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Semiparametric time series regression modeling with a diverging number of parameters
Zheng, Shengchao1,2; Li, Degao2,3
刊名STATISTICA NEERLANDICA
2018-05
卷号72期号:2页码:90-108
关键词high-dimensional data autoregressive error consistency asymptotic normality
ISSN号0039-0402
DOI10.1111/stan.12121
英文摘要Variable selection and error structure determination of a partially linear model with time series errors are important issues. In this paper, we investigate the regression coefficient and autoregressive order shrinkage and selection via the smoothly clipped absolute deviation penalty for a partially linear model with a divergent number of covariates and finite order autoregressive time series errors. Both consistency and asymptotic normality of the proposed penalized estimators are derived. The oracle property of the resultant estimators is proved. Simulation studies are carried out to assess the finite-sample performance of the proposed procedure. A real data analysis is made to illustrate the usefulness of the proposed procedure as well.
WOS研究方向Mathematics
语种英语
出版者WILEY
WOS记录号WOS:000430306300002
内容类型期刊论文
源URL[http://10.2.47.112/handle/2XS4QKH4/635]  
专题上海财经大学
通讯作者Li, Degao
作者单位1.Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai, Peoples R China;
2.Jiaxing Univ, Coll Math Phys & Informat Engn, Jiaxing, Zhejiang, Peoples R China;
3.Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R China
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GB/T 7714
Zheng, Shengchao,Li, Degao. Semiparametric time series regression modeling with a diverging number of parameters[J]. STATISTICA NEERLANDICA,2018,72(2):90-108.
APA Zheng, Shengchao,&Li, Degao.(2018).Semiparametric time series regression modeling with a diverging number of parameters.STATISTICA NEERLANDICA,72(2),90-108.
MLA Zheng, Shengchao,et al."Semiparametric time series regression modeling with a diverging number of parameters".STATISTICA NEERLANDICA 72.2(2018):90-108.
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