Optimal rates for local bandwidth selection

DOI10.1080/10485259608832689zbMath0872.62045OpenAlexW2038738791MaRDI QIDQ4349876

Martin L. Hazelton

Publication date: 25 August 1997

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485259608832689

zbMATH Keywords

mean squared errorsimulation studybandwidth selectionkernel density estimationrelative rate of convergence

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20)

Related Items

Inference for the mode of a log-concave density ⋮ An optimal local bandwidth selector for kernel density estimation

Uses Software

• pyuvdata

Cites Work

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• Using the bootstrap to estimate mean squared error and select smoothing parameter in nonparametric problems
• Using non-stochastic terms to advantage in kernel-based estimation of integrated squared density derivatives
• Smooth optimum kernel estimators of densities, regression curves and modes
• Estimation of integrated squared density derivatives
• On the amount of noise inherent in bandwidth selection for a kernel density estimator
• Optimal rates of convergence for nonparametric estimators
• Asymptotically optimum kernels for density estimation at a point
• Lower bounds for bandwidth selection in density estimation
• Exact mean integrated squared error
• Bounds for estimation of density functions and their derivatives
• A data-based algorithm for choosing the window width when estimating the density at a point
• Remarks on Some Nonparametric Estimates of a Density Function
• On the Best Obtainable Asymptotic Rates of Convergence in Estimation of a Density Function at a Point
• On Estimation of a Probability Density Function and Mode