Confidence bands for Horvitz-Thompson estimators using sampled noisy functional data

DOI10.3150/12-BEJ443zbMath1457.62394arXiv1105.2135MaRDI QIDQ2435235

Hervé Cardot, Etienne Josserand, David Degras

Publication date: 4 February 2014

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1105.2135

zbMATH Keywords

central limit theoremspace of continuous functionsmaximal inequalitiessurvey samplingfunctional dataCLTlocal polynomial smoothingsuprema of Gaussian processesweighted cross-validation

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Functional data analysis (62R10) Inequalities; stochastic orderings (60E15) Central limit and other weak theorems (60F05) Sampling theory, sample surveys (62D05) Nonparametric tolerance and confidence regions (62G15)

Related Items

Functional principal subspace sampling for large scale functional data analysis, Kolmogorov-Smirnov simultaneous confidence bands for time series distribution function, Simultaneous confidence bands for the distribution function of a finite population and of its superpopulation, On estimators of the mean of Infinite dimensional data in finite populations, Uniform convergence and asymptotic confidence bands for model-assisted estimators of the mean of sampled functional data, Unexpected properties of bandwidth choice when smoothing discrete data for constructing a functional data classifier, Variance Estimation and Asymptotic Confidence Bands for the Mean Estimator of Sampled Functional Data with High Entropy Unequal Probability Sampling Designs, A centroid classifier for functional/longitudinal data, Simultaneous confidence bands for the distribution function of a finite population in stratified sampling, Estimating with kernel smoothers the mean of functional data in a finite population setting. A note on variance estimation in presence of partially observed trajectories

Uses Software

• ConfBands

Cites Work

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