BAyesian Model Building Interface in Python
Project description
Bambi
BAyesian Model-Building Interface in Python
Overview
Bambi is a high-level Bayesian model-building interface written in Python. It's built on top of the PyMC3 probabilistic programming framework, and is designed to make it extremely easy to fit mixed-effects models common in social sciences settings using a Bayesian approach.
Installation
Bambi requires a working Python interpreter (3.7+). We recommend installing Python and key numerical libraries using the Anaconda Distribution, which has one-click installers available on all major platforms.
Assuming a standard Python environment is installed on your machine (including pip), Bambi itself can be installed in one line using pip:
pip install bambi
Alternatively, if you want the bleeding edge version of the package you can install from GitHub:
pip install git+https://github.com/bambinos/bambi.git
Dependencies
Bambi requires working versions of numpy, pandas, matplotlib, patsy, pymc3, and theano. Dependencies are listed in requirements.txt
, and should all be installed by the Bambi installer; no further action should be required.
Documentation
The Bambi documentation can be found in the official docs
Citation
If you use Bambi and want to cite it please use
Here is the citation in BibTeX format
@misc{capretto2020,
title={Bambi: A simple interface for fitting Bayesian linear models in Python},
author={Tomás Capretto and Camen Piho and Ravin Kumar and Jacob Westfall and Tal Yarkoni and Osvaldo A. Martin},
year={2020},
eprint={2012.10754},
archivePrefix={arXiv},
primaryClass={stat.CO}
}
Contributions
Bambi is a community project and welcomes contributions. Additional information can be found in the Contributing Readme.
For a list of contributors see the GitHub contributor page
Code of Conduct
Bambi wishes to maintain a positive community. Additional details can be found in the Code of Conduct
License
Project details
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