(6月21日）王学钦教授报告： Ball divergence

报告题目： Ball divergence

主讲嘉宾：王学钦教授

中山大学数学科学学院

时间地点：2017年6月21日(星期三)下午4:00-5:00

             浙江大学玉泉校区工商管理楼二楼报告厅

摘要：In this talk, we first introduce Ball Divergence, a novel measure of the difference between two probability measures in separable Banach spaces, and show that the Ball Divergence of two probability measures is zero if and only if these two probability measures are identical without any moment assumption. Using Ball Divergence, we present a metric rank test procedure to detect the equality of distribution measures underlying independent samples. It is therefore robust to outliers or heavy-tail data. We show that this multivariate two sample test statistic is consistent with the Ball Divergence, and it converges to a mixture of Chi-square distributions under the null hypothesis and a normal distribution under the alternative hypothesis. Importantly, we prove its consistency against a general alternative hypothesis. Moreover, this result does not depend on the ratio of the two imbalanced sample sizes, ensuring that can be applied to imbalanced data. Numerical studies confirm that our test is superior to several existing tests in terms of Type I error and power. We conclude our paper with two applications of our method: one is for virtual screening in drug development process and the other is for genome wide expression analysis in hormone replacement therapy.

王学钦教授简介：中山大学数学学院和中山医学院双聘教授，博士生导师，中山大学统计学科带头人，中山大学华南统计科学研究中心执行主任，教育部统计专业教指委委员。王学钦教授2003年获得美国纽约州立大学宾厄姆敦分校博士学位，2007年入职中山大学任教授，2012年入选中山大学首届优秀青年教师培养计划、教育部新世纪优秀人才支持计划，2013年获得国家自然科学基金优秀青年基金，2014年被评为第八批广东省高等学校“千百十工程”国家级培养对象，2016年入选“广东特支计划”百千万工程领军人才。其研究领域包括非参多元统计学、数理统计学、统计遗传学、计算生物学、生物信息学、数据挖掘、全基因组关联分析、统计学习、精准医学等。

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联系人: 张立新 stazlx@zju.edu.cn