Adaptive wavelet-based estimator of the memory parameter for stationary Gaussian processes

被引:7
|
作者
Bardet, Jean-Marc [1 ]
Bibi, Hatem [1 ]
Jouini, Abdellatif [2 ]
机构
[1] Univ Paris 01, Samos Matisse CES, CNRS, UMR 8174, F-75013 Paris, France
[2] Fac Sci Tunis, Dept Math, Tunis 1060, Tunisia
关键词
wavelet analysis; long range dependence; memory parameter; semi-parametric estimation; adaptive estimation;
D O I
10.3150/07-BEJ6151
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This work is intended as a contribution to the theory of 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 (Lip to a logarithm factor). The quality of the estimators is demonstrated via simulations.
引用
收藏
页码:691 / 724
页数:34
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