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”
1 maintainer
Metadata
1 maintainer
Release files for BayesPowerlaw 1.1.3
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| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| BayesPowerlaw-1.1.3.tar.gz | 214.9 kB | Without provenance | Details for BayesPowerlaw-1.1.3.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
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| BayesPowerlaw-1.1.3-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details for BayesPowerlaw-1.1.3-py2.py3-none-any.whl |
Total release size: 430.6 kB
Release files / BayesPowerlaw-1.1.3.tar.gz
| Download URL | BayesPowerlaw-1.1.3.tar.gz |
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| Size | 214.9 kB |
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Release files / BayesPowerlaw-1.1.3-py2.py3-none-any.whl
| Download URL | BayesPowerlaw-1.1.3-py2.py3-none-any.whl |
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| Size | 215.7 kB |
| Tags | Python 2 Python 3 |
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