Simulation for Stochastic Systems. 3 credits, 3 contact hours

Catalog description

Covers the use of Monte Carlo stochastic simulation for data science, finance, and other applications. Topics include generation of various random variables and stochastic processes (e.g., point processes, Brownian motion, diffusions), simulation methods for estimating quantities of interest (e.g., probabilities, expected values, quantiles), input modeling, and variance-reduction techniques. Simulation programming assignments will be included. Students cannot receive credit for both CS 661 and CS 666/ MATH 666 .