学术报告通知

报告题目：A groupwise dimension reduction model-adaptive test for conditional independence

报告人：陆军 博士（ 浙江工商大学  统计与数学学院）

报告时间：2019年9月27日  9:00—10:00

报告地点：37000cm威尼斯 B410

报告摘要： In this paper, we propose a groupwise dimension reduction adaptive-to-model test for conditional independence. The novel test is asymptotically normal distributed under the null hypothesis. Unlike other locally smoothing nonparametric tests for conditional independence, it behaves like a locally smoothing test as if the number of covariates was just the dimension of central subspace under the null hypothesis, which is less than that under the null hypothesis, and it can detect local alternative hypotheses distinct from the null hypothesis at the rate that is only related to the dimension of central subspace under the null hypothesis. Therefore, the curse of dimensionality is largely alleviated. To achieve the above goal, we also proposed groupwise least square estimation for the groupwise central subspace.

报告人简介：

陆军，2018年于37000cm威尼斯取得博士学位，2017年至2018年于美国西北大学访学一年，现为浙江工商大学统计与数学学院青年教师。陆军博士一直从事统计理论、方法与应用研究，研究兴趣涉及高维数据分析、变量选择、假设检验等领域。在Computational Statistics and Data Analysis, Statistical Papers等统计学国际重要学术期刊发表论文多篇。