Adaptive wavelet based estimator of the memory parameter for stationary Gaussian processes
Statistics Theory
2008-03-27 v2 Statistics Theory
Abstract
This work is intended as a contribution to a wavelet-based adaptive estimator of the memory parameter in the classical semi-parametric framework for Gaussian stationary processes. In particular we introduce and develop the choice of a data-driven optimal bandwidth. Moreover, we establish a central limit theorem for the estimator of the memory parameter with the minimax rate of convergence (up to a logarithm factor). The quality of the estimators are attested by simulations.
Cite
@article{arxiv.math/0701770,
title = {Adaptive wavelet based estimator of the memory parameter for stationary Gaussian processes},
author = {Jean-Marc Bardet and Hatem Bibi and Abdellatif Jouini},
journal= {arXiv preprint arXiv:math/0701770},
year = {2008}
}