Yu, Keming and Jones, M. C.
|DOI (Digital Object Identifier) Link:||http://doi.org/10.1016/S0167-9473(97)00006-6|
|Google Scholar:||Look up in Google Scholar|
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.|
|Keywords:||boundary behaviour; conditional quantile; kernel smoothing; local polynomial fit|
|Academic Unit/Department:||Mathematics, Computing and Technology > Mathematics and Statistics
Mathematics, Computing and Technology
|Depositing User:||Sarah Frain|
|Date Deposited:||11 May 2011 10:09|
|Last Modified:||15 Jan 2016 15:04|
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