Rutgers University 3 credits Statistics
An introduction to Bayesian statistical modeling, inference, and computation. Single- and multiparameter models, hierarchical models, model checking, evaluation, selection, sensitivity analysis and prediction. Bayesian decision analysis. Monte Carlo and Markov chain Monte Carlo (Metropolis-Hastings, Gibbs). Select topics in advanced Bayesian computation, e.g. Hamiltonian Monte Carlo and approximate Bayesian computation. Prerequisite: 16:960:582 or 16:960:592, 16:960:583 and level IV statistics.
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