Statistical Computing II Credit Hours: 3 hours Continuation of Statistical Computing I. Advanced statistical computing techniques will be covered. Topics may include advanced MCMC methods, Expectation-Maximization methods, machine-learning algorithms, constrained optimization, density estimation, nonparametric regression perfect sampling, data visualization, and parallel computing. Students will learn methods, theory, and implementation via existing functions and their own code. Offered spring semester every even-numbered year. Prerequisites: STAT 8060 Level: Graduate
