This package implements both the discrete and continuous maximum likelihood estimators for fitting the power-law distribution to data. Additionally, a goodness-of-fit based approach is used to estimate the lower cut-off for the scaling region.
| Version: | 0.20.5 |
| Depends: | R (≥ 3.0.0), methods |
| Imports: | VGAM, parallel |
| Suggests: | knitr, R.matlab, testthat |
| Published: | 2014-06-12 |
| 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 |
| CRAN checks: | poweRlaw results |
| Reference manual: | poweRlaw.pdf |
| Vignettes: |
Comparing distributions examples An overview |
| Package source: | poweRlaw_0.20.5.tar.gz |
| Windows binaries: | r-devel: poweRlaw_0.20.5.zip, r-release: poweRlaw_0.20.5.zip, r-oldrel: poweRlaw_0.20.5.zip |
| OS X Snow Leopard binaries: | r-release: poweRlaw_0.20.5.tgz, r-oldrel: poweRlaw_0.20.5.tgz |
| OS X Mavericks binaries: | r-release: poweRlaw_0.20.5.tgz |
| Old sources: | poweRlaw archive |