STAT7330 - Bayesian Data Analysis

STAT 7330 Bayesian Data Analysis (3 semester credit hours) Bayesian modeling fundamentals; prior distributions; large-sample theory and connection with classical inference; model checking and evaluation; Markov chain Monte Carlo methods, including Gibbs, Metropolis and related algorithms; convergence diagnostics; approximation of posterior mode and posterior density; single and multiparameter models such as those based on binomial, Poisson and normal distributions; regression models, including linear models, hierarchical linear models, generalized linear models, and basis function models; models for missing data; and implementation of methods using a software package. Prerequisite: STAT 6337 or instructor consent required. (3-0) T