Surrogate data for non-stationary signals

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dc.creatorSchmitz, Andreas
dc.creatorSchreiber, Thomas
dc.date1999-04-13
dc.date.accessioned2026-07-07T02:35:43Z
dc.date.available2026-07-07T02:35:43Z
dc.descriptionStandard tests for nonlinearity reject the null hypothesis of a Gaussian linear process whenever the data is non-stationary. Thus, they are not appropriate to distinguish nonlinearity from non-stationarity. We address the problem of generating proper surrogate data corresponding to the null hypothesis of an ARMA process with slowly varying coefficients.
dc.description4 pages, 4 figures. proceeding for a poster
dc.identifierhttps://arxiv.org/abs/chao-dyn/9904023
dc.identifierhttp://arxiv.org/abs/chao-dyn/9904023
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/15708
dc.subjectChaotic Dynamics
dc.titleSurrogate data for non-stationary signals
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