Bootstrap for Multifractal Analysis
type: Distribution
access URL: https://ens-lyon.hal.science/ensl-00080285
format: HTML
issued: 2026-05-12T06:05:29.363179
modified: 2026-05-12T06:05:29.295660

test_moissonnage_selune
type: Agent

Bootstrap for Multifractal Analysis
type: Dataset
contact point: Organization
  fn: CCSD
keyword: wavelet
keyword: infoeu-reposemanticsconferenceobject
keyword: multifractal-analysis
keyword: spisignalengineering-sciences-physicssignal-and-image-processing
keyword: infoinfo-tscomputer-science-cssignal-and-image-processing
keyword: conference-papers
keyword: spiotherengineering-sciences-physicsother
keyword: bootstrap
landing page: International Conference on Acoustics, Speech and Signal Processing
description: Multifractal analysis, which mainly consists in estimating scaling exponents, has become a popular tool for empirical data analysis. Although widely used in different applications, the statistical performance and the reliability of the estimation procedures are still poorly known. Notably, little is known about confidence intervals, though they are of first importance in applications. The present work investigates the potential uses of bootstrap for multifractal estimation: Can bootstrap improve current estimation procedures or be used to obtain reliable confidence intervals~? Comparing the statistical performance of different estimators, our major result is to show that bootstrap based procedures provide us both with accurate estimates and reliable confidence intervals. We believe that this brings substantial improvements to practical empirical multifractal analyses.
issued: 2026-05-12T06:05:29.313779
language: en
modified: 2026-05-12T06:05:29.313784