Ethan P. White, Brian J. Enquist, and Jessica L. Green. 2008. On estimating the exponents of power-law frequency distributions. Ecology 89:905–912.


Supplement

Matlab files for fitting power-law exponents using different methods.
Ecological Archives
E089-052-S1
.

Copyright


Authors
File list (downloads)
Description


Author(s)

Ethan P. White
Department of Biology and the Ecology Center
Utah State University
5305 Old Main Hill
Logan, Utah USA 84322
E-mail: epwhite@biology.usu.edu

Brian J. Enquist
Department of Ecology and Evolutionary Biology
University of Arizona
Bioscienses West
Tucson, Arizona USA 85721
Email: benquist@u.arizona.edu

Jessica L. Green
Center for Ecology and Evolutionary Biology
335 Pacific Hall
5289 University of Oregon
Eugene, Oregon USA 97403
Email: jlgreen@uoregon.edu


File list

cdf_pareto.m -- Matlab file for fitting the CDF of the Pareto distribution
cdf_power.m -- Matlab file for fitting the CDF of the Power distribution
linbin_estimator.m -- Matlab file for fitting linearly binned data
logbin_estimator.m -- Matlab file for fitting normalized logarithmicly binned data
mle_discretepareto.m -- Matlab file for maximum likelihood estimation of the discrete Pareto distribution
mle_pareto.m -- Matlab file for maximum likelihood estimation of the Pareto distribution
mle_power.m -- Matlab file for maximum likelihood estimation of the Power Function distribution
mle_truncpareto.m -- Matlab file for maximum likelihood estimation of the truncated Pareto distribution
allfiles.zip -- Download all files at once

Description

The accompanying Matlab files perform each of the different fitting methods described in the original paper. Depending on the method there may be several different files to allow the fitting of the different distributions described in the original paper. All files take a vector data that is list of each observed value of x, as well as a series of arguments that are unique to each combination of method and distribution. Detailed descriptions of these arguments are provided in a comment header at the beginning of each file. All files are also heavily commented for clarity. For non-Matlab users, m-files can be opened using any standard text editor (note: % is the comment symbol).


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