A new information criterion-based bandwidth selection method for non-parametric regressions

DOI10.1080/00949655.2016.1164158OpenAlexW2325336577MaRDI QIDQ5221544

Sijia Xiang, Weixin Yao

Publication date: 1 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://escholarship.org/uc/item/8303r0fw

zbMATH Keywords

non-parametric regressionbandwidth selectorinformation criterion method

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• car
• carData

Cites Work

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• Bayesian bandwidth estimation for a nonparametric functional regression model with unknown error density
• Generalized likelihood ratio statistics and Wilks phenomenon
• Local linear regression smoothers and their minimax efficiencies
• An Effective Bandwidth Selector for Local Least Squares Regression
• Loss and risk in smoothing parameter selection
• How Far Are Automatically Chosen Regression Smoothing Parameters From Their Optimum?
• Design-adaptive Nonparametric Regression
• Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion
• Calibrating the Degrees of Freedom for Automatic Data Smoothing and Effective Curve Checking

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