报告题目：Ball technique and algorithms
报 告 人：王学钦教授 中国科学技术大学
报告时间：2020年6月18日 下午 15:00-16:00
报告地点：腾讯会议
点击链接入会，或添加至会议列表：
https://meeting.tencent.com/s/rHNfT4vLzeEv
会议 ID：159 449 722
会议密码：200618
校内联系人：赵世舜 zhaoss@jlu.edu.cn
报告摘要：
The rapid development of modern technology has brought many complex datasets coming from non-linear spaces, while most of the statistical hypothesis tests are only available in Euclidean or Hilbert spaces. To properly analyze the data with more complicated structures, efforts have been made to solve the fundamental test problems in more general spaces (Lyons 2013; Pan, Tian, Wang, and Zhang 2018a; Pan, Wang, Zhang, Zhu, and Zhu 2018c). In this talk, we introduce Ball technique and its R package: Ball for the comparison of multiple distributions and the test of mutual independence in metric spaces, which extends the test procedures for the equality of two distributions (Pan et al. 2018a) and the independence of two random objects (Pan et al. 2018c). The Ball package is computationally efficient since several novel algorithms as well as engineering techniques are employed in speeding up the Ball test procedures. Two real data analyses and diverse numerical studies have been performed, and the results certify that the Ball package can detect various distribution differences and complicated dependences in complex datasets, e.g., directional data and symmetric positive definite matrix data.
报告人简介：
王学钦，中国科学技术大学管理学院教授。2003年毕业于纽约州立大学宾厄姆顿分校, 2012年入选教育部新世纪优秀人才支持计划学者，2013年获得国家优秀青年研究基金，2014年入选第八批广东省高等学校“千百十工程”国家级培养计划，2016年入选“广东特支计划”（百千工程领军人才）。此外，他还担任教育部高等学校统计学类专业教学指导委员会委员、统计学国际期刊《JASA》、《SII》、《JCS》的Associate Editor、高等教育出版社《Lecture Notes: Data Science, Statistics and Probability》系列丛书的副主编、中国现场统计研究会数据科学与人工智能分会副理事长和中国青年统计学家协会副会长等。
