Hamiltonian Monte Carlo for Hierarchical Models

Understand

Hierarchical modeling provides a framework for modeling the complex interactions typical of problems in applied statistics.

• By capturing these relationships, however, hierarchical models also introduce distinctive pathologies that quickly limit the efficiency of most common methods of in- ference.
• In this paper we explore the use of Hamiltonian Monte Carlo for hierarchical models and demonstrate how the algorithm can overcome those pathologies in practical applications.