Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network

  Advanced Search  

Wavelet Based Estimation for Univariate Stable Laws

Summary: Wavelet Based Estimation for Univariate
Stable Laws
Anestis Antoniadis
Laboratoire IMAG-LMC, University Joseph Fourier,
BP 53, 38041 Grenoble Cedex 9, France
Andrey Feuerverger
Department of Statistics, University of Toronto,
Toronto, Ontario, M5S 3G3 Canada
Paulo Gon¸calves
INRIA Rh^one-Alpes, ZIRST, 655 Avenue de l'Europe,
38330 Monbonnot Saint Martin, France.
Stable distributions are characterized by four parameters which can be estimated
via a number of methods, and although approximate maximum likelihood estimation
techniques have been proposed, they are computationally intensive and difficult to
implement. This article describes a fast, wavelet-based, regression-type method for
estimating the parameters of a stable distribution. Fourier domain representations,
combined with a wavelet multiresolution approach, are shown to be effective and
highly efficient tools for inference in stable law families. Our procedures are


Source: Antoniadis, Anestis - Laboratoire Jean Kuntzmann, Université Joseph Fourier


Collections: Mathematics