【報告題目】The Statistics Triangle

【報告簡介】

       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.

【報告人簡介】

       金加順，卡耐基梅隆大學統計與數據科學系教授，早期的主要研究領域是大規模稀疏數據的數據分析推斷，近期的研究興趣主要集中在社會網絡，曾獲美國數理統計學會現任會士（IMS Fellow)、特威迪獎（IMS Tweedie Award）、 勳章講座（IMS Medallion Lecture)、 應用統計年鑒特邀講座（IMS AOASLecture）、 美國統計學會會士（ASA Fellow)、 頂級統計期刊主編特邀評述專輯論文（Editor’s Invited Review Paper）和主編特邀評論論文（Editor’sDiscussion paper）等多項榮譽，并有着非常豐富的業界經曆，包括近年華爾街全球最成功的量化對沖基金巨頭（Two-Sigma Investment）數據科學團隊全職工作兩年的研發經驗等。

【報告時間】

       2024年3月7日（周四）上午10：00-11：30

【報告地點】

       九龍湖校區潤良報告廳