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Locally stationary long memory estimation

Abstract : There exists a wide literature on modelling strongly dependent time series using a longmemory parameter d, including more recent work on semiparametric 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 embed our approach into the framework of locally stationary processes. We show weak consistency and a central limit theorem for our log-regression wavelet estimator of the time-dependent d in a Gaussian context. Both simulations and a real data example complete our work on providing a fairly general approach.
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Preprints, Working Papers, ...
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Contributor : François Roueff <>
Submitted on : Wednesday, July 29, 2009 - 5:04:59 PM
Last modification on : Friday, July 31, 2020 - 10:44:05 AM
Long-term archiving on: : Tuesday, June 15, 2010 - 8:07:58 PM


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  • HAL Id : hal-00408224, version 1
  • ARXIV : 0907.5151


François Roueff, Rainer von Sachs. Locally stationary long memory estimation. 2009. ⟨hal-00408224v1⟩



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