An improved kernel regression method based on Taylor expansion

DOI10.1016/j.amc.2007.03.085zbMath1193.94025OpenAlexW2023152424MaRDI QIDQ990620

Jiang-She Zhang, Cheng-Hu Zhou, Xing-Fang Huang

Publication date: 1 September 2010

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2007.03.085

zbMATH Keywords

kernel regressioncross-validationTaylor expansionnonparametric regressionnadaraya-watson estimator

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (2)

Adaptive image enhancement algorithm combining kernel regression and local homogeneity ⋮ Restoration of images corrupted by Gaussian and uniform impulsive noise

Uses Software

• KernSmooth
• bootstrap

Cites Work

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• Optimal bandwidth selection in nonparametric regression function estimation
• Nonparametric regression analysis of longitudinal data
• Comparison of bandwidth selectors in nonparametric regression under dependence
• On the use of nonparametric regression in assessing parametric regression models
• Estimating the Error Rate of a Prediction Rule: Improvement on Cross-Validation
• Cross-validation and multinomial prediction
• Local Polynomial Kernel Regression for Generalized Linear Models and Quasi-Likelihood Functions
• On Non-Parametric Estimates of Density Functions and Regression Curves

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