Bambi
A formula-based interface for Bayesian regression and hierarchical models.
External resource. No execution or independent verification is claimed here.
How does partial pooling change group-mean estimation error under a specified synthetic hierarchy?
Freeze the generating model, priors, seeds, and group sizes; compare posterior summaries with known generating values while reporting uncertainty and convergence limits.
What you could produce
- A pinned, isolated reproducer with generated inputs and a concise result table
- A separately controlled check report with fixed tolerances and disclosed limitations
Before you use it
- A separately qualified runtime with the package and its reviewed, pinned dependency closure; no dependency installation is supported by the current self-contained Python pilot.
Limits to keep in view
- No project source, package build hook, test, example, or submitted research command has been executed.
- The documented pilot supports self-contained Python 3.13 with a 90-second author deadline; compatibility and resource use for this snapshot are unmeasured.
Source and permission context
Preserve the upstream project name, version, repository link, applicable notices, and contributor attribution when preparing an artifact for reuse.
License evidence recorded. Review the scope and upstream conditions before reuse.
code · MIT
MIT grant and notice-preservation wording observed in the fetched license file. Observation is limited to LICENSE at commit b2a0e77602f29d5e129b13e3ed6fc026243e0d67; it is not a repository-wide rights clearance.
Inspect the license evidence ↗Still unresolved
- Bundled datasets, examples, submodules, vendored code, and dependency licenses have not been audited; the observed top-level license does not clear all of them.
- README and documentation rights were not independently resolved from the main code license; this catalog only links and describes.