统计与数据科学系系列学术报告之四百四十五期
时 间：2024年7月10日（周三）14:00-15:00
地 点：史带楼301室
主持人：复旦大学 管理学院 统计与数据科学系 郁文 教授
报告人：Fangyi Chen PhD Candidate Department of Statistics, Columbia University
题 目：Dynamic Factor Analysis of High-dimensional Recurrent Events
摘 要：Recurrent event time data arise in many studies, including biomedicine, public health, marketing, and social media analysis. High-dimensional recurrent event data involving large numbers of event types and observations become prevalent with the advances in information technology. We proposes a semiparametric dynamic factor model for the dimension reduction and prediction of high-dimensional recurrent event data. The proposed model imposes a low-dimensional structure on the mean intensity functions of the event types while allowing for dependencies. A nearly rate-optimal smoothing-based estimator is proposed. An information criterion that consistently selects the number of factors is also developed. Simulation studies demonstrate the effectiveness of these inference tools. The proposed method is applied to grocery shopping data, for which an interpretable factor structure is obtained.
个人简介：Fangyi Chen is a fourth-year statistics PhD student at Columbia University with research interest in the analysis of survival data, longitudinal data and network data under the supervision of Professor Zhiliang Ying.
统计与数据科学系
2024-7-8
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