A short note on optimal bandwidth selection for kernel estimators

DOI10.1016/0167-7152(90)90090-TzbMath0687.62025OpenAlexW2024945411MaRDI QIDQ1263184

Enno Mammen

Publication date: 1990

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

Full work available at URL: https://doi.org/10.1016/0167-7152(90)90090-t

zbMATH Keywords

kernel estimatorsbandwidth selectiondensity estimationdata-based bandwidthMean Integrated Squared Error

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Nonparametric estimation (62G05)

Related Items

A comparative study of several smoothing methods in density estimation ⋮ Bandwidth selection in kernel density estimation for interval-grouped data ⋮ On bandwidth choice for density estimation with dependent data ⋮ Universal smoothing factor selection in density estimation: theory and practice. (With discussion) ⋮ On the excess of average squared error for data-driven bandwidths in nonparametric trend estimation ⋮ Lower bounds for bandwidth selection in density estimation ⋮ Loss and risk in smoothing parameter selection ⋮ Asymptotic behavior of bandwidth selected by the cross-validation method for local polynomial fitting

Cites Work

• Extent to which least-squares cross-validation minimises integrated square error in nonparametric density estimation
• Estimation of integrated squared density derivatives
• On the amount of noise inherent in bandwidth selection for a kernel density estimator
• Lower bounds for bandwidth selection in density estimation
• How Far Are Automatically Chosen Regression Smoothing Parameters From Their Optimum?
• Biased and Unbiased Cross-Validation in Density Estimation

This page was built for publication: A short note on optimal bandwidth selection for kernel estimators