Asymptotic behavior of bandwidth selected by the cross-validation method for local polynomial fitting

DOI10.1006/jmva.2001.2048zbMath1025.62016OpenAlexW2088987892MaRDI QIDQ1861386

Yingcun Xia, Wai Keung Li

Publication date: 16 March 2003

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1006/jmva.2001.2048

zbMATH Keywords

local polynomial fittingcross-validationstrongly mixing

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20)

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Cites Work

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• Weak convergence for weighted empirical processes of dependent sequences
• Central limit theorem for integrated square error of multivariate nonparametric density estimators
• Data-driven bandwidth choice for density estimation based on dependent data
• Extent to which least-squares cross-validation minimises integrated square error in nonparametric density estimation
• Optimal bandwidth selection in nonparametric regression function estimation
• Quadratic errors for nonparametric estimates under dependence
• Comparison of two bandwidth selectors with dependent errors
• Strong consistency of least squares estimates in normal linear regression
• A short note on optimal bandwidth selection for kernel estimators
• Comparison of bandwidth selectors in nonparametric regression under dependence
• Asymptotic behaviors of some measures of accuracy in nonparametric curve estimation with dependent observations
• The functional law of the iterated logarithm for stationary strongly mixing sequences
• Bandwidth selection: Classical or plug-in?
• Local linear regression smoothers and their minimax efficiencies
• An Effective Bandwidth Selector for Local Least Squares Regression
• Nonparametric Estimation and Identification of Nonlinear ARCH Time Series Strong Convergence and Asymptotic Normality: Strong Convergence and Asymptotic Normality
• How Far Are Automatically Chosen Regression Smoothing Parameters From Their Optimum?
• KERNEL REGRESSION SMOOTHING OF TIME SERIES
• MULTIVARIATE LOCAL POLYNOMIAL REGRESSION FOR TIME SERIES:UNIFORM STRONG CONSISTENCY AND RATES
• Local Polynomial Estimation of Regression Functions for Mixing Processes
• BANDWIDTH SELECTION IN KERNEL SMOOTHING OF TIME SERIES

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