报告题目：Partial Consistency and Its Applications to Semiparametric Regression Model
报告人：彭衡 香港浸会大学
时间：4月17日（周四）下午15:00-16:00
地点：创新港涵英楼经济金融研究院8121会议室
报告摘要：
For semiparametric regression models, the nonparametric components are often used to reduce the bias of the regression models and improve the stability of the estimate of parametric components in the regression models. Motivated by the partial consistency phenomena which were proposed by Neyman and Scott (1948), regarding the nonparametric components in the model as the so-called incidental parameters and utilizing recent theoretical results in high dimensional statistical modeling, a flexible yet computationally simple approach is proposed to estimate the partially linear models and varying coefficient models, and the variance of errors in the models. The proposed methods are easy to implement and are efficient enough for further inference. Hence, the proposed methods balanced the computation complexity and statistical efficiency of the statistical estimate and provided new insight into the trade-off between the bias and variance of the statistical model estimation.
报告人简介：
彭衡，现为香港浸会大学数学系教授，2003年从香港中文大学学取得统计学博士学位，2003年-2006年在普林斯顿大学做博士后。主要从事非参数与半参数模型、模型选择、高维数据建模、混合模型等领域的研究。当选IMS会员，曾担任Statistica Sinica副主编（2011-2014），现为Computational Statistics and Data Analysis副主编；担任AoS, JASA, JRSSB, Biometrika, Statistica Sinica等顶级期刊的评审。已在统计学国际顶级AoS, JASA, Biometrika, Statistica Sinica, TEST和Computational Statistics and Data Analysis,计量经济学国际顶级期刊JoE，JBES，以及国际顶级期刊PNAS等上发表论文数十篇。
经金学院
2025年4月15日
