MATH 628 Computational Methods in Statistics

Random variable generation, Monte Carlo methods and numerical integration, Bayesian inference and Markov chain Monte Carlo, Metropolis-Hastings and Gibbs Sampling, basics of numerical optimization such as Newton's method, constrained optimization, Expectation-Maximization algorithms. Prerequisite: MATH 620 or DSCI 602 or permission of the department chairperson.

Credits

3