报告题目：IDENTIFICATION OF INFLUENCING FACTORS ON SELF-REPORTED COUNT DATA WITH MULTIPLE POTENTIAL INFLATED VALUES

主讲人：李扬教授（中国人民大学）

时间：2024年7月13日（周六）16:00 p.m.

地点：北院卓远楼305会议室

主办单位：统计与数学学院

摘要：The Online Chauffeured Service Demand (OCSD) research is an exploratory market study of designated driver services in China. Researchers are interested in the influencing factors of chauffeured service adoption and usage and have collected relevant data using a self-reported questionnaire. As self-reported data of count measure is typically inflated, there exist challenges to its validity, which may bias estimation and increase error in empirical research. Motivated by the analysis of self-reported data with multiple inflated values, we propose a novel approach to simultaneously achieve data-driven inflated value selection and identification of important influencing factors. In particular, the regularization technique is applied to the mixing proportions of inflated values and the regression parameters to obtain shrinkage estimates. We analyze the OCSD data with the proposed approach, deriving insights into the determinants impacting service demand. The proper interpretations and implications contribute to service promotion and related policy optimization. Extensive simulation studies and consistent asymptotic properties further establish the effectiveness of the proposed approach.

主讲人简介：

李扬，中国人民大学吴玉章特聘教授、博士生导师，学校交叉科学学术委员会副主任、学校学位评定委员会委员，入选国家级青年人才项目；担任国际统计学会Elected Member、中国商业统计学会副会长、中国统计学会常务理事、中国现场统计研究会常务理事、北京生物医学统计与数据管理研究会监事长等；主要从事模型选择与不确定性评价、复杂调查设计与分析、潜变量建模、试验设计与推断等领域研究，在国内外知名期刊发表论文八十余篇，承担国家自然科学基金、教育部重大项目、全国统计科学研究重大项目等。