報告題目：Robust Subgroup Analysis for Network-Linked Data
報 告 人：朱文聖 教授
所在單位：東北師範大學
報告時間：2022年8月3日 星期三 9:00-10:00
報告地點：騰訊會議 ID：737-840-105
校内聯系人：趙世舜 zhaoss@jlu.edu.cn
報告摘要：Modern applications often collect data with individuals connected by a network to effectively record relationship information between individuals. In this paper, we use both covariates and the network to identify subgroup structures from a heterogeneous population, where heterogeneity arises from unknown or unobserved latent factors. We propose a penalization based method for subgroup analysis based on the median regression model, which can automatically divide the samples into subgroups by penalizing pairwise difference of intercepts for individuals connected by an edge in the network. The proposed method can also be used to predict response variables for new subjects with only covariates by taking advantage of the network reconstructed after adding these new subjects. We suggest an implementation algorithm based on the local linear approximation to the nondifferentiable and nonconvex penalty function and establish the oracle properties of the proposed estimator under some regularity conditions. Our simulation studies show that the proposed method can effectively identify heterogeneous subgroups even when the network has errors or mis-specified edges. Finally, the advantages of the proposed method are further illustrated by the analysis on a housing price data set from real estate transactions.
報告人簡介： 朱文聖，東北師範大學數學與統計學院教授、博士生導師、副院長。2006年博士畢業于東北師範大學，2008-2010年在耶魯大學做博士後研究，2015-2017年訪問北卡羅來納大學教堂山分校。中國現場統計研究會計算統計分會副理事長、旅遊大數據分會副理事長、數據科學與人工智能分會秘書長，中國概率統計學會副秘書長，吉林省現場統計研究會秘書長。研究方向為生物統計與精準醫療，在Journal of the American Statistical Association、Statistica Sinica、Test、Journal of Scientific Computing、中國科學等雜志發表學術論文多篇，主持并完成國家自然科學基金項目多項。
