报告题目：High order conditional distance covariance with conditional mutual independence
报 告 人：周望（新加坡国立大学教授）
报告时间：2019年6月4日(周二) 16:00-17:00
报告地点：磬苑校区数学科学学院H306
报告摘要：We construct a high order conditional distance covariance, which generalizes the notation of conditional distance covariance. The joint conditional distance covariance is defined as a linear combination of conditional distance covariances, which can capture the joint relation of many random vectors given one vector. Furthermore, we develop a new method of conditional independent test based on the joint conditional distance covariance. Simulation results indicate that the proposed method is very effective. We also apply our method to analyze the relationships of $PM_{2.5}$ in five Chinese cities: Beijing, Tianjin, Jinan, Tangshan and Qinhuangdao by Gaussian graphical model.
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科学技术处
2019年5月29日