Necessary and sufficient conditions for the multivariate bootstrap of the mean

DOI10.1016/0167-7152(94)90106-6zbMath0796.62020OpenAlexW2033137876MaRDI QIDQ1324604

Steven J. Sepanski

Publication date: 11 October 1994

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

Full work available at URL: https://doi.org/10.1016/0167-7152(94)90106-6

zbMATH Keywords

affine transformationsnecessary and sufficient conditionsbootstrap central limit theoremgeneralized domain of attractionrandom vectorsdomain of normal attractionalmost sure CLTbootstrap sample meanin probability CLT

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Central limit and other weak theorems (60F05) Nonparametric statistical resampling methods (62G09) Strong limit theorems (60F15)

Related Items

Asymptotics for multivariate \(t\)-statistic for random vectors in the generalized domain of attraction of the multivariate normal law

Cites Work

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• Necessary conditions for the bootstrap of the mean
• Matrix normalization of sums of random vectors in the domain of attraction of the multivariate normal
• Some asymptotic theory for the bootstrap
• Convergence of moments and related functional in the general central limit theorem in banach spaces
• Convergence of types in k-space