Publication:
Independent component analysis for time series

Simple item page
dc.contributor.advisorGarcía Ferrer, Antonio
dc.contributor.advisorPeña, Daniel
dc.contributor.authorGonzález Prieto, Ester
dc.contributor.departamentoUC3M. Departamento de Estadísticaes
dc.date.accessioned2011-08-01T17:21:26Z
dc.date.available2011-08-01T17:21:26Z
dc.date.issued2011-05
dc.date.submitted2011-07-15
dc.description.abstractEl objetivo de esta tesis es aplicar el análisis de componentes independientes (ICA) sobre datos multivariantes de series temporales. También, se propone un nuevo procedimiento para predecir un vector de series temporales a partir de un número reducido de componentes independientes
dc.description.abstractThe aim of this thesis is to analyze the performance of independent component analysis (ICA) when it is applied to a vector of non-Gaussian time series in order to find an "interesting" representation of the observations. First, we give an introduction to the ICA methodology and how it performs on estimating a set of non-Gaussian and statistically independent latent factors. Second, we review some basic ideas of multivariate time series analysis, paying special attention to well known dimension reduction techniques previously proposed in the literature. Third, we give an overview of the existing research that links ICA and time series data. Finally we outline the thesis
dc.description.sponsorshipSEJ2006-04957
dc.description.sponsorshipS2007-HUM-0413
dc.description.sponsorshipSEJ2007-64500
dc.description.sponsorshipECO2009-10287
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10016/11958
dc.language.isoeng
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaEstadística
dc.subject.otherAnálisis de series temporales
dc.subject.otherAnálisis multivariante
dc.subject.otherPrevisión
dc.titleIndependent component analysis for time series
dc.typedoctoral thesis*
dc.type.reviewPeerReviewed
dspace.entity.typePublication
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ester_gonzalez_tesis.pdf
Size:
940.65 KB
Format:
Adobe Portable Document Format
Download
Collections
Tesis Doctorales