Identification

Title

Fast nonparametric quantile regression with arbitrary smoothing methods

Abstract

The calculation of nonparametric quantile regression curve estimates is often computational intensive, as typically an expensive nonlinear optimization problem is involved. This paper proposes a fast and easy-to-implement method for computing such estimates. The main idea is to approximate the costly nonlinear optimization by a sequence of well-studied penalized least-squares type nonparametric mean regression estimation problems. The new method can be paired with different nonparametric smoothing methods and can also be applied to higher dimensional settings. Therefore, it provides a unified framework for computing different types of nonparametric quantile regression estimates, and it also greatly broadens the scope of the applicability of quantile regression methodology. This wide-applicability and the practical performance of the proposed method are illustrated with smoothing spline and wavelet curve estimators, for both uni- and bivariate settings. Results from numerical experiments suggest that estimates obtained from the proposed method are superior to many competitors.

Resource type

document

Resource locator

Unique resource identifier

code

https://n2t.org/ark:/85065/d7057hhf

codeSpace

Dataset language

eng

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Classification of spatial data and services

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geoscientificInformation

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Text

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title

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reference date

date type

publication

effective date

2016-01-01T00:00:00Z

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date type

publication

effective date

2011-06-01T00:00:00Z

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Use constraints

This is an electronic version of an article published in Oh, H.-S., Lee, T.C., Nychka, D., 2011: Fast nonparametric quantile regression with arbitrary smoothing methods. Journal of Computational and Graphical Statistics, 20 (2), 510-526. Journal of the American Statistical Association is available online at: http://www.tandfonline.com/openurl?genre=article&issn=1061-8600&volume=20&issue=2&spage=510

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

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