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Problems with fitting to the power-law distribution

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Author Info

  • M. Goldstein
  • S. Morris
  • G. Yen

    ()

Abstract

This short communication uses a simple experiment to show that fitting to a power law distribution by using graphical methods based on linear fit on the log-log scale is biased and inaccurate. It shows that using maximum likelihood estimation (MLE) is far more robust. Finally, it presents a new table for performing the Kolmogorov-Smirnov test for goodness-of-fit tailored to power-law distributions in which the power-law exponent is estimated using MLE. The techniques presented here will advance the application of complex network theory by allowing reliable estimation of power-law models from data and further allowing quantitative assessment of goodness-of-fit of proposed power-law models to empirical data. Copyright Springer-Verlag Berlin/Heidelberg 2004

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File URL: http://hdl.handle.net/10.1140/epjb/e2004-00316-5
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Bibliographic Info

Article provided by Springer in its journal The European Physical Journal B - Condensed Matter and Complex Systems.

Volume (Year): 41 (2004)
Issue (Month): 2 (09)
Pages: 255-258

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Handle: RePEc:spr:eurphb:v:41:y:2004:i:2:p:255-258

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Web page: http://www.springer.com/economics/journal/10051

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