Please use this identifier to cite or link to this item:
Title: Confidence intervals based on local linear smoother
Authors: Chen, S.X. 
Qin, Y.S.
Keywords: Confidence interval
Coverage probability
Edgeworth expansion
Non-parametric regression
Normal approximation
Issue Date: Mar-2002
Citation: Chen, S.X.,Qin, Y.S. (2002-03). Confidence intervals based on local linear smoother. Scandinavian Journal of Statistics 29 (1) : 89-99. ScholarBank@NUS Repository.
Abstract: Point-wise confidence intervals for a non-parametric regression function in conjunction with the popular local linear smoother are considered. The confidence intervals are based on the asymptotic normal distribution of the local linear smoother. Their coverage accuracy is evaluated by developing Edgeworth expansion for the coverage probability. It is found that the coverage error near the boundary of the support of the regression function is of a larger order than that in the interior, which implies that the local linear smoother is not adaptive to the boundary in terms of coverage. This is quite unexpected as the local linear smoother is adaptive to the boundary in terms of the mean squared error.
Source Title: Scandinavian Journal of Statistics
ISSN: 03036898
DOI: 10.1111/1467-9469.00028
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

checked on Jul 13, 2021

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.