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arXiv · 0907.5151

Locally stationary long memory estimation

François Roueff·Rainer Von Sachs
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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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François Roueff, Rainer Von Sachs. 2009-07-29. Locally stationary long memory estimation. https://arxiv.org/abs/0907.5151

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