STAT 716 - Asymptotic Statistics

Credits: 3

This course will cover modern statistical approximation theorems relating to the current statistical and machine learning literature in Mathematical Statistics. Specific topics to be covered are: Review of Stochastic Convergence (Almost-Sure representations, Convergence of Moments, Lindeberg-Feller Central Limit Theorem, etc.), Delta Method, Moment Estimators, and M- and Z- Estimators. An additional selection of 2-4 topics will also be covered that are related to the research focus of the PhD students in the class. Prerequisites: STAT 715, STAT 684, and MATH 741.

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