Chapter 6
Modeling with Bambi
A good tool improves the way you work. A great tool improves the way you think. – Jeff Duntemann
In Chapter 4, we described the basic ingredients of linear regression models and how to generalize them to better fit our needs. In this chapter, we are going to keep learning about linear models, but this time, we are going to work with Bambi [Capretto et al., 2022], a high-level Bayesian model-building interface written on top of PyMC. Bambi is designed to make it extremely easy to fit linear models, including hierarchical ones. We will see that Bambi’s domain is more comprehensive than just linear models.
We are going to learn about:
Using Bambi to build and fit models
Analyzing results with Bambi
Polynomial regression and splines
Distributional models
Categorical predictors
Interactions
Variable selection with Kulprit
