Bandwidth Selection for Local Linear Regression Smoothers

DOI10.1111/1467-9868.00361zbMath1067.62038OpenAlexW2069374968MaRDI QIDQ4672162

Eric Matzner-Løber, Marten H. Wegkamp, Nicolas W. Hengartner

Publication date: 29 April 2005

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1467-9868.00361

zbMATH Keywords

Local linear regression smootherOracle inequalityUniversal bandwidth selection

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Linear regression; mixed models (62J05)

Related Items

A NONPARAMETRIC REGRESSION ESTIMATOR THAT ADAPTS TO ERROR DISTRIBUTION OF UNKNOWN FORM, Model selection in nonparametric regression, Local generalised method of moments: an application to point process‐based rainfall models, Generalized kernel regression estimator for dependent size-biased data, Local adaptive smoothing in kernel regression estimation, Locally modelled regression and functional data, Understanding past ocean circulations: a nonparametric regression case study, Moving Least Squares Regression for High-Dimensional Stochastic Simulation Metamodeling

Cites Work

• Minimax theory of image reconstruction
• Risk bounds for model selection via penalization
• A universally acceptable smoothing factor for kernel density estimates
• Nonasymptotic universal smoothing factors, kernel complexity and Yatracos classes
• Asymptotic distribution of the errors in scalar and vector quantizers