bambinos/bambi

Health v2 · maintenance only

Adoption not part of the score

1296 stars · 148 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Bambi is a high-level Bayesian model-building interface for Python built on top of the PyMC probabilistic programming framework. It uses a formula-based syntax to make fitting Bayesian regression and mixed-effects models easy, particularly for social sciences and biology.

Use cases

• fit bayesian linear regression models in python
• fit mixed-effects models with a formula interface
• run bayesian hierarchical models on sleep study style data
• specify priors easily for regression models
• do bayesian statistical analysis without writing pymc code
• fit generalized linear models with bayesian inference

When to choose

• you want bayesian regression or mixed-effects models with minimal code
• you prefer formula-based model specification like R's lme4 or brms
• you already use PyMC and ArviZ and want a friendlier interface

When to avoid

• you need full control over custom probabilistic model structure
• you need non-Bayesian or frequentist modeling
• you work outside the Python/PyMC ecosystem

Facets

library · maturity active

machine-learning data-science math data-science machine-learning python cross-platform bayesian-inference pymc mixed-effects-models regression statistical-modeling formula-interface arviz statistics

Member repositories

For agents

markdown · JSON · MCP: product_card(name="bambinos/bambi")