PyMC-Extras (version 0.10.0) serves as an experimental extension library for PyMC, providing a sandbox for new probability distributions, advanced model fitting algorithms, and other specialized code not yet integrated into the main PyMC repository. It aims to offer bleeding-edge features to users, with a flexible release cadence tied to the development cycle of its experimental components.
pip install pymc-extrasVerified import paths — ran on the pinned version, not inferred.
Demonstrates defining a PyMC model using a specialized distribution, `LogitNormal`, from `pymc-extras`. This illustrates how to seamlessly integrate `pymc-extras` components into a standard PyMC workflow, typically followed by sampling if observed data is provided.
Treat `pymc-extras` components as potentially unstable; review release notes for updates and consider migrating critical production code to stable PyMC features where available.
Always use a recent, stable version of PyMC (`pip install --upgrade pymc`) alongside `pymc-extras`. Check the `pymc-extras` README or documentation for specific PyMC version requirements.
Regularly check PyMC release notes and `pymc-extras` updates. If a feature moves to core PyMC, consider updating your code to use the official PyMC implementation for long-term stability and maintenance.
Install the library using pip: `pip install pymc-extras`
Verify the correct spelling and existence of the distribution in the `pymc-extras` documentation or by inspecting the module contents (e.g., `dir(pmx_dist)` if imported as `pmx_dist`).
Ensure both PyMC and `pymc-extras` are up-to-date (`pip install --upgrade pymc pymc-extras`). Review the documentation for the specific distribution's parameter requirements. If issues persist, consider isolating the problem in a minimal reproducible example.