报告题目：General Jackknife Empirical Likelihood and its Applications

报 告 人：刘一鸣 助理教授

所在单位：暨南大学

报告时间：2023年9月20日 11：00-12：00

报告地点：数学楼第二报告厅

联系人：dingxue83@jlu.edu.cn

报告摘要: 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.

报告人简介: 刘一鸣，新加坡南洋理工大学博士后。2020年7月博士毕业于新加坡南洋理工大学数理学院，导师潘光明教授。本科毕业于哈尔滨工业大学，硕士毕业于澳门大学。目前主要研究方向：机器学习、高维统计推断的理论研究和应用、随机矩阵等。在博士期间已在 Statistica Sinica, Computational statistics & data analysis, Science China Mathematics 等SCI期刊发表论文6篇，且担任 Random Matrices：Theory and Application 杂志审稿人。