Covers the theory of estimation, confidence intervals, hypothesis testing, and decision theory. In particular, it covers the material of APPM 5520 in greater depth, especially the topics of optimality and asymptotic approximation. Additional topics include M-estimation, minimax tests, the EM algorithm, and an introduction to Bayesian estimation and empirical likelihood techniques. Recommended Prerequisite is a one-semester calculus-based probability course such as MATH 4510 or APPM 3570. Degree credit not granted for this course and STAT 5520 or MATH 5520 or STAT 4520 or MATH 4520.
instructor(s)
Corcoran, Jem
Primary Instructor
- Fall 2019 / Fall 2020 / Fall 2021 / Fall 2022
