报告题目：High order conditional distance covariance with conditional mutual independence
报告时间：2018年12月26日（星期三）15:30-16:10
报告地点：尚贤楼706
主持人：来鹏副教授
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报告内容简介：
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 PM2.5 in five Chinese cities: Beijing, Tianjin, Jinan, Tangshan and Qinhuangdao by Gaussian graphical model.
专家介绍：
周望主要从事统计学的理论与应用研究，特别在高维数据估计、高维数据检验、数据降维、大维数据随机矩阵的研究都处于世界的前沿。发表了40多篇研究性文章，其中许多篇发表在统计学领域和计量经济学领域的顶级杂志，如: Annals of Statistics, Journal of American Statistical Association, Journal of Royal Statistical Society（B）, Biometrika, Bernoulli, Journal of Econometrics，Trans. Amer. Math. Soc.上。一些文章被多位学者引用。周望教授主持过多个新加坡国家自然科学基金项目，并应邀在多个国际会议上作大会报告和邀请报告。
数学与统计学院
2018年12月24日
