Reducing the mean squared error in kernel density estimation

DOI10.1016/j.jkss.2012.12.003zbMath1294.62076OpenAlexW2000344959MaRDI QIDQ395883

Choongrak Kim, Jinmi Kim

Publication date: 7 August 2014

Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jkss.2012.12.003

zbMATH Keywords

bias reductionvariance reductionhigher-order kernelskewing method

Mathematics Subject Classification ID

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

Uses Software

• KernSmooth

Cites Work

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• Smooth optimum kernel estimators of densities, regression curves and modes
• Reducing variance in univariate smoothing
• Exact mean integrated squared error
• Variable kernel density estimation
• Bias reduction in kernel density estimation by smoothed empirical transformations
• On bandwidth variation in kernel estimates. A square root law
• Skewing methods for two-parameter locally parametric density estimation
• On nonparametric kernel density estimates
• Generalized jackknifing and higher order kernels
• Improvement of Kernel Type Density Estimators
• Variable Kernel Estimates of Multivariate Densities
• On bias reduction in local linear smoothing
• A Comparison of Higher-Order Bias Kernel Density Estimators
• Skewing and Generalized Jackknifing in Kernel Density Estimation
• A simple bias reduction method for density estimation
• On Estimation of a Probability Density Function and Mode

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