Statistics 609 (spring 2012)

Empirical Processes

Instructor: David Pollard
When: MW 1:00-2:15
Where: 24 Hillhouse Room 107
Office hours: TBA
TA: none
Short description: A rigorous discussion of probabilistic methods distilled from the empirical process literature. Chaining arguments; maximal inequalities; symmetrization and combinatorial entropy; VC dimension and beyond; bracketing; concentration of measure; majorizing measures; uniform laws of large numbers and Donsker theorems. Applications to asymptotics for statistical inference and econometrics. Assumes knowledge of probability theory at the level of Stat 600.
Grading: To be discussed in first lecture