报告题目：Goodness-of-fit test for partially linear quantile

regression models using projections

报告时间：北京时间2020年10月17日9:00-11:00

报告地点：腾讯会议 会议 ID：628 119 603

摘要：In this talk, we consider a specification test for partially linear quantile regression models with high-dimensional covariates, which combines basis function approximations and unidimensional linear projections of the covariates. Under mild conditions, we establish the consistency of the proposed test method, and show that the proposed test can detect Pitman local alternatives converging to the null at the usual parametric rate. To improve the finite sample properties of the proposed test, we develop a wild bootstrap method to obtain the critical values or p-values, and show the validity of the proposed bootstrap method. We conduct Monte Carlo studies to investigate the finite sample performance

of our new procedure, and find that the proposed test method produces

satisfactory results. Finally, the proposed test method is illustrated by two real data examples.

报告人简介：北京工业大学副教授，博士生导师。2016年入选北京工业大学日新人才计划；2019年入选北京市教委青年拔尖人才计划。现为美国数学评论评论员、北京应用统计协会理事、中国青年统计学家协会理事。目前主持国家自然科学基金面上项目1项，中国博士后基金（面上）1项，北京市教委科技计划项目1项，参加国家重点研发计划1项、国家自然科学基金2项、国家社科科学基金1项。已在国内外学术刊物上发表论文30余篇，其中20余篇被SCI检索。研究方向为函数型数据分析、空间数据分析、分位数回归、贝叶斯分析。