Bootstrapping the Chambers--Dunstan estimate of a finite population distribution function

DOI10.1016/S0378-3758(02)00240-9zbMath1022.62008OpenAlexW1964398534MaRDI QIDQ1408732

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

Publication date: 25 September 2003

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0378-3758(02)00240-9

zbMATH Keywords

finite populationdistribution functionauxiliary informationbandwidth parameterkernel density resampling methods

Mathematics Subject Classification ID

Sampling theory, sample surveys (62D05) Nonparametric statistical resampling methods (62G09)

Related Items (5)

Inference on finite population categorical response: nonparametric regression-based predictive approach ⋮ Non-parametric bootstrap mean squared error estimation for \(M\)-quantile estimators of small area averages, quantiles and poverty indicators ⋮ Small area estimation based on M-quantile models in presence of outliers in auxiliary variables ⋮ Estimation of a finite population distribution function based on a linear model with unknown heteroscedastic errors ⋮ Calibration methods for estimating quantiles

Cites Work

• 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
• The jackknife and bootstrap
• On estimating distribution functions and quantiles from survey data using auxiliary information
• On the Strong Law of Large Numbers and Related Results for Quasi-Stationary Sequences
• Properties of estimators of the finite population distribution function
• Bandwith selection for the smoothing of distribution functions
• Bootstrap Methods for Finite Populations
• Bias Robust Estimation in Finite Populations Using Nonparametric Calibration
• Estimating distribution functions from survey data
• A functional approach to estimating finite population distribution functions

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