I implemented it for the normally distributed hierarchical variables (function model.hierarchical_normal), however it could be that a partial hierarchical parametrization is better from an sampling standpoint (see pdf above). Unsure whether it is worse digging deeper into it.
In order to parametrize better the hierarchical model, a non-centered parametrical distribution is better when the data is not very informative, see for example: https://docs.pymc.io/notebooks/Diagnosing_biased_Inference_with_Divergences.html or https://pdfs.semanticscholar.org/7b85/fb48a077c679c325433fbe13b87560e12886.pdf
I implemented it for the normally distributed hierarchical variables (function model.hierarchical_normal), however it could be that a partial hierarchical parametrization is better from an sampling standpoint (see pdf above). Unsure whether it is worse digging deeper into it.