報告題目：Ball technique and algorithms
報 告 人：王學欽教授 中國科學技術大學
報告時間：2020年6月18日 下午 15:00-16:00
報告地點：騰訊會議
點擊鍊接入會，或添加至會議列表：
https://meeting.tencent.com/s/rHNfT4vLzeEv
會議 ID：159 449 722
會議密碼：200618
校内聯系人：趙世舜 zhaoss@jlu.edu.cn
報告摘要：
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.
報告人簡介：
王學欽，中國科學技術大學管理學院教授。2003年畢業于紐約州立大學賓厄姆頓分校, 2012年入選教育部新世紀優秀人才支持計劃學者，2013年獲得國家優秀青年研究基金，2014年入選第八批廣東省高等學校“千百十工程”國家級培養計劃，2016年入選“廣東特支計劃”（百千工程領軍人才）。此外，他還擔任教育部高等學校統計學類專業教學指導委員會委員、統計學國際期刊《JASA》、《SII》、《JCS》的Associate Editor、高等教育出版社《Lecture Notes: Data Science, Statistics and Probability》系列叢書的副主編、中國現場統計研究會數據科學與人工智能分會副理事長和中國青年統計學家協會副會長等。
