Mathematics 216: Applied Stochastic Processes

Mathematics 216: Applied Stochastic Processes (Spring 2003)

Instructor

Description

This is an introduction to stochastic processes without measure theory. Topics include: Markov chains (discrete and continuous time) including queueing and branching processes; martingles; optimal stopping; renewal theory; Brownian motion and stochastic integration.

There will be weekly assignments including a large assignment at the end of the semester which serves as a take-home final exam.

Prerequisites

Math 104 and Math 135 or the equivalent.

Text(s)

Introduction to Stochastic Processes, by Greg Lawler (Chapman & Hall/CRC).

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Last modified: 29 October 2002