A Nonparametric Model Checking Test for Functional Linear Composite Quantile Regression Models  

作　　者：XIA Lili DU Jiang ZHANG Zhongzhan 

机构地区：[1]Faculty of Science,Beijing University of Technology,Beijing 100124,China

出　　处：《Journal of Systems Science & Complexity》2024年第4期1714-1737,共24页系统科学与复杂性学报（英文版）

基　　金：supported by the Natural Science Foundation of China under Grant Nos.11271014 and 11971045。

摘　　要：This paper is focused on the goodness-of-fit test of the functional linear composite quantile regression model.A nonparametric test is proposed by using the orthogonality of the residual and its conditional expectation under the null model.The proposed test statistic has an asymptotic standard normal distribution under the null hypothesis,and tends to infinity in probability under the alternative hypothesis,which implies the consistency of the test.Furthermore,it is proved that the test statistic converges to a normal distribution with nonzero mean under a local alternative hypothesis.Extensive simulations are reported,and the results show that the proposed test has proper sizes and is sensitive to the considered model discrepancies.The proposed methods are also applied to two real datasets.

关 键 词：Composite quantile regression consistent test functional data nonparametric test quadratic form 

分 类 号：O212.1[理学—概率论与数理统计]