CRAN: Package poweRlaw

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: 1.0.0

Depends: R (≥ 3.4.0)

Imports: methods, parallel, pracma, stats, utils

Suggests: covr, knitr, testthat

Published: 2025年02月03日

DOI: 10.32614/CRAN.package.poweRlaw

Author: Colin Gillespie ORCID iD [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, http://csgillespie.github.io/poweRlaw/

NeedsCompilation: no

Language: en-GB

Citation: poweRlaw citation info

Materials: README, NEWS

In views: Distributions

CRAN checks: poweRlaw results

Documentation:

Reference manual: poweRlaw.html , poweRlaw.pdf

Vignettes: 1. An introduction to the poweRlaw package (source, R code)
2. Examples using the poweRlaw package (source, R code)
3. Comparing distributions with the poweRlaw package (source, R code)
4. Journal of Statistical Software Article (source)

Downloads:

Package source: poweRlaw_1.0.0.tar.gz

Windows binaries: r-devel: poweRlaw_1.0.0.zip, r-release: poweRlaw_1.0.0.zip, r-oldrel: poweRlaw_1.0.0.zip

macOS binaries: r-release (arm64): poweRlaw_1.0.0.tgz, r-oldrel (arm64): poweRlaw_1.0.0.tgz, r-release (x86_64): poweRlaw_1.0.0.tgz, r-oldrel (x86_64): poweRlaw_1.0.0.tgz

Old sources: poweRlaw archive

Reverse dependencies:

Reverse depends: BioNAR

Reverse imports: CNEr, ForestGapR, miaSim, MultIS, randnet, sads

Reverse suggests: ercv, poppr, spatialwarnings

Linking:

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