Quantile regression for varying coefficient spatial error models
Dai, Xiaowen; Li, Erqian; Tian, Maozai
2019-09-18
发表期刊COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
卷号50期号:10页码:2382-2397
摘要This paper investigates the quantile regression estimation for spatial error models with possibly varying coefficients. The local polynomial fitting scheme is employed to approximate the varying coefficients. The rank-based score test is developed for hypotheses on the model and the constancy of the varying coefficients. The asymptotic properties of the proposed estimators and test statistics are both established. Monte Carlo simulations are conducted to study the finite sample performance of the proposed method. Analysis of a real data example is presented for illustration.
关键词Spatial error models varying coefficient quantile regression local polynomial approximation
DOI10.1080/03610926.2019.1667396
收录类别SCI ; EI ; SSCI ; SCOPUS ; SCIE
ISSN0361-0926
语种英语
WOS研究方向Mathematics
WOS类目Statistics & Probability
WOS记录号WOS:000486988600001
出版者TAYLOR & FRANCIS INC
EI入藏号20194407596596
EI主题词Polynomial approximation
原始文献类型Journal article (JA)
EISSN1532-415X
引用统计
被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.lzufe.edu.cn/handle/39EH0E1M/571
专题统计与数据科学学院
作者单位1.Shanghai Lixin Univ Accounting & Finance, Sch Stat & Math, Shanghai, Peoples R China;
2.North China Univ Technol, Coll Sci, Beijing, Peoples R China;
3.Renmin Univ China, Ctr Appl Stat, Sch Stat, Beijing 100872, Peoples R China;
4.Xinjiang Univ Finance & Econ, Sch Stat & Informat, Urumqi, Peoples R China;
5.Lanzhou Univ Finance & Econ, Sch Stat, Lanzhou, Gansu, Peoples R China
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GB/T 7714
Dai, Xiaowen,Li, Erqian,Tian, Maozai. Quantile regression for varying coefficient spatial error models[J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS,2019,50(10):2382-2397.
APA Dai, Xiaowen,Li, Erqian,&Tian, Maozai.(2019).Quantile regression for varying coefficient spatial error models.COMMUNICATIONS IN STATISTICS-THEORY AND METHODS,50(10),2382-2397.
MLA Dai, Xiaowen,et al."Quantile regression for varying coefficient spatial error models".COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 50.10(2019):2382-2397.
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