Bootstrapping the Dorfman–Hall–Chambers–Dunstan estimator of a finite population distribution function

DOI10.1080/10485250310001622604zbMath1053.62055OpenAlexW2004415333MaRDI QIDQ4819552

José Manuel Prada-Sánchez, María José Lombardía, Wenceslao González Manteiga

Publication date: 27 September 2004

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

Full work available at URL: https://doi.org/10.1080/10485250310001622604

zbMATH Keywords

bandwidthkernel estimationresampling methodsauxiliary information

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Sampling theory, sample surveys (62D05) Nonparametric statistical resampling methods (62G09)

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Cites Work

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• Weak and strong uniform consistency of the kernel estimate of a density and its derivatives
• Estimators of the finite population distribution function using nonparametric regression
• Approximation Theorems of Mathematical Statistics
• Properties of estimators of the finite population distribution function
• Bandwith selection for the smoothing of distribution functions
• Bootstrap Methods for Finite Populations
• Estimating distribution functions from survey data
• On Non-Parametric Estimates of Density Functions and Regression Curves

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