Bambi is a high-level Bayesian model-building interface written in Python. It works with the PyMC probabilistic programming framework. Bambi provides an interface to build and solve Bayesian generalized (non-)linear multivariate multilevel models.
Bambi is an open source project, developed by the community and is an affiliated project of NumFOCUS.
Etymology
Bambi is an acronym for BAyesian Model-Building Interface.
Library features
- Model specification using a Wilkison-like formula style
- Bayesian inference using MCMC and Variational Inference methods
- Interface with ArviZ, as Bambi returns an object
- Model interpretation via conditional adjusted comparisons, predictions, and slopes
- A wide array of response families
- Default priors that the users can modify if needed
See also
- Stan, a probabilistic programming language for statistical inference written in C++
References
External links