报告简介  Abstract

Threshold models have a wide variety of applications in statistics and economics. We generalize the threshold quantile regression in literature to single-index thresholding quantile regression which depends on a linear combination of regressors as threshold variable. We propose smoothed estimator and study its asymptotic properties for a single quantile as well as for the quantile process. To perform inference for index parameters, we propose a Wald-type method and a Mixed-bootstrap method which is more stable. We also extend the Mixed-bootstrap to test constancy of index parameters across different quantile indexes. The finite sample performance of the proposed method is assessed through simulation and the analysis of a real data.

嘉宾简介  About the Speaker

朱仲义，复旦大学统计系教授，博士研究生导师；曾任中国概率统计学会第八、九届副理事长,国际著名杂志“Statistica Sinica”副主编；“应用概率统计”、“数理统计与管理”杂志编委，中国统计教材编审委员会委员；现为Elected Member of the ISI（国际数理统计学会）；“中国科学：数学”杂志编委。专业研究方向为：保险精算；纵向数据(面板数据)模型；分位数回归模型等。主持完成国家自然科学基金四项、国家社会科学基金一项，作为子项目负责人完成国家自然科学基金重点项目一项。目前主持国家自然科学基金重大项目子项目一项，重点项目子项目一项，面上项目一项。近几年发表论文100多篇(其中包括在国际四大统计顶级刊物等SCI论文六十多篇)。获得教育部自然科学二等奖一次。

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