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poweRlaw (version 0.20.1)

Fitting heavy tailed distributions: the poweRlaw package

Description

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 cut-off for the scaling region.

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Install

install.packages('poweRlaw')

Monthly Downloads

5,858

Version

0.20.1

License

GPL-2 | GPL-3

Issues

0

Pull Requests

0

Stars

114

Forks

24

Maintainer

Gillespie Colin

Last Published

June 25th, 2013

Functions in poweRlaw (0.20.1)

poweRlaw-package

The poweRlaw package
swiss_prot

Word frequency in the Swiss-Prot data base
dist_data_cdf

The data cumulative distribution function
population

City boundaries and the universality of scaling laws
lines

Plotting functions
conpl

Heavy-tailed distributions
moby

Moby Dick word count
dist_cdf

The cumulative distribution function (cdf)
dist_rand

Random number generation for the distribution objects
native_american

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

The probability density function (pdf)
bootstrap_moby

Example bootstrap results for the full Moby Dick data set
estimate_pars

Estimates the distributions using mle.
compare_distributions

Vuong's test for non-nested models
dplcon

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

The log-likelihood function
dpldis

Discrete powerlaw distribution.
bootstrap_p

Estimates the lower bound (xmin)