英文论文


文献类型
Journal article (JA)
题名
Model checks for functional linear regression models based on projected empirical processes
作者
Chen, Feifei; Jiang, Qing; Feng, Zhenghui; Zhu, Lixing
作者单位
[Chen, Feifei] Renmin Univ China, Sch Stat, Beijing, Peoples R China. [Jiang, Qing] Southwestern Univ Finance & Econ, Sch Stat, Chengdu, Peoples R China. [Feng, Zhenghui] Xiamen Univ, Sch Econ, Dept Stat, MOE Key Lab Econometr, Xiamen, Peoples R China. [Feng, Zhenghui] Xiamen Univ, Wang Yanan Inst Studies Econ, Xiamen, Peoples R China. [Zhu, Lixing] Hong Kong Baptist Univ, Dept Math, Hong Kong, Peoples R China. [Zhu, Lixing] Beijing Normal Univ, Sch Stat, Beijing, Peoples R China.
通讯作者地址
Xiamen Univ, Sch Econ, Dept Stat, MOE Key Lab Econometr, Xiamen, Peoples R China.; Feng, ZH (reprint author), Xiamen Univ, Wang Yanan Inst Studies Econ, Xiamen, Peoples R China.
Email
zhfengwise@xmu.edu.cn
ResearchID
ORCID
期刊名称
Computational Statistics and Data Analysis
出版社
Elsevier B.V.
ISSN
0167-9473
出版信息
2020-04, 144:-.
JCR
3
影响因子
1.681
ISBN
基金
National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [11871409, 11671042, 11971064]; Humanity and Social Science Youth Foundation of Ministry of Education of China [18YJC910006]; Fundamental Research Funds for the Central Universities, ChinaFundamental Research Funds for the Central Universities [JBK1805004]; Joint Lab of Data Science and Business Intelligence at Southwestern University of Finance and Economics, China; University Grants Council of Hong Kong
会议名称
会议地点
会议开始日期
会议结束日期
关键词
Ergonomics; Monte Carlo methods; Regression analysis; Statistical tests
摘要
The goodness-of-fit testing for functional linear regression models with functional responses is studied. A residual-marked empirical process-based test is proposed. The test is projection-based, which can well circumvent the curse of dimensionality. The test is omnibus against any global alternative hypothesis as it integrates over all projection directions in the unit ball. The weak convergence of the test statistic under the null hypothesis is derived and it is shown that the proposed test can detect the local alternative hypotheses distinct from the null hypothesis at the fastest possible rate of order O(n(-1/2)). To reduce computational burden for critical value determination, a nonparametric Monte Carlo method is used, and simulation studies show the good performance of the proposed method in various scenarios. An ergonomics data set is analyzed for illustration. (C) 2019 Elsevier B.V. All rights reserved.
一级学科
Computer Science, Interdisciplinary Applications; Statistics & Probability
WOS入藏号
WOS:000515446200031
EI收录号
20195107876775
DOI
10.1016/j.csda.2019.106897
ESI
MATHEMATICS
收录于
SCIE, EI

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