Reducing bias in curve estimation by use of weights.

DOI10.1016/S0167-9473(98)00081-4zbMath1042.62531OpenAlexW2087714606MaRDI QIDQ1285485

Turlach, Berwin A., Hall, Peter

Publication date: 28 April 1999

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-9473(98)00081-4

zbMATH Keywords

Nonparametric regressionBandwidthBootstrapKernel density estimationCross-validationWeighted bootstrapAbramson's methodNonparametric density estimationVariable kernel methods

Mathematics Subject Classification ID

Density estimation (62G07) Nonparametric statistical resampling methods (62G09)

Related Items

Constraining kernel estimators in semiparametric copula mixture models, Estimation, diagnostics, and extensions of nonparametric Hawkes processes with kernel functions, The generalized cross entropy method, with applications to probability density estimation, Estimation in hazard regression models under ordered departures from proportionality, Maximum likelihood kernel density estimation: on the potential of convolution sieves, Density estimation from aggregate data, Reweighted kernel density estimation, Bias reduction in kernel binary regression, Kernel density estimation based distributionally robust mean-CVaR portfolio optimization, Density estimation and nonparametric inferences using maximum likelihood weighted kernels

Uses Software

• KernSmooth

Cites Work

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