Introduction to Stochastic Processes

Catalog description

This course is an introduction to the theory of stochastic processes. Topics covered include discrete time Markov chains and key properties such as recurrence, ergodicity, stationary measures, and mixing; Poisson processes; Renewal processes; generalization to continuous time Markov processes; and a brief treatment of Martingales. Selected applications of these topics to the physical and life sciences and finance. Offered as MATH 437 and STAT 437 . Prereq: STAT 301 or STAT 312 or STAT 332 or STAT 445 or MATH 380 or Requisites Not Met permission.