報告題目：General Jackknife Empirical Likelihood and its Applications
報 告 人：劉一鳴 助理教授
所在單位：暨南大學
報告時間：2023年9月20日 11：00-12：00
報告地點：數學樓第二報告廳
聯系人：dingxue83@jlu.edu.cn
報告摘要: This paper is to give a novel Jackknife empirical likelihood for both smooth and unsmooth statistical functionals. Specifically, we consider the estimation of unknown statistical functionals under the framework of general delete-d jackknife and an usage of subsampling method which can reduce the computational burden. Moreover, the corresponding statistical inference issues and asymptotic properties of the proposed method are also investigated. Several related application examples are carefully conducted to check the superiority of our new proposed method. Finally, the finite sample simulation studies are also included.
報告人簡介: 劉一鳴，新加坡南洋理工大學博士後。2020年7月博士畢業于新加坡南洋理工大學數理學院，導師潘光明教授。本科畢業于哈爾濱工業大學，碩士畢業于澳門大學。目前主要研究方向：機器學習、高維統計推斷的理論研究和應用、随機矩陣等。在博士期間已在 Statistica Sinica, Computational statistics & data analysis, Science China Mathematics 等SCI期刊發表論文6篇，且擔任 Random Matrices：Theory and Application 雜志審稿人。
