Estimators of long-memory: Fourier versus wavelets |
| |
Authors: | Gilles Faÿ ,Eric Moulines,Franç ois Roueff,Murad S. Taqqu |
| |
Affiliation: | 1. Laboratoire Paul-Painlevé, Université Lille-1, 59655 Villeneuve-d’Ascq Cedex, France;2. Institut TELECOM, TELECOM ParisTech, LTCI CNRS, 46, rue Barrault, 75634 Paris Cedex 13, France;3. Department of Mathematics and Statistics, Boston University Boston, MA 02215, USA |
| |
Abstract: | Semi-parametric estimation methods of the long-memory exponent of a time series have been studied in several papers, some applied, others theoretical, some using Fourier methods, others using a wavelet-based technique. In this paper, we compare the Fourier and wavelet approaches to the local regression method and to the local Whittle method. We provide an overview of these methods, describe what has been done and indicate the available results and the conditions under which they hold. We discuss their relative strengths and weaknesses both from a practical and a theoretical perspective. We also include a simulation-based comparison. The software written to support this work is available on demand and we illustrate its use at the end of the paper. |
| |
Keywords: | Wavelet analysis Long range dependence Semi-parametric estimation |
本文献已被 ScienceDirect 等数据库收录! |
|