poweRlaw
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 cutoff for the scaling region.
Science Score: 49.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 4 DOI reference(s) in README -
✓Academic publication links
Links to: arxiv.org -
○Committers with academic emails
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (18.5%) to scientific vocabulary
Keywords
clauset
cran
powerlaw
r
Last synced: 6 months ago
·
JSON representation
Repository
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 cutoff for the scaling region.
Basic Info
- Host: GitHub
- Owner: csgillespie
- Language: R
- Default Branch: main
- Homepage: http://csgillespie.github.io/poweRlaw/
- Size: 16.3 MB
Statistics
- Stars: 113
- Watchers: 17
- Forks: 24
- Open Issues: 1
- Releases: 2
Topics
clauset
cran
powerlaw
r
Created about 13 years ago
· Last pushed about 1 year ago
Metadata Files
Readme
Changelog
README.Rmd
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# The poweRlaw package
[](https://app.codecov.io/github/csgillespie/poweRlaw?branch=master)
[](https://cran.r-project.org/package=poweRlaw)
[](https://cran.r-project.org/package=poweRlaw)
This package implements both the discrete and continuous maximum likelihood estimators for fitting the power-law distribution to data using the methods described in [Clauset et al, 2009](http://arxiv.org/abs/0706.1062). It also provides function to fit log-normal and Poisson distributions. Additionally, a goodness-of-fit based approach is used to estimate the lower cut-off for the scaling region.
The code developed in this package was influenced from the python and R code found at Aaron Clauset's website. In particular, the R code of Laurent Dubroca and Cosma Shalizi.
To cite this package in academic work, please use:
Gillespie, C. S. "*Fitting heavy tailed distributions: the poweRlaw package.*" Journal of Statistical Software, 64(2) 2015. ([pdf](https://doi.org/10.18637/jss.v064.i02)).
For a different way of handling powerlaw type distributions, see
Gillespie, C.S. "
*Estimating the number of casualties in the American Indian war: a Bayesian analysis using the power law distribution.*" Annals of Applied Statistics, 2017. ([pdf](https://doi.org/10.1214/17-AOAS1082))
Installation
------------
This package is hosted on [CRAN](https://cran.r-project.org/package=poweRlaw) and can be installed in the usual way:
```{r, eval =FALSE}
install.packages("poweRlaw")
```
Alternatively, the development version can be install from from github using the devtools package:
```{r, eval = FALSE}
install.packages("devtools")
devtools::install_github("csgillespie/poweRlaw")
```
Getting Started
---------------
To get started, load the package
```{r}
library("poweRlaw")
```
then work through the four vignettes (links to the current CRAN version):
* [Getting started](https://cran.r-project.org/package=poweRlaw/vignettes/a_introduction.pdf)
* [Worked examples](https://cran.r-project.org/package=poweRlaw/vignettes/b_powerlaw_examples.pdf)
* [Comparing distributions](https://cran.r-project.org/package=poweRlaw/vignettes/c_comparing_distributions.pdf)
* [JSS paper](https://cran.r-project.org/package=poweRlaw/vignettes/d_jss_paper.pdf)
Alternatively, you can access the vignettes from within the package:
```{r, eval =FALSE}
browseVignettes("poweRlaw")
```
The plots below show the line of best fit to the Moby Dick and blackout data sets (from Clauset et al, 2009).
Other information
-----------------
* Unfortunately, I can no longer commit time to adding new feature
If you find bugs, please use the github [issue tracker](https://github.com/csgillespie/poweRlaw/issues)
* Feel free to submit pull requests
* Data was originally obtained from Arron Clausett's website. But this site is no longer
available.
---
Development of this package was supported by [Jumping Rivers](https://www.jumpingrivers.com)
Owner
- Name: Colin Gillespie
- Login: csgillespie
- Kind: user
- Location: Newcastle, UK
- Company: Newcastle University
- Website: https://www.jumpingrivers.com
- Twitter: csgillespie
- Repositories: 62
- Profile: https://github.com/csgillespie
Author of Efficient R programming. R consultant with Jumping Rivers and Senior Statistics lecturer at Newcastle University.
GitHub Events
Total
- Create event: 3
- Release event: 1
- Issues event: 11
- Watch event: 5
- Delete event: 1
- Issue comment event: 7
- Push event: 12
- Pull request event: 5
Last Year
- Create event: 3
- Release event: 1
- Issues event: 11
- Watch event: 5
- Delete event: 1
- Issue comment event: 7
- Push event: 12
- Pull request event: 5
Committers
Last synced: 9 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Colin Gillespie | c****e@g****m | 481 |
| csgillespie | b****s@t****m | 9 |
| Luiz Max Carvalho | l****o@u****r | 7 |
| mpadge | m****m@e****m | 5 |
| Zhongpeng Lin (林中鹏) | l****p@g****m | 3 |
| Max Joseph | m****h@g****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 94
- Total pull requests: 13
- Average time to close issues: 11 months
- Average time to close pull requests: 6 months
- Total issue authors: 46
- Total pull request authors: 6
- Average comments per issue: 2.31
- Average comments per pull request: 1.62
- Merged pull requests: 10
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 2
- Pull requests: 4
- Average time to close issues: 2 months
- Average time to close pull requests: about 9 hours
- Issue authors: 2
- Pull request authors: 1
- Average comments per issue: 1.0
- Average comments per pull request: 0.0
- Merged pull requests: 4
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- csgillespie (30)
- lsaravia (6)
- linzhp (4)
- anilaba (3)
- haikolietz (3)
- Lvulis (2)
- dbmehta (2)
- damienchallet (2)
- jkeirstead (2)
- jcredberry (2)
- changshuaili (2)
- LaurentFranckx (2)
- xerroxcopy (1)
- scais (1)
- jpgoldberg (1)
Pull Request Authors
- csgillespie (7)
- mpadge (2)
- mbjoseph (1)
- maxbiostat (1)
- linzhp (1)
- khemeia (1)
Top Labels
Issue Labels
enhancement (14)
bug (8)
Documentation (7)
Fix in progress (2)
question (1)
Pull Request Labels
Packages
- Total packages: 2
-
Total downloads:
- cran 5,440 last-month
- Total docker downloads: 45,529
-
Total dependent packages: 9
(may contain duplicates) -
Total dependent repositories: 17
(may contain duplicates) - Total versions: 24
- Total maintainers: 1
cran.r-project.org: poweRlaw
Analysis of Heavy Tailed Distributions
- Homepage: https://github.com/csgillespie/poweRlaw
- Documentation: http://cran.r-project.org/web/packages/poweRlaw/poweRlaw.pdf
- License: GPL-2 | GPL-3
-
Latest release: 1.0.0
published about 1 year ago
Rankings
Forks count: 3.2%
Stargazers count: 3.7%
Dependent packages count: 6.1%
Downloads: 6.7%
Dependent repos count: 7.1%
Average: 7.8%
Docker downloads count: 19.8%
Maintainers (1)
Last synced:
6 months ago
conda-forge.org: r-powerlaw
- Homepage: https://github.com/csgillespie/poweRlaw
- License: GPL-2 | GPL-3
-
Latest release: 0.70.6
published almost 6 years ago
Rankings
Dependent repos count: 24.4%
Stargazers count: 33.6%
Forks count: 34.2%
Average: 35.9%
Dependent packages count: 51.6%
Last synced:
6 months ago
Dependencies
DESCRIPTION
cran
- R >= 3.4.0 depends
- methods * imports
- parallel * imports
- pracma * imports
- stats * imports
- utils * imports
- covr * suggests
- knitr * suggests
- testthat * suggests