报告题目：Unified Variable Selection for Varying Coefficient Models with Longitudinal Data

报告摘要：Variable selection for varying coefficient models (VCM) includes the separation of varying and constant effects, and the selection of variables with nonzero varying effects and those with nonzero constant effects. In our work, we propose a unified variable selection approach called the double-penalized quadratic inference functions (DPQIF) method for VCM with longitudinal data. The proposed method can not only separate varying coefficients and constant coefficients, but also estimate and select the nonzero varying coefficients and nonzero constant coefficients. It is suitable for variable selection of linear models, VCM, and partial linear VCM. Under some regularity conditions, the DPQIF is consistent in both separation and selection of varying coefficients and constant coefficients. The resulting estimators of varying coefficients possess the optimal convergence rate of non-parametric function estimation, and the estimators of nonzero constant coefficients are consistent and asymptotically normal. Finally, we investigate the finite sample performance of the proposed method through simulation studies and a real data analysis. The results show that our proposed method performs better than the existing competitor.

报告人简介：赵明涛，男，中共党员，安徽财经大学统计与应用数学学院教授，硕士生导师，博士生导师（兼）。哈尔滨工业大学理学学士、硕士，中国人民大学统计学博士，爱尔兰科克大学访问学者（2018.1-2018.3）、美国密歇根州立大学（统计与概率系）高级访问学者(2019.1-2020.4)。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统计分析、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1项、省部级科研课题3项，主持省部级以上教研课题8项，出版专著1本（独撰），出版省级规划/一流教材1本（副主编），获得省级科研获奖2项、教研获奖4项。在《统计研究》《Journal of Systems Science and Complexity》《Journal of Applied Statistics》《Journal of Computational and Applied Mathematics》《Electronic Journal of Statistics》《Statistical and probability Letters》《Communications in Statistics - Theory and Methods》《Random Matrices: Theory and Application》《Computational Statistics》《Petroleum Science》等期刊发表论文30余篇。

报告时间：2024年1月8日（周一）14:30-15:30

报告地点：理学院东一503

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