MS&E 321 Stochastic Systems (Spring 2016)

Department of Management Science and Engineering,
Stanford University

Information

    Location: McMurtry Building 360
    Time: Mon. and Wed. 1:30 PM - 2:50 PM

    Instructor: Prof. Peter W. Glynn
    Email: glynn "at" stanford "dot" edu

Course Description

    This course addresses fundamental topics in the modern theory of stochastic processes, with emphasis on a broad spectrum of applications in engineering, economics, finance, and the sciences. The course carefully treats Markov chains in discrete and continuous time, Perron-Frobenius theory, Markov processes in general state space (including Harris chains), Lyapunov functions and supermartingale arguments for establishing stability, theory of regenerative processes and related coupling ideas, rare event analysis via large deviations, renewal theory, martingales, Brownian motion, and associated diffusion approximations. At the conclusion of this course, students will have a working knowledge of the mathematical tools and models that represent the cutting edge in the theory and application of stochastic processes to complex systems. The ideas will be illustrated by appealing to examples chosen from queueing theory, inventory theory, and finance.

Materials

    Course lecture notes will be distributed via Canvas.