報 告 人：杜江 副教授

主 持 人：張曉穎

時    間：2019年9月6日 16：00-17：00

地    點：第三教學樓五樓大數據實驗室

主辦單位：理學院

報告人簡介：杜江，副教授，統計學博士，碩士生導師。2016年入選北京工業大學日新人才計劃；2019年入選北京市教委青年拔尖人才計劃。現為美國數學評論評論員、北京應用統計協會理事、中國青年統計學家協會理事、中國工業與應用數學學會會員、河北省研究生數學建模評審專家。主持國家自然科學基金面上項目和青年項目各1項、中國博士后基金（面上）1項、北京市教委科技計劃項目1項；參加國家重點研發計劃1項、國家自然科學基金5項、國家社科科學基金1項、省部級項目3項和多項橫向項目。已在國內外著名學術刊物上發表論文30余篇，其中20余篇被SCI檢索。

觀點綜述：In this talk, we present a novel model checking method for functional linear quantile regression model (FLQRM). FLQRMis widely used to characterize the relationship between a scalar response and a functional covariate. Most existing research results are based on a correct assumption that the response is related to the functional predictor through a linear model for given quantile level. Thistalkfocuses on investigating the adequacy check of the functional linear quantile regression model. We propose a nonparametric kernel-based test statistic by using the functional principal component analysis. It is proved that the test statistic follows a normal distribution asymptotically under the null hypothesis and diverges to infinity for any misspecified models. Therefore, the test is consistent against any fixed alternative. Moreover, it is shown that the test has asymptotic power one for the local alternative hypothetical models converging to the null hypothesis. The finite sample properties of the test statistic are illustrated through extensive simulation studies. A real data set of 24 hourly measurements of ozone levels in Sacramento, California is analyzed by the proposed test.