Computational Statistics

This course will cover efficient methods for obtaining numerical solutions to statistical problems. Topics include numerical optimization in statistical inference [expectation-maximization (EM) algorithm, Fisher scoring, etc.], Monte Carlo methods, random number generation, jackknife methods, bootstrap methods, kernel density estimation, and splines.