报告题目: Semiparametric inference for two-sample semi-continuous populations

报告人：University of Waterloo     Pengfei Li

报告时间：2026年6月22日9:00-10:00

报告地点：赌博网站 106会议室

Abstract: Semi-continuous data, characterized by a mixture of excessive zero values and positively skewed continuous outcomes, arise frequently in applications such as medical expenditures, hospitalization costs, insurance claims, rainfall measurements, and income studies. Conventional parametric approaches may suffer from model misspecification, while fully nonparametric procedures often fail to efficiently utilize the common structure shared by related populations.

In this talk, I will present a unified semiparametric framework for statistical inference on two semi-continuous populations. The framework models the positive components of the two populations through a density ratio model, allowing flexible information pooling without imposing restrictive parametric assumptions on the underlying distributions. Using empirical likelihood techniques, we develop efficient estimators and inference procedures for a broad class of population characteristics. The talk will cover several recent developments, including semiparametric inference for distributional functionals, mean-related quantities, and inequality measures such as the Gini index. We establish asymptotic properties of the proposed estimators, construct confidence intervals and hypothesis tests, and show that the proposed methods achieve efficiency gains over existing fully nonparametric procedures. Simulation studies  demonstrate the advantages of the proposed methods in finite samples.

报告人简介: Dr. Pengfei Li received his Ph.D. in Statistics from the University of Waterloo in December 2007 and completed postdoctoral training at the University of British Columbia in 2008. He has been a Professor at the University of Waterloo since 2019. His research interests include finite mixture models, empirical likelihood, missing data analysis, ROC curve analysis, and non-probability survey sampling. Dr. Li has published approximately 85 papers in refereed journals and book chapters, including sixteen articles in leading statistical journals such as The Annals of Statistics, Biometrika, Journal of the American Statistical Association, and Journal of the Royal Statistical Society: Series B. He was elected a Fellow of the Institute of Mathematical Statistics (IMS) and received the CRM-SSC Prize in Statistics in 2022.