Wild Bootstrap of the Sample Mean in the Infinite Variance Case

DOI10.1080/07474938.2012.690660zbMath1491.62033OpenAlexW2133953615MaRDI QIDQ5080545

Iliyan Georgiev, A. M. Robert Taylor, Giuseppe Cavaliere

Publication date: 31 May 2022

Published in: Econometric Reviews (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/07474938.2012.690660

zbMATH Keywords

bootstrapweak convergencestable distributionsrandom probability measures

Mathematics Subject Classification ID

Infinitely divisible distributions; stable distributions (60E07) Applications of statistics to economics (62P20) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Nonparametric statistical resampling methods (62G09)

Related Items (4)

LINK OF MOMENTS BEFORE AND AFTER TRANSFORMATIONS, WITH AN APPLICATION TO RESAMPLING FROM FAT-TAILED DISTRIBUTIONS ⋮ UNIT ROOT INFERENCE FOR NON-STATIONARY LINEAR PROCESSES DRIVEN BY INFINITE VARIANCE INNOVATIONS ⋮ Bootstrapping the mean vector for the observations in the domain of attraction of a multivariate stable law ⋮ A justification of conditional confidence intervals

Cites Work

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• Subsampling
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• A Three-step Method for Choosing the Number of Bootstrap Repetitions
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• The Dependent Wild Bootstrap
• A PARAMETRIC BOOTSTRAP FOR HEAVY-TAILED DISTRIBUTIONS
• Testing Statistical Hypotheses
• Inference in Arch and Garch Models with Heavy-Tailed Errors
• Inference When a Nuisance Parameter Is Not Identified Under the Null Hypothesis
• An Introduction to the Theory of Point Processes
• Subsampling inference for the mean in the heavy-tailed case.

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