Problems with Fitting to the Power-Law Distribution

Michel L. Goldstein; Steven A. Morris; Gary G. Yen

doi:10.1140/epjb/e2004-00316-5

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arXiv · cond-mat/0402322

Problems with Fitting to the Power-Law Distribution

Michel L. Goldstein·Steven A. Morris·Gary G. Yen

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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-Smirnof 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.

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BibTeX RIS

Michel L. Goldstein, Steven A. Morris, Gary G. Yen. 2004-08-13. Problems with Fitting to the Power-Law Distribution. https://doi.org/10.1140/epjb%2Fe2004-00316-5

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