报告时间：2021年11月2日 19：00-20：00

腾讯会议：458 712 548

报告人：晏振（广西师范大学）

报告摘要：

Single series Gini coefficient is the extension of Gini coefficient, including all the advantages of Gini coefficient. Considering the complexity of jackknife's empirical likelihood method and the possibility that the solution does not exist, this paper discusses the confidence interval estimation problem of single series Gini coefficients by adjusting jackknife's empirical likelihood method. Firstly, this paper estimates the confidence interval of single series Gini coefficients by adjusting empirical likelihood and jackknife empirical likelihood respectively, and gives the statistical properties of the estimators in theory. Secondly, the performance of the method is compared by Monte Carlo simulation. Finally, the empirical analysis is carried out by adjusting jackknife's empirical likelihood method. The results show that the confidence intervals constructed by adjusting the empirical likelihood method of jackknife have similar properties in theory. The simulation results show that the confidence intervals constructed by adjusting the empirical likelihood method of jackknife have higher coverage.

报告人介绍：

晏振，副教授，硕士研究生导师，中国人民大学博士毕业，现担任广西师范大学数学与统计学院院长助理，兼任中国商业统计学会理事、全国工业统计学教学研究会青年统计学家协会理事。研究领域主要包括经验似然、分位回归、函数型数据分析等。主持国家自然科学青年基金项目1项、广西自然科学基金项目1项，参与国家级科研课题4项。在《Communications in Statistics - Theory and Methods》、《数理统计与管理》等期刊发表学术论文10多篇。曾获北京市第十二届统计科研优秀成果评比优秀课题论文一等奖、广西高等教育自治区级教学成果奖二等奖。

邀请人：马学俊