Advanced numerical methods and algorithms for statistical computing, emphasizing techniques relevant to modern Bayesian statistical research. Topics drawn from: numerical linear algebra, optimization, advanced Monte Carlo simulation and integration, approximate Bayesian computation, variational methods, belief propagation, distributed computing, and other areas of current research. Prerequisite: Statistical Science 831, 832.
Statistical Science