Using i.i.d. bootstrap inference for general non-i.i.d. models

zbMath0811.62052MaRDI QIDQ1345547

Regina Y. Liu, Kesar Singh

Publication date: 4 May 1995

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

zbMATH Keywords

product-limit estimatorcoverage probabilitybootstrap confidence intervalsjackknife proceduresconservative inference

Mathematics Subject Classification ID

Nonparametric tolerance and confidence regions (62G15) Nonparametric statistical resampling methods (62G09)

Related Items (8)

Combinatorial stochastic processes ⋮ A central limit theorem for bootstrap sample sums from non-i.i.d. models ⋮ Kesar Singh's contributions to statistical methodology ⋮ Valid post-selection inference in model-free linear regression ⋮ Bootstrap, wild bootstrap, and asymptotic normality ⋮ On inference validity of weighted U-statistics under data heterogeneity ⋮ Asymptotically robust variance estimation for person-time incidence rates ⋮ Five Nonobvious Changes in Editorial Practice for Editors and Reviewers to Consider When Evaluating Submissions in a Post p < 0.05 Universe

Cites Work

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• Bootstrap procedures under some non-i.i.d. models
• Theoretical comparison of bootstrap confidence intervals
• Bootstrap methods: another look at the jackknife
• A general theory for jackknife variance estimation
• The product-limit estimator and the bootstrap: Some asymptotic representations
• Bootstrap confidence intervals for a class of parametric problems
• Better Bootstrap Confidence Intervals
• Prepivoting to reduce level error of confidence sets
• A Note on Quantiles in Large Samples

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