Biostatistics and Medical Informatics Department Seminar with Yuan Ji, University of Chicago

Dr. Ji will discuss a class of nonparametric Bayesian models called the Shared Atoms Model (SAM) based on the dependent Dirichlet processes and present a real world model. SAM uses a simple idea of atom skipping to generate group specific patterns of clustering, allow atoms to be common, unique, and shared across multiple groups. In finite data sets, SAM clusters experimental units in a similar fashion, facilitating interpretable and flexible inference.