【专家简介】：冯龙，现任南开大学beat365中文在线官网教授、博士生导师。入选教育部青年人才计划、南开大学百名青年学科带头人。主要从事高维数据分析方面的研究，在统计学国际顶尖杂志JRSSB, JASA、Biometrika、Annals of Statistics、JOE、JBES等发表50余篇论文。主持一项天津市杰出青年基金、国家自然科学基金面上项目和青年项目。担任Statistical Theory and Related Field副主编。
【报告摘要】：We propose a unified ridge-regularized Hotelling framework for detecting and locating mean changes in functional time series. A growing basis expansion converts the functional observations into high-dimensional score vectors. Their long-run covariance is estimated by an edge-corrected difference-based procedure. Ridge regularization stabilizes inference under spectral decay. An explicit local-power formula shows that the power-maximizing ridge depends on the unknown spectral orientation of the change. We therefore combine a family of ridge CUSUM statistics by a Cauchy transform and calibrate the aggregate directly from their joint weighted-bridge limit. For multiple changes, we embed local maximum-ridge statistics in a wild binary segmentation procedure, followed by local refinement. Under mild conditions, we establish the validity, local power, consistency, and localization properties of the proposed tests. In the multiple-change setting, the procedure consistently recovers the number of changes and uniformly estimates their locations. The framework accommodates weak dependence and non-Gaussian functional errors. Simulations and two empirical applications demonstrate the favorable finite-sample performance of the proposed methods.
【报告时间】：2026年10月31日（周六）15:30-16:30
【报告地点】：位育楼417
