Consistency of the jackknife-after-bootstrap variance estimator for the bootstrap quantiles of a Studentized statistic

DOI10.1214/009053605000000507zbMath1086.62033arXivmath/0602328OpenAlexW2054317850MaRDI QIDQ2368860

Soumendra Nath Lahiri

Publication date: 28 April 2006

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/math/0602328

zbMATH Keywords

tablesconsistencyweak dependenceblock bootstrap

Mathematics Subject Classification ID

Related Items (4)

Statistical Model for Biochemical Network Inference ⋮ A nonparametric plug-in rule for selecting optimal block lengths for block bootstrap methods ⋮ Predictive quantile regressions under persistence and conditional heteroskedasticity ⋮ Non-nested model selection based on the quantiles and it’s application in time series

Cites Work

• Unnamed Item
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• Refinements in asymptotic expansions for sums of weakly dependent random vectors
• A nonparametric plug-in rule for selecting optimal block lengths for block bootstrap methods
• Second order optimality of stationary bootstrap
• Resampling a coverage pattern
• The use of subseries values for estimating the variance of a general statistic from a stationary sequence
• Edgeworth correction by bootstrap in autoregressions
• Second order and \(L^ p\)-comparisons between the boostrap and empirical Edgeworth expansion methodologies
• A general resampling scheme for triangular arrays of \(\alpha\)-mixing random variables with application to the problem of spectral density estimation
• On the validity of the formal Edgeworth expansion
• Bootstrap methods: another look at the jackknife
• Validity of blockwise bootstrap for empirical processes with stationary observations
• Blockwise bootstrapped empirical process for stationary sequences
• Second-order correctness of the blockwise bootstrap for stationary observations
• Resampling methods for dependent data
• Theoretical comparisons of block bootstrap methods
• A general theory for jackknife variance estimation
• The jackknife and the bootstrap for general stationary observations
• Asymptotic distribution of statistics in time series
• The jackknife and bootstrap
• On Edgeworth expansion and moving block bootstrap for Studentized \(M\)-estimators in multiple linear regression models
• Bootstrap Inference for a First-Order Autoregression with Positive Innovations
• General M-estimates for contaminated p th-order autoregressive processes: Consistency and asymptotic normality
• Asymptotic expansions for sums of weakly dependent random vectors
• Asymptotic expansions in the central limit theorem under moment conditions
• The Stationary Bootstrap
• Jackknifing the bootstrap: some monte carlo evidence
• The tapered block bootstrap for general statistics from stationary sequences
• Jackknifing L-Statistics with Smooth Weight Functions
• ON THE JACKKNIFE-AFTER-BOOTSTRAP METHOD FOR DEPENDENT DATA AND ITS CONSISTENCY PROPERTIES
• On blocking rules for the bootstrap with dependent data
• Probability Inequalities for Sums of Independent Random Variables
• The bootstrap and Edgeworth expansion

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