Weak and strong representations for quantile processes from finite populations with application to simulation size in resampling inference

DOI10.2307/3315562zbMath0706.62051OpenAlexW1964332961MaRDI QIDQ3486675

Jiahua Chen, C. F. Jeff Wu, Xi-Quan Shi

Publication date: 1990

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/3315562

zbMATH Keywords

bootstrapMonte Carlo simulationsstrong representationfinite populationjackknifequantile processBahadur-type representationrandom sampling with replacementrandom sampling without replacementstrong approximation resultweak representationaccuracy of resampling inferencesimulation size

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Sampling theory, sample surveys (62D05) Order statistics; empirical distribution functions (62G30) Strong limit theorems (60F15)

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Cites Work

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• On the asymptotic properties of the jackknife histogram
• On the bootstrap and confidence intervals
• On the number of bootstrap simulations required to construct a confidence interval
• On the validity of the formal Edgeworth expansion
• Better Bootstrap Confidence Intervals
• Prepivoting to reduce level error of confidence sets
• A NOTE ON SAMPLE QUANTILE PROCESSES OF FINITE POPULATIONS