数学科学学院学术报告[2025] 143号

(高水平大学建设系列报告1244号)

报告题目：Model identification and selection method for varying coefficient EV models with missing responses

报告人：赵明涛 教授（安徽财经大学）

报告时间：2025年12月9日下午15:00-16:00

报告地点：#腾讯会议：405-809-173

内容摘要：In this talk, we propose a model identification and selection method for varying coefficient errors-in-variables (EV) models with missing responses, termed the imputation-based bias-corrected double-penalized estimating equation (ibbcDPEE) method. The proposed method does not need to assume in advance whether the regression coefficients in models are constants or varying coefficients. First, it utilizes B-spline basis functions to approximate the nonparametric regression coefficients. Subsequently, the bias-corrected double-penalized estimating equation (bcDPEE) is constructed based on the observed responses, while accounting for the bias in the unobserved covariates. The missing responses are then imputed via the kernel estimation technique. Lastly, the ibbcDPEE is constructed to do model identification and selection simultaneously. Under some regularity conditions, the proposed method can consistently identify and select varying coefficients and nonzero constant coefficients. Moreover, the estimators of the varying coefficients achieve the optimal convergence rate of nonparametric function estimation. The finite sample performance of the proposed method is evaluated through simulation studies and a real data analysis

报告人简历：赵明涛，安徽财经大学教授，博士生导师。主要研究方向为数理统计推断和应用统计分析，研究兴趣为复杂数据非参数和半参数统计建模和统计推断、经济金融环境资源等领域的应用统计分析。近年来，主持完成国家社科基金及省部级科研课题多项，在《统计研究》《Statistics and Computing》《Electronic Journal of Statistics》等期刊发表论文40余篇。欢迎师生参加！

邀请人：数学科学学院（周彦）

数学科学学院

2025年12月5日