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: | 0.70.2 |
| Depends: | R (≥ 3.4.0) |
| Imports: | VGAM, parallel, methods, utils, stats |
| Suggests: | knitr, R.matlab, testthat, codetools, covr |
| Published: | 2019-01-10 |
| 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: | 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_0.70.2.tar.gz |
| Windows binaries: | r-devel: poweRlaw_0.70.2.zip, r-devel-gcc8: poweRlaw_0.70.2.zip, r-release: poweRlaw_0.70.2.zip, r-oldrel: poweRlaw_0.70.2.zip |
| OS X binaries: | r-release: poweRlaw_0.70.2.tgz, r-oldrel: poweRlaw_0.70.2.tgz |
| Old sources: | poweRlaw archive |
| Reverse depends: | AbSim |
| Reverse imports: | CNEr, immuneSIM, randnet, SNscan |
| Reverse suggests: | ercv, poppr, spatialwarnings |
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