MA Kouritzin
Contact
Professor, Faculty of Science - Mathematics & Statistical Sciences
- michaelk@ualberta.ca
Overview
Research
Areas
Stochastic Processes, Probability Theory and Applications
Courses
MATH 471 - Markov Models
Birth-death processes; continuous-time Markov chains; functional central limit theorem; Brownian motion; weak solutions to stochastic differential equations; weak uniqueness; filtrations; discrete and continuous martingales; martingales problems; strong Markov property; Kolmogorov forward and backward equations; stationary distributions; null and positive recurrence; transience; particle filtering. Prerequisite: STAT 281 or STAT 371. Note: Credit cannot be obtained in MATH 471 if credit has already been in STAT 471.
STAT 371 - Probability and Stochastic Processes
Problem solving of classical probability questions, random walk, gambler's ruin, Markov chains, branching processes. Selected topics of the instructor's choice. Prerequisite: STAT 265. Note: Credit can be obtained in at most one of STAT 281 or STAT 371.
STAT 471 - Probability I
Probability spaces, algebra of events. Elements of combinatorial analysis. Conditional probability, stochastic independence. Special discrete and continuous distributions. Random variables, moments, transformations. Basic limit theorems. Prerequisite: One of STAT 371 or STAT 281.