A Class of Robust Independence Tests Based on Weighted Integrals of Empirical Characteristic Functions

作     者：Feng ZOU Chang Liang ZOU Heng Jian CUI 

作者机构：School of Statistics and MathematicsZhongnan University of Economics and LawWuhan430073P.R.China NITFIDSchool of Statistics and Data ScienceLPMC and KLMDASR and LEBPSNankai UniversityTianjin300071P.R.China School of Mathematical SciencesCapital Normal UniversityBeijing100048P.R.China 

出 版 物：《Acta Mathematica Sinica,English Series》 (数学学报（英文版）)

年 卷 期：2024年第40卷第12期

页      面：2921-2952页

核心收录：

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

基　　金：supported by National Natural Science Foundation of China(NNSFC)(Grant No.12201317) China Postdoctoral Science Foundation(Grant No.2022M721716),Changliang Zou’s research was supported by the National Key R&D Program of China(Grant Nos.2022YFA1003703,2022YFA1003800) the National Natural Science Foundation of China(Grant Nos.11925106,12231011,11931001,12226007,12326325) Cui’s research was supported by NNSFC(Grant Nos.12031016 and 11971324) 

主　　题：Asymptotic properties data-driven robust independence tests special distributions weighted integrals 

摘      要：In this paper,we propose a class of robust independence tests for two random vectors based on weighted integrals of empirical characteristic *** letting weight functions be probability density functions of a class of special distributions,the proposed test statistics have simple closed forms and do not require moment conditions on the random ***,we derive the asymptotic distributions of the test statistics under the null *** proposed testing method is computationally feasible and easy to *** on a data-driven bandwidth selection method,Monte Carlo simulation studies indicate that our tests have a relatively good performance compared with the competitors.A real data example is also presented to illustrate the application of our tests.