Supplement 1. Matlab files for fitting power-law exponents using different methods.

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).