题 目：A Powerful Test for Independence Using Refitted Cross-Validation

主讲人：周亭攸博士

时 间：2021年6月24日（周四）下午13:30-14:30

地 点：6号学院楼402会议室

主办单位：银河7163官网 浙江省2011“数据科学与大数据分析协同创新中心”

摘要：

Measuring the association between random variables is of fundamental importance in data science and statistical inference. In this work, we propose a distribution free independence test based on projected distance covariance using refitted cross-validation. The proposed test is consistent against all fixed alternatives, insensitive to the dimension and free of tuning parameters. More importantly, under the null hypothesis, the test can control type-I error rate at the nominal level pretty well and the asymptotic null distribution has an explicit form that does not involve any unknown parameters, which facilitates to compute the empirical p-value efficiently in practice. Under the alternative hypothesis, the test statistic enjoys the oracle property. Extensive Monte Carlo simulations reveal that our test is superior to the competitors and as powerful as if both random variables are univariate.

主讲人简介：

周亭攸，理学博士，银河7163官网讲师，硕士生导师。现担任青年统计学家协会理事学术兼职。主要研究领域为高维数据分析的统计理论、方法及应用研究工作，涉及半参数模型，充分降维，变量选择等。主持了国家自科基金青年项目一项，在《Journal of the American Statistical Association》、《Statistica Sinica》等期刊发表学术论文。

欢迎各位老师和同学积极参加！