pymc
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
- Version
- 1.3
- License
- Apache License, Version 2.0
- Compatibility
- Requires Python 3.12+ and PyMC 6.0.1-compatible dependencies. Install reproducible environments with `uv pip install "pymc[nutpie]==6.0.1"`; optional NumPyro or BlackJAX samplers require separately pinned JAX-compatible dependencies.
Pinned to revision de66e10cd0c8, so it is the text this page describes rather than whatever the author pushed since.
Pre-approved tools experimental
Experimental field. Support varies between clients, so this list is what the author declared, not what your client will enforce.
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Files
- skills/pymc/SKILL.md
- skills/pymc/assets/hierarchical_model_template.py
- skills/pymc/assets/linear_regression_template.py
- skills/pymc/references/distributions.md
- skills/pymc/references/model_patterns.md
- skills/pymc/references/sampling_inference.md
- skills/pymc/references/standard_workflow.md
- skills/pymc/references/workflows.md
- skills/pymc/scripts/model_comparison.py
- skills/pymc/scripts/model_diagnostics.py
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