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Journal Articles Stochastic Processes and their Applications Year : 2011

Locally stationary long memory estimation

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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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Dates and versions

hal-00408224 , version 1 (29-07-2009)
hal-00408224 , version 2 (08-04-2010)

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Cite

François Roueff, Rainer von Sachs. Locally stationary long memory estimation. Stochastic Processes and their Applications, 2011, 121 (4), pp.Pages 813-844. ⟨10.1016/j.spa.2010.12.004⟩. ⟨hal-00408224v2⟩
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