Nonparametric modeling and spatiotemporal dynamical systems

dc.creatorAbel, M.
dc.date2002-02-26
dc.date2002-08-14
dc.date.accessioned2026-07-07T05:33:57Z
dc.date.available2026-07-07T05:33:57Z
dc.descriptionIn this article, it is described how to use statistical data analysis to obtain models directly from data. The focus is put on finding nonlinearities within a generalized additive model. These models are found by the means of backfitting algorithms or more general versions, like the alternating conditional expectation value method. The method is illustrated by numerically generated data. As an application the example of vortex ripple dynamics, a highly complex fluid-granular system is treated.
dc.description20 pages, 11 figures
dc.identifierhttps://arxiv.org/abs/nlin/0202058
dc.identifierhttp://arxiv.org/abs/nlin/0202058
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/80183
dc.subjectPattern Formation and Solitons
dc.subjectChaotic Dynamics
dc.titleNonparametric modeling and spatiotemporal dynamical systems
dc.typetext

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