Problems with fitting to the power-law distribution
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
Year of publication: |
2004
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Authors: | Goldstein, M. ; Morris, S. ; Yen, G. |
Published in: |
The European Physical Journal B - Condensed Matter and Complex Systems. - Springer. - Vol. 41.2004, 2, p. 255-258
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Publisher: |
Springer |
Saved in:
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