Bootstrapping nonparametric density estimators with empirically chosen bandwidths.

DOI10.1214/aos/1013203461zbMath1043.62028OpenAlexW1589992100MaRDI QIDQ1848913

Kee-Hoon Kang, Hall, Peter

Publication date: 14 November 2002

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1013203461

zbMATH Keywords

rate of convergenceEdgeworth expansionskernel methodssecond-order accuracysmoothing parameter

Mathematics Subject Classification ID

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Uses Software

• KernSmooth
• bootstrap
• bootlib

Cites Work

• On the number of bootstrap simulations required to construct a confidence interval
• Estimation of integrated squared density derivatives
• Exact mean integrated squared error
• Bootstrap choice of the smoothing parameter in kernel density estimation
• Edgeworth expansions for nonparametric density estimators, with applications
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