I am a pymc3 newbie and need some guidance to handle nested hierarchical data. I am trying to port a BRMS model from R which has the following lme4 formula
y ~ x1 + x2 + x3 + (1 | x4/x5) -
where the (1 | x4/x5) notation means that the intercept can vary between x4 and also for all the x5 contained within x4. For a more detailed explanation of this notation please refer to pg.7 https://cran.r-project.org/web/packages/lme4/vignettes/lmer.pdf
To take a simple example, let’s consider the radon dataset (https://docs.pymc.io/notebooks/multilevel_modeling.html) where instead of simply focusing on the Minnesota state, we develop a model for all states and then handle counties within those states with a suitable hierarchical formulation.
How to define hyperpriors for such models?