Kernel selection in nonparametric regression

DOI10.3103/S1066530720010044zbMath1476.62069arXiv2006.07673MaRDI QIDQ2239312

Yanyan Li

Publication date: 3 November 2021

Published in: Mathematical Methods of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2006.07673

zbMATH Keywords

model selectionnonparametric estimatorsregression modelprojection estimators

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07)

Related Items (1)

Nadaraya–Watson estimator for I.I.D. paths of diffusion processes

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Nonparametric weighted estimators for biased data
• Bandwidth selection in kernel density estimation: oracle inequalities and adaptive minimax optimality
• Concentration inequalities and model selection. Ecole d'Eté de Probabilités de Saint-Flour XXXIII -- 2003.
• Estimator selection: a new method with applications to kernel density estimation
• On a Nadaraya-Watson estimator with two bandwidths
• Bandwidth selection for the Wolverton-Wagner estimator
• Warped bases for conditional density estimation
• Uniform in bandwidth consistency of kernel-type function estimators
• Optimal Kernel Selection for Density Estimation
• Remarks on Some Nonparametric Estimates of a Density Function
• Mathematical Foundations of Infinite-Dimensional Statistical Models
• On Estimation of a Probability Density Function and Mode
• Introduction to nonparametric estimation
• An empirical process approach to the uniform consistency of kernel-type function estimators

This page was built for publication: Kernel selection in nonparametric regression