Root n bandwidths selectors in multivariate kernel density estimation

DOI10.1007/s00440-004-0357-8zbMath1050.62039OpenAlexW2038923306MaRDI QIDQ1885364

Min-Hsiao Tsai, Tiee-Jian Wu

Publication date: 28 October 2004

Published in: Probability Theory and Related Fields (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00440-004-0357-8

zbMATH Keywords

characteristic functioninformation boundcross-validationmultivariate datarelative convergence rate

Mathematics Subject Classification ID

Density estimation (62G07) Estimation in multivariate analysis (62H12) Asymptotic properties of nonparametric inference (62G20)

Related Items (4)

A variable bandwidth selector in multivariate kernel density estimation ⋮ ADAPTIVE ESTIMATION OF HETEROSKEDASTIC ERROR COMPONENT MODELS ⋮ Efficient estimation of the mode of continuous multivariate data ⋮ Root \(n\) estimates of vectors of integrated density partial derivative functionals

Cites Work

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• An asymptotically optimal window selection rule for kernel density estimates
• Optimal rates of convergence for nonparametric estimators
• Lower bounds for bandwidth selection in density estimation
• Smoothed cross-validation
• Bandwidth selection for kernel density estimation
• A simple root \(n\) bandwidth selector
• Best possibility constant for bandwidth selection
• Some theory for penalized spline generalized additive models
• Adaptive root \(n\) estimates of integrated squared density derivatives
• Multivariate plug-in bandwidth selection
• A Brief Survey of Bandwidth Selection for Density Estimation
• Optimal smoothing parameters for multivariate fized and adaptive kernel methods
• Biased and Unbiased Cross-Validation in Density Estimation
• Bootstrap choice of the smoothing parameter in kernel density estimation
• An automatic bandwidth selector for kernel density estimation
• Cross-Validation of Multivariate Densities
• Root n Bandwidth Selectors for Kernel Estimation of Density Derivatives
• Multivariate Bandwidth Selection for Local Linear Regression
• Comparison of Smoothing Parameterizations in Bivariate Kernel Density Estimation

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