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On estimating the exponent of power-law frequency distributions.

Authors
  • White, Ethan P
  • Enquist, Brian J
  • Green, Jessica L
Type
Published Article
Journal
Ecology
Publisher
Wiley (John Wiley & Sons)
Publication Date
Apr 01, 2008
Volume
89
Issue
4
Pages
905–912
Identifiers
PMID: 18481513
Source
Medline
License
Unknown

Abstract

Power-law frequency distributions characterize a wide array of natural phenomena. In ecology, biology, and many physical and social sciences, the exponents of these power laws are estimated to draw inference about the processes underlying the phenomenon, to test theoretical models, and to scale up from local observations to global patterns. Therefore, it is essential that these exponents be estimated accurately. Unfortunately, the binning-based methods traditionally used in ecology and other disciplines perform quite poorly. Here we discuss more sophisticated methods for fitting these exponents based on cumulative distribution functions and maximum likelihood estimation. We illustrate their superior performance at estimating known exponents and provide details on how and when ecologists should use them. Our results confirm that maximum likelihood estimation outperforms other methods in both accuracy and precision. Because of the use of biased statistical methods for estimating the exponent, the conclusions of several recently published papers should be revisited.

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