This class is the continuation of Probability Theory I (STAT G6105) for Statistics PhD students.
Our main topic will be stochastic processes. Distributions of stochastic processes are essentially probability measures on infinite-dimensional spaces, and we will have to learn basic analysis and measure theory on such spaces as we go along. Other topics include conditioning and martingales.
Many of these concepts are also of great importance in statistics—infinite-dimensional spaces are the natural habitat of nonparametric models, conditioning is the principal tool of Bayesian statistics, and so forth—and I will try to highlight connections between probability and statistics wherever possible.
Course Specs
Time: Mondays and Wednesdays, 10:10-11:25am.
Room: SSW 903.
Requirements: Probability Theory I.
Class Notes
- Class Notes (Version: 9 May 2016)