【报告题目】The Statistics Triangle

【报告简介】

       In his Fisher’s Lecture in 1996, Efron suggested that there is a philosophical triangle in statistics with “Bayesian”, “Fisherian”, and “Frequentist” being the three vertices, and most of the statistical methods can be viewed as aconvex linear combination of the three philosophies. We collected and cleaned adata set consisting of the citation and bibtex (e.g., title, abstract, authorinformation) data of 83,331 papers published in 36 journals in statistics andrelated fields, spanning 41 years. Using the data set, we constructed 21co-citation networks, each for a time window between 1990 and 2015. We proposea dynamic Degree-Corrected Mixed- Membership (dynamic-DCMM) model, where wemodel the research interests of an author by a low-dimensional weight vector(called the network memberships) that evolves slowly over time. We propose dynamic-SCORE as a new approach to estimating the memberships. We discover a triangle in the spectral domain which we call the Statistical Triangle, and use it to visualize the research trajectories of individual authors. We interpret the three vertices of the triangle as the three primary research areas instatistics: “Bayes”, “Biostatistics” and “Nonparametrics”. The Statistical Triangle further splits into 15 sub-regions, which we interpret as the 15 representative sub-areas in statistics. These results provide useful insightsover the research trend and behavior of statisticians.

【报告人简介】

       金加顺，卡耐基梅隆大学统计与数据科学系教授，早期的主要研究领域是大规模稀疏数据的数据分析推断，近期的研究兴趣主要集中在社会网络，曾获美国数理统计学会现任会士（IMS Fellow)、特威迪奖（IMS Tweedie Award）、 勋章讲座（IMS Medallion Lecture)、 应用统计年鉴特邀讲座（IMS AOASLecture）、 美国统计学会会士（ASA Fellow)、 顶级统计期刊主编特邀评述专辑论文（Editor’s Invited Review Paper）和主编特邀评论论文（Editor’sDiscussion paper）等多项荣誉，并有着非常丰富的业界经历，包括近年华尔街全球最成功的量化对冲基金巨头（Two-Sigma Investment）数据科学团队全职工作两年的研发经验等。

【报告时间】

       2024年3月7日（周四）上午10：00-11：30

【报告地点】

       九龙湖校区润良报告厅