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Model checks for functional linear regression models based on projected empirical processes

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Model checks for functional linear regression models based on projected empirical processes
文献类型:期刊
通讯作者:Feng, ZH (reprint author), 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.
期刊名称:COMPUTATIONAL STATISTICS & DATA ANALYSIS影响因子和分区
年:2020
卷:144
ISSN:0167-9473
关键词:Functional linear models; Model checking; Residual-marked; Projected empirical processes
所属部门:统计学院
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 ca ...More
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. ...Hide

DOI:10.1016/j.csda.2019.106897
百度学术:Model checks for functional linear regression models based on projected empirical processes
语言:外文
人气指数:2
浏览次数:2
基金:National Natural Science Foundation of ChinaNational Natural Science Foundation of China [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
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Multiple permutation test for high-dimensional data: a components-combined algorithm.Yu, Wei, Xu, Wangli, Zhu, Lixing,.JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION. 2019, 89(4), 686-707.
On some characterizations and multidimensional criteria for testing homogeneity, symmetry and independencel.Chen, Feifei, Meintanis, Simos G., Zhu, Lixing,.JOURNAL OF MULTIVARIATE ANALYSIS. 2019, 173, 125-144.
Model checking for parametric regressions with response missing at random.Guo, Xu;Xu, Wangli;Zhu, Lixing.ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS.2015,67(2),229-259.
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