Learn R Programming
⚠️There's a newer version (0.80.0) of this package.Take me there.

poweRlaw (version 0.30.1)

Analysis of Heavy Tailed Distributions

Description

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.

Copy Link

Version

Install

install.packages('poweRlaw')

Monthly Downloads

5,858

Version

0.30.1

License

GPL-2 | GPL-3

Issues

0

Pull Requests

0

Stars

114

Forks

24

Maintainer

Colin Gillespie

Last Published

March 13th, 2015

Functions in poweRlaw (0.30.1)

moby

Moby Dick word count
bootstrap_moby

Example bootstrap results for the full Moby Dick data set
dist_rand

Random number generation for the distribution objects
dist_pdf

The probability density function (pdf)
estimate_pars

Estimates the distributions using mle.
dist_all_cdf

The data cumulative distribution function
dist_cdf

The cumulative distribution function (cdf)
native_american

Casualities in the American Indian Wars (1776 and 1890)
dplcon

The continuous powerlaw distribution Density and distribution function of the continuous power-law distribution, with parameters xmin and alpha.
dpldis

Discrete powerlaw distribution
dist_ll

The log-likelihood function
poweRlaw-package

The poweRlaw package
bootstrap

Estimating the lower bound (xmin)
swiss_prot

Word frequency in the Swiss-Prot data base
compare_distributions

Vuong's test for non-nested models
population

City boundaries and the universality of scaling laws
plot.bs_xmin

Plot methods for bootstrap objects
conexp-class

Heavy-tailed distributions
show,distribution-method

Generic show method for distribution objects
lines,distribution-method

Generic plotting functions