One-sided cross-validation for nonsmooth regression functions

DOI10.1080/10485252.2013.817575zbMath1416.62227OpenAlexW1981968764MaRDI QIDQ2863056

Olga Y. Savchuk, Simon P. Sheather, Jeffrey D. Hart

Publication date: 21 November 2013

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485252.2013.817575

zbMATH Keywords

cross-validationlocal linear estimatorbandwidth selectionaverage squared errormean average squared error

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20)

Related Items (2)

Fully robust one-sided cross-validation for regression functions ⋮ One-Sided Cross-Validation for Nonsmooth Density Functions

Uses Software

• UCI-ml

Cites Work

• Asymptotics for least squares cross-validation bandwidths in nonsmooth cases
• Consistent nonparametric regression. Discussion
• Robustness of one-sided cross-validation to autocorrelation
• Miscellanea. A note on design transformation and binning in nonparametric curve estimation
• Applied Linear Regression
• Indirect Cross-Validation for Density Estimation
• A Comparison of Two Bandwidth Selectors OSCV and AICc in Nonparametric Regression

This page was built for publication: One-sided cross-validation for nonsmooth regression functions