Statistics Colloquium: STA 290
Tuesday, February 4th at 4:10pm, MSB 1147 (Colloquium Room) Refreshments at 3:30pm in MSB 4110 (4th floor lounge)
Speaker: Yanyuan Ma, Texas A&M University
Title: "A Semiparametric View to Dimension Reduction: Estimation, Inference and Efficiency"
Abstract: We provide a novel and completely different approach to dimension-reduction problems from the existing literature. We cast the dimension-reduction problem in a semiparametric estimation framework and derive estimating equations. Viewing this problem from the new angle allows us to derive a rich class of estimators, and obtain the classical dimension reduction techniques as special cases in this class. The semiparametric approach also reveals that in the inverse regression context while keeping the estimation structure intact, the common assumption of linearity and/or constant variance on the covariates can be removed at the cost of performing additional nonparametric regression. We further illustrate how to perform inference and derive efficient estimators with proper parameterization. Very different results are obtained in different common dimension reduction models.
This talk is based on joint work with Liping Zhu.
NOTE: Students enrolled in BST 290 would be expected to attend this seminar