Functional limit theorems for inverse bootstrap processes of sample quantiles

DOI10.1016/0167-7152(91)90119-CzbMath0732.62043OpenAlexW2026295976MaRDI QIDQ808578

Michael Falk

Publication date: 1991

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(91)90119-c

zbMATH Keywords

functional central limit theoremBrownian motionconfidence intervalsample quantilekernel estimatesmoothed bootstrapquantile functionbootstrap estimateempirical quantile processesinverse bootstrap process

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric statistical resampling methods (62G09) Functional limit theorems; invariance principles (60F17)

Related Items

Edgeworth expansions for studentized and prepivoted sample quantiles

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Weak convergence of the maximum error of the bootstrap quantile estimate
• On the estimation of the quantile density function
• Weighted empirical and quantile processes
• On the bootstrap and confidence intervals
• On a partial correction by the bootstrap
• Bootstrapping the distance between smooth bootstrap and sample quantile distribution
• Theoretical comparison of bootstrap confidence intervals
• On smoothing and the bootstrap
• A note on the accuracy of bootstrap percentile method confidence intervals for a quantile
• On the asymptotic accuracy of Efron's bootstrap
• Approximate distributions of order statistics. With applications to nonparametric statistics
• Bootstrap methods: another look at the jackknife
• The performance of kernel density functions in kernel distribution function estimation
• Weak convergence of smoothed and nonsmoothed bootstrap quantile estimates
• Relative efficiency and deficiency of kernel type estimators of smooth distribution functions
• Nonparametric Statistical Data Modeling
• On the deviations in the Skorokhod-Strassen approximation scheme