国产a片 学术报告[2026]046号

(高水平大学建设系列报告1305号)

报告题目：Estimation and inference of high-dimensional factor augmented regression model

报告人： 郭旭 教授 （北京师范大学）

报告时间：2026年5月14日下午15:30-16:30

报告地点：校友广场304会议室

报告摘要：Factor model is a powerful tool to deal with high correlations among predictors. It has also been incorporated in regression analysis. In this talk, I will share recent developments about estimation and inference of high-dimensional factor augmented regression model. We first address the concern whether it is necessary to consider the augmented part. Existing test procedures do not perform well under dense alternatives. To address this critical issue, we introduce a novel quadratic-type test statistic which can efficiently detect dense alternative hypotheses. We further propose an adaptive test procedure to remain powerful under both sparse and dense alternative hypotheses. We further investigate the penalized estimation of the single-index models with latent factors. With estimated latent factors, we establish the error bounds of the estimators. Lastly, we introduce debiased estimator and construct confidence interval for individual coefficient based on the asymptotic normality. Simulation studies and real data analysis are conducted to illustrate the proposed methods.

报告人简介：郭旭，现任北京师范大学统计学院教授，博士生导师。曾荣获北京师范大学第十一届“最受本科生欢迎的十佳教师”，北京师范大学第十八届“青教赛”一等奖和北京市第十三届“青教赛”三等奖。目前主要关注高维回归模型中的假设检验问题也对基于机器学习算法的统计推断感兴趣，有多篇文章发表在统计学和计量经济学国际顶尖期刊包括JRSSB, JASA, Biometrika, JOE和JMLR，担任统计学国际知名期刊JMVA副主编。

欢迎师生参加！

邀请人：王江洲

国产a片

2026年5月11日