✳flâneur — a map of the web's best reading

Hierarchical Modeling

betanalpha.github.io · 1,135 words · saved by 1 readers

Hierarchical modeling is a powerful technique for modeling heterogeneity and, consequently, it is becoming increasingly ubiquitous in contemporary applied statistics. Unfortunately that ubiquitous application has not brought with it an equivalently ubiquitous understanding for how awkward these models can be to fit in practice. In this case study we dive deep into hierarchical models, from their theoretical motivations to their inherent degeneracies and the strategies needed to ensure robust computation. We'll learn not only how to use hierarchical models but also how to use them robustly.

Hierarchical Modeling Hierarchical Modeling Michael Betancourt November 2020 Hierarchical modeling is a powerful technique for modeling heterogeneity and, consequently, it is becoming increasingly ubiquitous in contemporary applied statistics. Unfortunately that ubiquitous application has not brought with it an equivalently ubiquitous understanding for how awkward these models can be to fit in practice. In this case study we dive deep into hierarchical models, from their theoretical motivations to their inherent degeneracies and the strategies needed to ensure robust computation. We'll learn n

Explore this link on the map →

saved by

related reading