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pymc-modeling

maintained by fonnesbeck

star 11 account_tree 2 verified_user MIT License
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Bayesian statistical modeling with PyMC v5+. Use when building probabilistic models, specifying priors, running MCMC inference, diagnosing convergence, or comparing models. Covers PyMC, ArviZ, pymc-bart, pymc-extras, nutpie, and JAX/NumPyro backends. Triggers on tasks involving: Bayesian inference, posterior sampling, hierarchical/multilevel models, GLMs, time series, Gaussian processes, BART, mixture models, prior/posterior predictive checks, MCMC diagnostics, LOO-CV, WAIC, model comparison, or causal inference with do/observe.

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Skill Details

GitHub Stars 11
GitHub Forks 2
Created Jan 2026
Last Updated 3 months ago
tools tools machine learning

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