Double smoothing for kernelestimators in nonparametric regression

DOI10.1080/10485259208832537zbMath1360.62143OpenAlexW2093880742MaRDI QIDQ3432324

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Publication date: 16 April 2007

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

Full work available at URL: https://doi.org/10.1080/10485259208832537

Mathematics Subject Classification ID

Nonparametric estimation (62G05)

Related Items (8)

DOUBLE SMOOTHING ESTIMATION OF THE MULTIVARIATE REGRESSION FUNCTION IN NONPARAMETRIC REGRESSION ⋮ Estimation of change-points in a nonparametric regression function through kernel density estimation ⋮ Binned modified cross–validation with dependent errors ⋮ An interpolation method for adapting to sparse design in multivariate nonparametric regression ⋮ A Remedy for Kernel Estimation Under Random Design ⋮ A study of local linear ridge regression estimators ⋮ Triple smoothing estimation of the regression function and its derivatives in nonparametric regression ⋮ A regression point of view toward density estimation

Cites Work

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• Convolution type estimators for nonparametric regression
• Choosing a kernel regression estimator. With comments and a rejoinder by the authors
• Approximation Theorems of Mathematical Statistics
• A Unifying Approach to Nonparametric Regression Estimation

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