BayesPowerlaw¶
Written by Kristina Grigaityte.


BayesPowerlaw is a Python package that fits a single or a mixture of power law distributions to data using a Bayesian inference approach. Posterior distributions of parameters are numerically determined by Markov chain Monte Carlo sampling. In addition, the package provides capability for - power law simulations - data plotting - maximum likelihood estimation
Installation¶
BayesPowerlaw can be installed from PyPI using the pip package manager (version 9.0.0 or higher). At the command line:
pip install BayesPowerlaw
The code for BayesPowerlaw is open source and available on GitHub.
Quick Start¶
To make the figures shown above, type this from within Python:
import BayesPowerlaw as bp
bp.demo()
Contact¶
For technical assistance or to report bugs, please contact Kristina Grigaityte.
For general correspondence, please contact Gurinder (Mickey) Atwal.