On a state-space modelling for functional data

Ortega-Moreno, Mónica; Escabias Machuca, Manuel

doi:https://doi.org/10.1007/s00180-007-0049-9

dc.contributor.author	Ortega-Moreno, Mónica
dc.contributor.author	Escabias Machuca, Manuel
dc.date.accessioned	2022-03-15T11:38:54Z
dc.date.available	2022-03-15T11:38:54Z
dc.date.issued	2007-03-17
dc.identifier.citation	Ortega-Moreno, M., Escabias, M. On a state-space modelling for functional data. Computational Statistics 22, 429–438 (2007). https://doi.org/10.1007/s00180-007-0049-9	es_ES
dc.identifier.uri	http://hdl.handle.net/10481/73446
dc.description.abstract	The objective of this paper is to derive a state-space model for several continuous-time processes, by applying the Karhunen–Loève expansion, and then to apply the Kalman filter equations. The accuracy of the models on the basis of deterministic or random inputs is studied by means of simulation on two well-known processes.	es_ES
dc.description.sponsorship	Project MTM2004-5992 of Dirección General de Investigación del Ministerio de Ciencia y Tecnología of Spain and the Research Group FQM307 financed by III-PAI of Conserjería de Educación y Ciencia de la Junta de Andalucía	es_ES
dc.language.iso	eng	es_ES
dc.publisher	Springer	es_ES
dc.rights	Atribución-SinDerivadas 3.0 España	*
dc.rights.uri	http://creativecommons.org/licenses/by-nd/3.0/es/	*
dc.subject	Karhunen–Loève expansion	es_ES
dc.subject	State-space models	es_ES
dc.subject	Kalman filter	es_ES
dc.subject	CAR(1)	es_ES
dc.subject	Random binary signal	es_ES
dc.title	On a state-space modelling for functional data	es_ES
dc.type	journal article	es_ES
dc.rights.accessRights	embargoed access	es_ES
dc.identifier.doi	https://doi.org/10.1007/s00180-007-0049-9
dc.type.hasVersion	SMUR	es_ES

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