PyMC Extras

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PyMC Extras extends PyMC with additional distributions, inference methods, and model transformations. It is maintained by the PyMC team and hosts functionality that is too specialized for the core library, but useful enough that you shouldn’t have to write it yourself.

What’s inside

• Automatic marginalization: exact for finite discrete and conjugate variables, approximate via the Laplace approximation.

• Alternative inference methods: Pathfinder, DADVI, INLA, Laplace approximation, and better MAP estimation.

• Statespace models: SARIMAX, VARMAX, ETS, and structural time series with Kalman filtering.

• Additional distributions such as DiscreteMarkovChain, GeneralizedPoisson, and GenExtreme.

• Model building tools like the as_model decorator and the ModelBuilder base class.

See the full API Reference for everything else.

Installation

To install the latest release on PyPI, you can use a package manager like pip:

pip install pymc-extras

For the development version, you can install directly from GitHub:

pip install git+https://github.com/pymc-devs/pymc-extras.git

Contributing

We welcome contributions from interested individuals or groups! For information about contributing to PyMC Extras check out our instructions, policies, and guidelines here. If you want to extend the internals (e.g. add a new marginalization), start with the Developer Guide.

Contributors

See the GitHub contributor page.