(STA 3047F, Fall 2001)

Time and place: Wednesdays, 6:10 to 9:00 p.m. Sidney Smith Hall room 1080. First class September 12; last class December 5.

Instructor: Professor Jeffrey S. Rosenthal, Department of Statistics, University of Toronto
Office hours TBA. Sidney Smith Hall, room 6024; phone (416) 978-4594; contact me;

Course Outline: We will investigate stochastic processes in discrete and continuous time, with emphasis on their convergence properties in various topologies (including total variation distance and weak convergence). Examples of processes will include Markov chain Monte Carlo algorithms and point processes, with additional examples selected based on student interests.

Prerequisites: STA 2111H (Graduate Probability I), or equivalent knowledge of probability theory, measure theory, and real analysis. (The course is designed primarily for Statistics PhD students.)

References: The following references may be helpful at times: Requirements: Homework 70%, Class Participation 30%. Class Participation involves attending class regularly, answering questions in class (such as helping to summarise the previous class), and posing questions in class. See HW #1, HW #2, HW #3.

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