A PROJECTIVE APPROACH TO CONDITIONAL INDEPENDENCE TEST FOR DEPENDENT PROCESSES
报告人: 朱利平,中国人民大学
时间:2019-05-16 14:00-15:00
地点:光华2号楼217
Abstract:
Conditional independence is a fundamental concept in many scientific fields. In this paper, we propose a projective approach to measuring and testing departure from conditional independence for dependent processes. Through projecting high dimensional dependent processes onto low dimensional subspaces, our proposed projective approach is insensitive to the dimensions of the processes. We show that, under the common $\beta$-mixing conditions, our proposed projective test is $n$-consistent if these processes are conditionally independent and root-$n$-consistent otherwise. We suggest a bootstrap procedure to approximate the asymptotic null distribution of the test statistic. The consistency of this bootstrap procedure is also rigorously established. The finite-sample performance of our proposed projective test is demonstrated through simulations against various alternatives and an economic application to test Granger causality.
About the Speaker:
朱利平,中国人民大学统计与大数据研究院“杰出学者”特聘教授、博士生导师。
朱利平长期从事统计学理论和方法研究,他在高维及超高维数据统计分析、半参数回归模型统计推断等领域做出了一些比较重要的研究工作,在统计学领域主要的四个杂志上发表论文18篇,得到了诸多著名统计学家的关注与高度评价。
朱利平是国家自然科学基金优秀青年基金获得者,也入选中组部万人计划青年拔尖人才计划以及教育部新世纪优秀人才计划等。