Literature DB >> 12513446

From gene families and genera to incomes and internet file sizes: why power laws are so common in nature.

William J Reed1, Barry D Hughes.   

Abstract

We present a simple explanation for the occurrence of power-law tails in statistical distributions by showing that if stochastic processes with exponential growth in expectation are killed (or observed) randomly, the distribution of the killed or observed state exhibits power-law behavior in one or both tails. This simple mechanism can explain power-law tails in the distributions of the sizes of incomes, cities, internet files, biological taxa, and in gene family and protein family frequencies.

Year:  2002        PMID: 12513446     DOI: 10.1103/PhysRevE.66.067103

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  28 in total

1.  Quantitative and empirical demonstration of the Matthew effect in a study of career longevity.

Authors:  Alexander M Petersen; Woo-Sung Jung; Jae-Suk Yang; H Eugene Stanley
Journal:  Proc Natl Acad Sci U S A       Date:  2010-12-20       Impact factor: 11.205

2.  The growth of business firms: theoretical framework and empirical evidence.

Authors:  Dongfeng Fu; Fabio Pammolli; S V Buldyrev; Massimo Riccaboni; Kaushik Matia; Kazuko Yamasaki; H Eugene Stanley
Journal:  Proc Natl Acad Sci U S A       Date:  2005-12-19       Impact factor: 11.205

3.  Inferring the distribution of mutational effects on fitness in Drosophila.

Authors:  Laurence Loewe; Brian Charlesworth
Journal:  Biol Lett       Date:  2006-09-22       Impact factor: 3.703

4.  Precisely timed spatiotemporal patterns of neural activity in dissociated cortical cultures.

Authors:  J D Rolston; D A Wagenaar; S M Potter
Journal:  Neuroscience       Date:  2007-07-05       Impact factor: 3.590

5.  An inverse power-law distribution of molecular bond lifetimes predicts fractional derivative viscoelasticity in biological tissue.

Authors:  Bradley M Palmer; Bertrand C W Tanner; Michael J Toth; Mark S Miller
Journal:  Biophys J       Date:  2013-06-04       Impact factor: 4.033

6.  Understanding Zipf's law of word frequencies through sample-space collapse in sentence formation.

Authors:  Stefan Thurner; Rudolf Hanel; Bo Liu; Bernat Corominas-Murtra
Journal:  J R Soc Interface       Date:  2015-07-06       Impact factor: 4.118

7.  Handicap principle implies emergence of dimorphic ornaments.

Authors:  Sara M Clifton; Rosemary I Braun; Daniel M Abrams
Journal:  Proc Biol Sci       Date:  2016-11-30       Impact factor: 5.349

8.  Hierarchical networks, power laws, and neuronal avalanches.

Authors:  Eric J Friedman; Adam S Landsberg
Journal:  Chaos       Date:  2013-03       Impact factor: 3.642

9.  Tracking random walks.

Authors:  Riccardo Gallotti; Rémi Louf; Jean-Marc Luck; Marc Barthelemy
Journal:  J R Soc Interface       Date:  2018-02       Impact factor: 4.118

10.  Distributions of observed death tolls govern sensitivity to human fatalities.

Authors:  Christopher Y Olivola; Namika Sagara
Journal:  Proc Natl Acad Sci U S A       Date:  2009-12-15       Impact factor: 11.205

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