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.

View on GitHub Website

114 Stars

25 Forks

114 Watchers

R Language

100 SrcLog Score

Cost to Build

$1.07M

Market Value

$2.32M

How is this calculated?

Growth over time

8 data points · 2021-08-01 → 2026-04-01

Stars Forks Watchers

💬

How do you feel about this project?

Ask AI about poweRlaw

Question copied to clipboard

What is the csgillespie/poweRlaw GitHub project? 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 cutoff for the scaling region.". Written in R. Explain what it does, its main use cases, key features, and who would benefit from using it.

Question is copied to clipboard — paste it after the AI opens.

How to clone poweRlaw

Clone via HTTPS

git clone https://github.com/csgillespie/poweRlaw.git

Clone via SSH

[email protected]:csgillespie/poweRlaw.git

Download ZIP

Download master.zip

Found an issue?

Report bugs or request features on the poweRlaw issue tracker:

Open GitHub Issues

Similar to poweRlaw

LightGBM prophet graal mal h2o-3 ggplot2 awesome-R catboost shiny dplyr data-science-at-the-command-line devtools knitr benchm-ml r4ds plotly.R adv-r rmarkdown DataScienceR mlr DiagrammeR awesome-quant IRkernel arl swirl blogdown broom wesanderson httr plumber