STAT 243 Stochastic Processes

Includes probabilistic and statistical analysis of random processes, continuous-time Markov chains, hidden Markov models, point processes, Markov random fields, spatial and spatio-temporal processes, and statistical modeling and inference in stochastic processes. Applications to a variety of fields. (Formerly AMS 263.)


Prerequisite(s): STAT 205; or STAT 131 and STAT 132. Enrollment is restricted to graduate students, undergraduates may enroll by permission of the instructor if they've completed STAT 131 and STAT 132 (subject to instructor verification).