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A comparison of local constant and local linear regression quantile estimators

Yu, Keming and Jones, M. C. (1997). A comparison of local constant and local linear regression quantile estimators. Computational Statistics and Data Analysis, 25(2) pp. 159–166.

DOI (Digital Object Identifier) Link: http://dx.doi.org/10.1016/S0167-9473(97)00006-6
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Abstract

Two popular nonparametric conditional quantile estimation methods, local constant fitting and local linear fitting, are compared. We note the relative lack of differences in results between the two approaches. While maintaining the expected preference for the local linear version, the arguments in favour are relatively slight, at least in the interior, and not as compelling as may be thought. The main differences between the approaches lie at the boundaries.

Item Type: Journal Article
Copyright Holders: 1997 Elsevier Science B.V.
ISSN: 0167-9473
Keywords: boundary behaviour; conditional quantile; kernel smoothing; local polynomial fit
Academic Unit/Department: Mathematics, Computing and Technology > Mathematics and Statistics
Item ID: 24111
Depositing User: Sarah Frain
Date Deposited: 11 May 2011 10:09
Last Modified: 11 May 2011 10:09
URI: http://oro.open.ac.uk/id/eprint/24111
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