Canonical higher-order kernels for density derivative estimation

DOI10.1016/j.spl.2012.03.013zbMath1296.62080OpenAlexW2059626291WikidataQ56288946 ScholiaQ56288946MaRDI QIDQ449407

Daniel J. Henderson, Christopher F. Parmeter

Publication date: 30 August 2012

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

Full work available at URL: https://doi.org/10.1016/j.spl.2012.03.013

zbMATH Keywords

derivative estimationAMISE

Mathematics Subject Classification ID

Density estimation (62G07)

Related Items (5)

Some results about kernel estimators for function derivatives based on stationary and ergodic continuous time processes with applications ⋮ Normal reference bandwidths for the general order, multivariate kernel density derivative estimator ⋮ Enforcing shape constraints on a probability density estimate using an additive adjustment curve ⋮ Asymptotics for function derivatives estimators based on stationary and ergodic discrete time processes ⋮ Uniform almost sure convergence and asymptotic distribution of the wavelet-based estimators of partial derivatives of multivariate density function under weak dependence

Uses Software

• KernSmooth

Cites Work

• Unnamed Item
• Smooth optimum kernel estimators of densities, regression curves and modes
• Choice of kernel order in density estimation
• Canonical kernels for density estimation
• Optimal asymmetric kernels
• EXACT MEAN INTEGRATED SQUARED ERROR OF HIGHER ORDER KERNEL ESTIMATORS
• Bias reduction in kernel density estimation via Lipschitz condition

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