An iterative bandwidth selector for kernel estimation of densities and their derivatives

DOI10.1080/10485259408832598zbMath1380.62146OpenAlexW2074497516MaRDI QIDQ3432393

Joachim Engel, Theo Gasser, Eva Herrmann

Publication date: 16 April 2007

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

Full work available at URL: https://doi.org/10.1080/10485259408832598

Mathematics Subject Classification ID

Density estimation (62G07)

Related Items

Universal smoothing factor selection in density estimation: theory and practice. (With discussion), Infill asymptotics for adaptive kernel estimators of spatial intensity, Infill asymptotics and bandwidth selection for kernel estimators of spatial intensity functions, Contribution to the bandwidth choice for kernel density estimates, On estimating the cumulant generating function of linear processes, A general and fast convergent bandwidth selection method of kernel estimator, Bayesian model robustness via disparities, Estimation of densities and derivatives of densities with directional data., Multistage plug—in bandwidth selection for kernel distribution function estimates, An assessment of finite sample performance of adaptive methods in density estimation

Cites Work

• Using non-stochastic terms to advantage in kernel-based estimation of integrated squared density derivatives
• Extent to which least-squares cross-validation minimises integrated square error in nonparametric density estimation
• Lower bounds for bandwidth selection in density estimation
• Smoothed cross-validation
• A simple root \(n\) bandwidth selector
• Exact mean integrated squared error
• On optimal data-based bandwidth selection in kernel density estimation
• A Flexible and Fast Method for Automatic Smoothing
• Choice of bandwidth for kernel regression when residuals are correlated