主 题：Linear Hypothesis Testing in Linear Models with High Dimensional Responses
地 点：线上Zoom会议ID: 82143638771密码：251442
In this paper, we propose a new projection test for linear hypotheses on regression coefficient matrices in linear models with high dimensional responses. We systematically study the theoretical properties of the proposed test. We first derive the optimal projection matrix for any given projection dimension to achieve the best power and provide an upper bound for the optimal dimension of projection matrix. We further provide insights into how to construct the optimal projection matrix. One- and two-sample mean problems can be formulated as special cases of linear hypotheses studied in this paper. We both theoretically and empirically demonstrate that the proposed test can outperform the existing ones for one- and two-sample mean problems. We conduct Monte Carlo simulation to examine the finite sample performance and illustrate the proposed test by a real data example.
李润泽是宾州州立大学冠名讲习教授。他的主要研究方向有高维变量选择及超高维变量筛选，半参数和非参数回归建模。他是IMS, ASA和AAAS的Fellow。他曾是Annals of Statistics的副主编，主编。他现在是Journal of American Statistical Association的副主编。