Asymptotically best bandwidth selectors in kernel density estimation

DOI10.1016/0167-7152(94)90143-0zbMath0787.62043OpenAlexW1982076905MaRDI QIDQ1314689

V. Pereyra

Publication date: 27 March 1994

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(94)90143-0

zbMATH Keywords

Fisher informationkernel density estimatorbandwidth selectionbest constantbandwidth factorizationfastest possible rate of convergencenonnegative kernel estimatorsasymptotically best data based choices of the bandwidth

Mathematics Subject Classification ID

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

Related Items (5)

Bandwidth selection for kernel density estimation: a review of fully automatic selectors ⋮ Universal smoothing factor selection in density estimation: theory and practice. (With discussion) ⋮ The influence function of the optimal bandwidth for kernel density estimation ⋮ Exact risk approaches to smoothing parameter selection ⋮ Root-nconvergent transformation-kernel density estimation

Cites Work

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• Lower bounds for bandwidth selection in density estimation
• Smoothed cross-validation
• Bandwidth selection for kernel density estimation
• A simple root \(n\) bandwidth selector
• Exact mean integrated squared error
• Best possibility constant for bandwidth selection
• Progress in data-based bandwidth selection for kernel density estimation
• On optimal data-based bandwidth selection in kernel density estimation
• On the use of pilot estimators in bandwidth selection

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