Kernel estimation for a superpopulation probability density function under informative selection

DOI10.1007/S40300-017-0127-XzbMath1392.62099OpenAlexW2761590184MaRDI QIDQ1689529

Daniel Bonnéry, François Coquet, F. Jay Breidt

Publication date: 12 January 2018

Published in: Metron (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s40300-017-0127-x

zbMATH Keywords

Nadaraya-Watson estimatorcomplex surveyBochner's lemmaprobability density function (pdf)survey weighting D

Mathematics Subject Classification ID

Density estimation (62G07) Sampling theory, sample surveys (62D05)

Related Items (3)

Foreword to the special issue on ``Advances in survey statistics ⋮ Kernel density estimation based on the distinct units in sampling with replacement ⋮ Kernel density estimation from complex surveys in the presence of complete auxiliary information

Uses Software

• ks
• BonneryBreidtCoquetMetronKDE
• GitHub

Cites Work

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• Sample surveys: inference and analysis
• Asymptotic properties of kernel density estimation with complex survey data
• Uniform convergence of the empirical cumulative distribution function under informative selection from a finite population
• Asymptotics for the maximum sample likelihood estimator under informative selection from a finite population
• Sampling Statistics
• A new approach to weighting and inference in sample surveys
• Introduction to nonparametric estimation

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