STAT 206B Intermediate Bayesian Inference

Bayesian statistical methods for inference and prediction including: estimation; model selection and prediction; exchangeability; prior, likelihood, posterior, and predictive distributions; coherence and calibration; conjugate analysis; Markov Chain Monte Carlo methods for simulation-based computation; hierarchical modeling; Bayesian model diagnostics, model selection, and sensitivity analysis. (Formerly AMS 206B.)


Prerequisite(s): STAT 203. Enrollment is restricted to graduate students. Undergraduates may enroll by permission (STAT 131 and 132 have to be verified by the instructor directly with the student).