


# The poweRlaw package

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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
install.packages("poweRlaw")
```

Alternatively, the development version can be install from from github
using the devtools package:

``` r
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
browseVignettes("poweRlaw")
```

The plots below show the line of best fit to the Moby Dick and blackout
data sets (from Clauset et al, 2009).

Cumulative CDF of the Moby Dick and blackout data sets with line of best fit.

Cumulative CDF of the Moby Dick and
blackout data sets with line of best fit.

## 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)
