Bayesian Statistics and Data Analysis

Catalog description

Priors, posteriors, Bayes estimators, decision theory, asymptotic theory, Bayes factors, credible regions, hierarchical models, nonparametric Bayes, computational methods, Bayesian robustness, and applications. This is a theory-oriented course intended for PhD students. For a more applied introduction to Bayesian statistics, students should take STSCI 4780 , Bayesian Data Analysis: Principles and Practice, which is offered in the spring.