rmcelreath/rethinking

Health v2 · maintenance only

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2419 stars · 626 forks observed · 2026-08-28

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

An R package accompanying McElreath's Statistical Rethinking book and course on Bayesian data analysis. It provides tools for quadratic approximation and Hamiltonian Monte Carlo via RStan or cmdstanr, requiring models to be specified as explicit lists of distributional assumptions for teaching purposes.

Use cases

• learn Bayesian data analysis with the Statistical Rethinking book
• fit Bayesian generalized linear models with quadratic approximation
• run Hamiltonian Monte Carlo sampling through Stan
• specify statistical models as explicit distributional assumptions
• work through course exercises without installing Stan using the slim version
• teach students Bayesian modeling by writing out every model detail

When to choose

• you are following the Statistical Rethinking course or book
• you want a teaching-oriented Bayesian modeling tool with explicit model specification
• you need both quick quadratic approximation and full MCMC in one package

When to avoid

• you need a production-grade Bayesian workflow with formula-based syntax
• you require a CRAN-installable package
• you want automated or black-box model fitting rather than explicit assumptions

Facets

library · maturity active

machine-learning data-science developer-tools data-science education tutorials python cross-platform bayesian-statistics r-package mcmc stan quadratic-approximation teaching statistical-modeling hamiltonian-monte-carlo textbook-companion

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