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Local linear additive quantile regression
Yu, KM; Lu, ZD
2004-09-01
Source PublicationSCANDINAVIAN JOURNAL OF STATISTICS
ISSN0303-6898
Volume31Issue:3Pages:333-346
AbstractWe consider non-parametric additive quantile regression estimation by kernel-weighted local linear fitting. The estimator is based on localizing the characterization of quantile regression as the minimizer of the appropriate 'check function'. A backfitting algorithm and a heuristic rule for selecting the smoothing parameter are explored. We also study the estimation of average-derivative quantile regression under the additive model. The techniques are illustrated by a simulated example and a real data set.
Keywordadditive models average derivative backfitting algorithm bandwidth selection local linear fitting quantile regression
Language英语
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:000222961800002
PublisherBLACKWELL PUBL LTD
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/19290
Collection中国科学院数学与系统科学研究院
Corresponding AuthorYu, KM
Affiliation1.Univ Plymouth, Dept Math & Stat, Plymouth PL4 8AA, Devon, England
2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100864, Peoples R China
Recommended Citation
GB/T 7714
Yu, KM,Lu, ZD. Local linear additive quantile regression[J]. SCANDINAVIAN JOURNAL OF STATISTICS,2004,31(3):333-346.
APA Yu, KM,&Lu, ZD.(2004).Local linear additive quantile regression.SCANDINAVIAN JOURNAL OF STATISTICS,31(3),333-346.
MLA Yu, KM,et al."Local linear additive quantile regression".SCANDINAVIAN JOURNAL OF STATISTICS 31.3(2004):333-346.
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