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Distribution-free strong consistency for nonparametric kernel regression involving nonlinear time series
Lu, ZD; Cheng, P
1997-12-01
Source PublicationJOURNAL OF STATISTICAL PLANNING AND INFERENCE
ISSN0378-3758
Volume65Issue:1Pages:67-86
AbstractUnder quite mild conditions on the kernel and on the bandwidth, the distribution-free strong consistency is proved for the kernel regression and the modified kernel regression of an a-mixing stationary sequence in time series context. The condition imposed on the mixing coefficients is Sigma(j=1)(infinity)alpha(j)(1-1/v)1, v>1) or Sigma(j=1)(infinity)j(a-1)alpha(j) < infinity (a > 1), which is simple and weaker than those in the literature. (C) 1997 Elsevier Science B.V.
Keywordalpha-mixing stationary sequence kernel regression modified kernel regression distribution-free strong consistency nonlinear time series models
Language英语
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:000071469600004
PublisherELSEVIER SCIENCE BV
Citation statistics
Cited Times:20[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/13236
Collection中国科学院数学与系统科学研究院
AffiliationAcad Sinica, Inst Syst Sci, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Lu, ZD,Cheng, P. Distribution-free strong consistency for nonparametric kernel regression involving nonlinear time series[J]. JOURNAL OF STATISTICAL PLANNING AND INFERENCE,1997,65(1):67-86.
APA Lu, ZD,&Cheng, P.(1997).Distribution-free strong consistency for nonparametric kernel regression involving nonlinear time series.JOURNAL OF STATISTICAL PLANNING AND INFERENCE,65(1),67-86.
MLA Lu, ZD,et al."Distribution-free strong consistency for nonparametric kernel regression involving nonlinear time series".JOURNAL OF STATISTICAL PLANNING AND INFERENCE 65.1(1997):67-86.
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