Bootstrap for Multifractal Analysis

Patrice Abry (1) , Herwig Wendt (1)

1 Phys-ENS - Laboratoire de Physique de l'ENS Lyon

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.

Mots clés: Multifractal analysis; Bootstrap; Wavelet

Domaines: Autre; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Patrice Abry, Herwig Wendt. Bootstrap for Multifractal Analysis. International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2006, Toulouse, France. ⟨ensl-00080285⟩