A study of local linear ridge regression estimators

DOI10.1016/S0378-3758(00)00161-0zbMath0965.62056MaRDI QIDQ5931397

Wen-Shuenn Deng, Ming-Yen Cheng, Chih-Kang Chu

Publication date: 31 July 2001

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

zbMATH Keywords

boundary effectfinite-sample behaviorlocal linear estimatorlocal linear ridge regression estimatorridge regression

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07) Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05)

Uses Software

• KernSmooth

Cites Work

• Bandwidth choice for nonparametric regression
• Optimal bandwidth selection in nonparametric regression function estimation
• Nonparametric regression analysis of longitudinal data
• Smoothing techniques. With implementation in S
• Exact mean integrated squared error
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• On the role of the shrinkage parameter in local linear smoothing
• Smoothing methods in statistics
• Local linear regression smoothers and their minimax efficiencies
• Finite-Sample Variance of Local Polynomials: Analysis and Solutions
• Double smoothing for kernelestimators in nonparametric regression
• How Far Are Automatically Chosen Regression Smoothing Parameters From Their Optimum?
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