Better Bootstrap Confidence Intervals for Regression Curve Estimation

DOI10.1080/02331889508802498zbMath0836.62031OpenAlexW2048100687MaRDI QIDQ4857301

Emmanuel Jolivet, Sylvie Huet, Wolfgang Karl Härdle

Publication date: 6 May 1996

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331889508802498

zbMATH Keywords

confidence intervalskernel estimatorscurve estimationnonparametric regressioncoverage accuracybias correctionwild bootstrapsmoothing parameter selectionundersmoothingexplicit bias estimationheteroscedatic variance structure

Mathematics Subject Classification ID

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

Related Items

Automatic bandwidth choice and confidence intervals in nonparametric regression, A simple bootstrap method for constructing nonparametric confidence bands for functions, Pointwise Confidence Intervals in Nonparametric Regression with Heteroscedastic Error Structure, The choice of smoothing parameter in nonparametric regression through wild bootstrap, Nonparametric inference via bootstrapping the debiased estimator

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Rate of convergence for the wild bootstrap in nonparametric regression
• On bootstrapping kernel spectral estimates
• On bootstrap confidence intervals in nonparametric regression
• Jackknife, bootstrap and other resampling methods in regression analysis
• Bootstrap simultaneous error bars for nonparametric regression
• Bootstrapping in Nonparametric Regression: Local Adaptive Smoothing and Confidence Bands
• Edgeworth expansions for nonparametric density estimators, with applications
• The bootstrap and Edgeworth expansion