Bias reduction in kernel density estimation via Lipschitz condition

DOI10.1080/10485250903266058zbMath1182.62074OpenAlexW2122467210MaRDI QIDQ5189270

Kairat T. Mynbaev, Carlos Martins-Filho

Publication date: 15 March 2010

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

Full work available at URL: https://mpra.ub.uni-muenchen.de/24904/2/MPRA_paper_24904.pdf

zbMATH Keywords

bias reductionkernel density estimationLipschitz conditions

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Monte Carlo methods (65C05)

Related Items (10)

Smoothed conditional scale function estimation in AR(1)-ARCH(1) processes ⋮ Density estimates of low bias ⋮ New classes of density estimates of low bias ⋮ Methodology for nonparametric bias reduction in kernel regression estimation ⋮ Canonical higher-order kernels for density derivative estimation ⋮ Improving bias in kernel density estimation ⋮ In search of an optimal kernel for a bias correction method for density estimators ⋮ Bias reduction in kernel density estimation ⋮ Unified estimation of densities on bounded and unbounded domains ⋮ Consistency and asymptotic normality for a nonparametric prediction under measurement errors

Cites Work

• Unnamed Item
• Exact mean integrated squared error
• Generalized jackknifing and higher order kernels
• Optimizing Kernel Methods: A Unifying Variational Principle
• A Comparison of Higher-Order Bias Kernel Density Estimators
• Stochastic Limit Theory
• A simple bias reduction method for density estimation
• Boosting kernel density estimates: A bias reduction technique?
• On Estimation of a Probability Density Function and Mode

This page was built for publication: Bias reduction in kernel density estimation via Lipschitz condition