*****COURSES ARE SUBJECT TO CHANGE*****
Bayesian statistical methods for inference and prediction including: estimatation; model selection and prediction; exchangability; 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. Prerequisite(s): course 203. Enrollment restricted to graduate students; undergraduates may enroll by permission of instructor. A. Rodriguez
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