4.3 Article

Locally stationary long memory estimation

期刊

STOCHASTIC PROCESSES AND THEIR APPLICATIONS
卷 121, 期 4, 页码 813-844

出版社

ELSEVIER
DOI: 10.1016/j.spa.2010.12.004

关键词

Locally stationary process; Long memory; Semi-parametric estimation; Wavelets

资金

  1. Fondation Telecom
  2. Belgian government (Belgian Science Policy) [P6/03]
  3. Communaute francaise de Belgique [07/12-002]
  4. Academic universitaire Louvain

向作者/读者索取更多资源

There exists a wide literature on parametrically or semi-parametrically modelling strongly dependent time series using a long-memory parameter d, including more recent work on wavelet estimation. As a generalization of these latter approaches, in this work we allow the long-memory parameter d to be varying over time. We adopt a semi-parametric approach in order to avoid fitting a time-varying parametric model, such as tvARFIMA, to the observed data. We study the asymptotic behavior of a local log-regression wavelet estimator of the time-dependent d. Both simulations and a real data example complete our work on providing a fairly general approach. (C) 2010 Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.3
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据