Fall 2008 - 5214 Topics in Analysis
CRN #96482 MWF 1:25-2:15 McBryde #204
Introduction to Stochastic Processes
This course will be an introduction to stochastic processes, presented
at a level appropriate for beginning graduate students and
well-prepared undergraduates. The course will cover topics such
as Markov chains, random walks, classical continuous time processes
(branching and birth & death processes for example), Brownian
motion and diffusions, Kolmogorov forward and backward equations.
Other possible topics include stopping time problems, chemical
kinetic processes, simulations (Gillespie algorithm and methods for
stochastic differential equations). The course will span two
semesters, continuing in Spring 2009.
Students from all disciplines are welcome. As background students
will need to be familiar with infinite series and basic linear ordinary
differential equations. Students simultaneously enrolled in Math
4225 should be adequately prepared. (The course will not
assume or rely on measure theory.) As a text we will use G. Grimmett and D.
Stirzaker, Probability and Random Processes [QA273 G74 1992] (but
the 2001 edition), supplemented with additional resources as needed for
topics in the second semester.
For further information contact Prof. M. Day.