 9490672