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2019概率统计及其应用系列报告之八(周望)

  发布日期:2019-05-28  浏览量:267


: 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: 201964()  16:00-17:00

报告地点:磬苑校区澳门赌搏网站大全H306

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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数学科学学院

2019528

专家概况:

周望,新加坡国立大学(National University of Singapore)应用概率统计系教授,2004年获得香港科技大学统计学博士学位。周望教授研究领域包括SLE、高维随机矩阵、多元数据分析等。目前,周望教授担任SCI期刊《随机矩阵:理论与应用》的主编工作。截止目前,周望教授共发表70余篇研究论文,其中在概率统计、经济、信息论领域顶级期Annals of ProbabilityAnnals of Applied ProbabilityAnnals of StatisticsJournal of the Royal Statistical Society, Series B Journal of the American Statistical Association BiometrikaJournal of EconometricIEEE Transactions on Information Theory期刊上共发表二十余篇论文。

 

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