A covariate-matched estimator of the error variance in nonparametric regression

DOI10.1080/10485250802626873zbMath1231.62065OpenAlexW2170284417MaRDI QIDQ3619659

Jichang du, Anton Schick

Publication date: 8 April 2009

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

Full work available at URL: https://doi.org/10.1080/10485250802626873

zbMATH Keywords

asymptotic normalitydifference-based estimatorU-processes

Mathematics Subject Classification ID

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

Related Items (6)

Asymptotically optimal differenced estimators of error variance in nonparametric regression ⋮ Optimal variance estimation based on lagged second-order difference in nonparametric regression ⋮ Efficient error variance estimation in non‐parametric regression ⋮ Variance estimation in nonparametric regression with jump discontinuities ⋮ Difference-based variance estimation in nonparametric regression with repeated measurement data ⋮ A least squares method for variance estimation in heteroscedastic nonparametric regression

Cites Work

• Limit theorems for \(U\)-processes
• Bandwidth choice for nonparametric regression
• Nonparametric functional data analysis. Theory and practice.
• Asymptotically optimal difference-based estimation of variance in nonparametric regression
• On variance estimation in nonparametric regression
• The estimation of residual variance in nonparametric regression
• Residual variance and residual pattern in nonlinear regression
• Estimating the error variance in nonparametric regression by a covariate-matched u-statistic
• Probability Inequalities for Sums of Bounded Random Variables

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