Advanced Statistical Computing

1 Course Unit

This course covers the underlying computational methods that both underlie modern statistical and machine learning tools, as well as explicitly computational approaches to performing statistical methods. The class will cover the basics of computer arithmetic, simulation, bootstrap, jackknife and permutation methods, numerical methods for optimization and their application to statistical estimation and machine learning, nonparametric smoothing, generating random variables, and simulation methods. The course will assume familiarity with programming in the R computing environment. By the end of the course, students should be able to design and code estimation methods for sophisticated statistical models, as well as procedures to provide uncertainty about those estimates Spring Prerequisite: (STAT 1110 OR STAT 1120 OR STAT 4310 OR ESE 4020) AND (STAT 4300 OR ESE 3010) AND (MATH 1080 OR MATH 1410 OR MATH 1610) AND (MATH 2400 OR MATH 3120 OR MATH 3140) 1 Course Unit