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: | 0.70.6 |
| Depends: | R (≥ 3.4.0) |
| Imports: | methods, parallel, pracma, stats, utils |
| Suggests: | covr, knitr, testthat |
| Published: | 2020-04-25 |
| Author: | Colin Gillespie |
| 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: | README NEWS |
| In views: | Distributions |
| CRAN checks: | poweRlaw results |
| 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_0.70.6.tar.gz |
| Windows binaries: | r-devel: poweRlaw_0.70.6.zip, r-release: poweRlaw_0.70.6.zip, r-oldrel: poweRlaw_0.70.6.zip |
| macOS binaries: | r-release: poweRlaw_0.70.6.tgz, r-oldrel: poweRlaw_0.70.6.tgz |
| Old sources: | poweRlaw archive |
| Reverse depends: | AbSim |
| Reverse imports: | CNEr, immuneSIM, randnet, SNscan |
| Reverse suggests: | ercv, poppr, spatialwarnings |
Please use the canonical form https://CRAN.R-project.org/package=poweRlaw to link to this page.