Assessing white noise assumption with semi-parametric additive partial linear models
文献类型:期刊论文
作者 | Zhang, Tianyong1; Yuan, Demei1; Ma, Jiali1; Hu, Xuemei1,2 |
刊名 | STATISTICAL PAPERS
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出版日期 | 2017-06-01 |
卷号 | 58期号:2页码:417-431 |
关键词 | White noise Semi-parametric additive partial linear models Empirical likelihood |
ISSN号 | 0932-5026 |
DOI | 10.1007/s00362-015-0705-z |
英文摘要 | In this paper, we present two test statistics for assessing white noise assumption with semi-parametric additive partial linear models. The test statistics are shown to have asymptotic normal or chi-squared distributions under the null hypothesis that the model errors belong to white noise series. By applying R, Monte Carlo experiments are conducted to examine the finite sample performance of the test statistics. Simulation results indicate that the test statistics perform satisfactorily in both estimated sizes and powers. |
资助项目 | National Natural Science Foundation of China[11101452] ; Natural Science Foundation Project of CQ CSTC[2012jjA00035] ; SCR of Chongqing Municipal Education Commission[KJ1400613] ; National Basic Research Program of China (973 Program)[2011CB808000] |
WOS研究方向 | Mathematics |
语种 | 英语 |
WOS记录号 | WOS:000401414200007 |
出版者 | SPRINGER |
源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/25464] ![]() |
专题 | 中国科学院数学与系统科学研究院 |
通讯作者 | Hu, Xuemei |
作者单位 | 1.Chongqing Technol & Business Univ, Sch Math & Stat, Chongqing, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, Tianyong,Yuan, Demei,Ma, Jiali,et al. Assessing white noise assumption with semi-parametric additive partial linear models[J]. STATISTICAL PAPERS,2017,58(2):417-431. |
APA | Zhang, Tianyong,Yuan, Demei,Ma, Jiali,&Hu, Xuemei.(2017).Assessing white noise assumption with semi-parametric additive partial linear models.STATISTICAL PAPERS,58(2),417-431. |
MLA | Zhang, Tianyong,et al."Assessing white noise assumption with semi-parametric additive partial linear models".STATISTICAL PAPERS 58.2(2017):417-431. |
入库方式: OAI收割
来源:数学与系统科学研究院
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