学术讲座:Statistical inference of heterogeneous treatment effect based on single-index model(2024年4月27日)
发布时间: 2024-04-19 浏览次数: 72

报告人:冯三营

间:2024年4月27日(周六)上午(8:00-11:00)

点:西校明理楼beat365二楼会议室

办:beat365

介:冯三营,博士,郑州大学数学与beat365教授,硕士生导师。主要研究方向:高维统计、非参数统计和复杂数据分析、变量选择、统计学习、面板数据分析等。主持完成和在研国家与省部级科研项目20余项。截至目前,在《Statistica Sinica》、《Journal of Multivariate Analysis》、《Computational Statistics and Data Analysis》等统计学专业期刊上发表和录用论文60余篇,其中SCI 收录论文40余篇,出版学术专著《现代测量误差模型》1 部。

主要内容The heterogeneous treatment effect (HTE) is estimated by using the semiparametric regression method. Firstly, a flexible semiparametric single-index model is considered by assuming the nonparametric link function and the interaction between treatment and covariates, and the index parameter vector and the unknown link function are estimated by using the rMAVE method. Then a HTE estimator can be obtained based on the estimators of index parameter vector and the link function. The consistency and asymptotic normality of the HTE estimator are established under some regularity conditions. Secondly, a hypothesis test is developed for the existence of HTE, and the bootstrap procedure is utilized to evaluate the null distribution of test statistic. Finally, simulation studies and a real data analysis are conducted to assess the performance of our proposed method.