STAT 680

Bayesian Statistics

Topics include Bayesian inference, Loss function and Risk, One parameter models and posterior inference, conjugate priors, non-informative priors, Multi parameter models, Bayesian computation, Gibbs sampling and Markov Chain Monte Carlo Methods and Applications in different areas. Additional topics may include Decision theory, Theoretical and convergence properties of the Markov chain samplers, Bayesian model checking, selection and assessment criteria, Hierarchical models, Bayesian survival analysis

Units: 3.0