Metadata-Version: 2.1
Name: BayesPowerlaw
Version: 1.0
Summary: Fitting power law distributions using Bayesian Inference
Home-page: https://github.com/AtwalLab/BayesPowerlaw
Author: Kristina Grigaityte, Gurinder Atwal
Author-email: atwal@cshl.edu
License: MIT
Keywords: power law,bayesian inference
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Mathematics
Requires-Dist: scipy
Requires-Dist: numpy
Requires-Dist: matplotlib

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

- Python >= 3.6.2
- numpy >= 1.10.1
- scipy >= 1.0.0
- matplotlib >= 2.0.0 

- Documentation: "http://BayesPowerlaw.readthedocs.org"
- Github: "https://github.com/atwallab/BayesPowerlaw"
- PyPI: "https://pypi.python.org/pypi/BayesPowerlaw"

