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: https://doi.org/10.1016/S0167-9473(97)00006-6

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.

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About

• Item ORO ID
• 24126
• Item Type
• Journal Item
• ISSN
• 0167-9473
• Keywords
• boundary behaviour; conditional quantile; kernel smoothing; local polynomial fit
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Copyright Holders
• © 1997 Elsevier Science B.V.
• Depositing User
• Sarah Frain