A Comparison of Two Bandwidth Selectors OSCV and AICc in Nonparametric Regression

DOI10.1081/SAC-200068387zbMath1075.62032MaRDI QIDQ5697365

Seongbaek Yi

Publication date: 17 October 2005

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

zbMATH Keywords

tablesnonparametric regressionimproved Akaike information criterionone sided cross-validation

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Monte Carlo methods (65C05)

Related Items (2)

Fully robust one-sided cross-validation for regression functions ⋮ One-sided cross-validation for nonsmooth regression functions

Cites Work

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• Bandwidth choice for nonparametric regression
• Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation
• Nonparametric smoothing and lack-of-fit tests
• An Effective Bandwidth Selector for Local Least Squares Regression
• A Flexible and Fast Method for Automatic Smoothing
• How Far Are Automatically Chosen Regression Smoothing Parameters From Their Optimum?
• Regression and time series model selection in small samples
• Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion
• One-Sided Cross-Validation
• ASYMPTOTIC STABILITY OF THE OSCV SMOOTHING PARAMETER SELECTION

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