Academics
  /  
Courses
  /  
Descriptions
IEMS 435: Stochastic Simulation


VIEW ALL COURSE TIMES AND SESSIONS

Prerequisites

Probability, stochastic processes, statistics, and real analysis at the undergraduate engineering or mathematics level; computer programming in Python; and graduate standing. It is recommended to take IEMS 460-1 (Stochastic Processes I) at the same time.

Description

Topics

  • Discrete event simulation modeling
  • Design and analysis of simulation experiments
  • Simulation optimization
  • Variance reduction & rare event simulation
  • MCMC, steady-state simulation, and exact methods

Materials

  • Asmussen, S., & Glynn, P. W. (2007). Stochastic simulation: algorithms and analysis (Vol. 57). Springer Science & Business Media. A pdf version of the book is free to Northwestern students connecting from inside the northwestern.edu domain.
  • Glasserman, P. (2013). Monte Carlo methods in financial engineering (Vol. 53). Springer Science & Business Media. A pdf version of the book is free to Northwestern students connecting from inside the northwestern.edu domain.
  • Nelson, B. (2013). Foundations and methods of stochastic simulation: a first course. Springer Science & Business Media. A pdf version of the book is free to Northwestern students connecting from inside the northwestern.edu domain at https://link.springer.com/book/10.1007/978-1-4614-6160-9.
  • Owen, A. (2019+). Monte Carlo theory, methods and examples. A Book in Progress. pdf files are available at https://statweb.stanford.edu/~owen/mc/