Skip to main content

Fitting power law distributions using Bayesian Inference

Project description

BayesPowerlaw fits single or mixtures of power law distributions and estimate their exponent using Bayesian Inference, specifically Markov-Chain Monte Carlo Metropolis Hastings algorithm. See the Documentation page for details.

Installation : pip install BayesPowerlaw

Requirements

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
BayesPowerlaw-0.7b0-py2.py3-none-any.whl (461.2 kB) Copy SHA256 hash SHA256 Wheel py2.py3
BayesPowerlaw-0.7b0.tar.gz (434.4 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page