poweRlaw: Analysis of Heavy Tailed Distributions

An implementation of maximum likelihood estimators for a variety of heavy tailed distributions, including both the discrete and continuous power law distributions. Additionally, a goodness-of-fit based approach is used to estimate the lower cut-off for the scaling region.

Version: 0.30.2
Depends: R (≥ 3.0.0), methods
Imports: VGAM, parallel
Suggests: knitr, R.matlab
Published: 2015-04-16
Author: Colin Gillespie [aut, cre]
Maintainer: Colin Gillespie <csgillespie at gmail.com>
BugReports: https://github.com/csgillespie/poweRlaw/issues
License: GPL-2 | GPL-3
URL: https://github.com/csgillespie/poweRlaw
NeedsCompilation: no
Citation: poweRlaw citation info
Materials: NEWS
In views: Distributions
CRAN checks: poweRlaw results

Downloads:

Reference manual: poweRlaw.pdf
Vignettes: 1. An introduction to the poweRlaw package
2. Examples using the poweRlaw package
3. Comparing distributions with the poweRlaw package
4. Journal of Statistical Software Article
Package source: poweRlaw_0.30.2.tar.gz
Windows binaries: r-devel: poweRlaw_0.30.2.zip, r-release: poweRlaw_0.30.2.zip, r-oldrel: poweRlaw_0.30.2.zip
OS X Snow Leopard binaries: r-release: poweRlaw_0.30.2.tgz, r-oldrel: poweRlaw_0.30.2.tgz
OS X Mavericks binaries: r-release: poweRlaw_0.30.2.tgz
Old sources: poweRlaw archive

Reverse dependencies:

Reverse suggests: poppr