Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars

Speaker:	Jiming Jiang, University of California, Davis, USA
Inviter:
Title:	A Random-effects Approach to Regression Involving Many Categorical Predictors and Their Interactions
Language:	Chinese
Time & Venue:	2023.07.30 14:00-15:00 南楼N402
Abstract:	Linear model prediction with a large number of potential predictors is both statistically and computationally challenging. The traditional approaches are largely based on shrinkage selection/estimation methods, which are applicable even when the number of potential predictors is (much) larger than the sample size. A situation of the latter scenario occurs when the candidate predictors involve many binary indicators corresponding to categories of some categorical predictors as well as their interactions. We propose an alternative approach to the shrinkage prediction methods in such a case based on mixed model prediction, which effectively treats combinations of the categorical effects as random effects. We establish theoretical validity of the proposed method, and demonstrate empirically its advantage over the shrinkage methods. We also develop measures of uncertainty for the proposed method and evaluate their performance empirically. A real-data example is considered. This work is joint with Hanmei Sun of Shandong Normal University, China.