Bootstrap MISE Estimators to Obtain Bandwidth for Kernel Density Estimation

DOI10.1080/03610918.2010.500108zbMath1195.62038OpenAlexW2094842593MaRDI QIDQ3590018

Alan D. Hutson, Jeffrey C. Miecznikowski, Dongliang Wang

Publication date: 17 September 2010

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2010.500108

zbMATH Keywords

bootstrapbandwidthMSEkernel density

Mathematics Subject Classification ID

Density estimation (62G07) Nonparametric statistical resampling methods (62G09)

Related Items (4)

An Investigation of Quantile Function Estimators Relative to Quantile Confidence Interval Coverage ⋮ Joint confidence region estimation of L-moment ratios with an extension to right censored data ⋮ Density estimation via the random forest method ⋮ Dependence structure estimation using copula recursive trees

Uses Software

• R

Cites Work

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• A bandwidth selection for kernel density estimation of functions of random variables
• An asymptotically optimal window selection rule for kernel density estimates
• Some asymptotic theory for the bootstrap
• Do robust estimators work with real data?
• Bootstrap methods: another look at the jackknife
• Bootstrap choice of the smoothing parameter in kernel density estimation
• The length heuristic for simultaneous hypothesis tests
• The Exact Bootstrap Mean and Variance of an L-estimator
• Utilizing a quantile function approach to obtain exact bootstrap solutions

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