Analysis of irregularly spaced time series

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dc.contributor.advisorPalma M., Wilfredo
dc.contributor.authorOjeda Echeverri, César Andrés
dc.contributor.otherPontificia Universidad Católica de Chile. Facultad de Matemáticas
dc.date.accessioned2020-11-18T16:02:31Z
dc.date.available2020-11-18T16:02:31Z
dc.date.issued2019
dc.descriptionTesis (Doctor en Estadística)--Pontificia Universidad Católica de Chile, 2019
dc.description.abstractIn this thesis, we propose novel stationary time series models that can be used when the observations are taken on irregularly spaced times. First, we present a model with a firstorder moving average structure, and then we generalized it to consider an autoregressive component. We called the first model irregularly spaced first-order moving average and the second one irregularly spaced first-order autoregressive moving average. Their definitions and properties are established. We present their state-space representations and their one-step linear predictors. The behavior of the maximum likelihood estimator is studied through Monte Carlo experiments. Illustrations are presented with real and simulated data.
dc.format.extent65 páginas
dc.identifier.doi10.7764/tesisUC/MAT/48405
dc.identifier.urihttps://doi.org/10.7764/tesisUC/MAT/48405
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/48405
dc.information.autorucFacultad de Matemáticas ; Palma M., Wilfredo ; S/I ; 100091
dc.information.autorucFacultad de Matemáticas ; Ojeda Echeverri, César Andrés ; S/I ; 250660
dc.language.isoen
dc.nota.accesoContenido completo
dc.rightsacceso abierto
dc.subject.otherModelos matemáticoses_ES
dc.titleAnalysis of irregularly spaced time serieses_ES
dc.typetesis doctoral
sipa.codpersvinculados100091
sipa.codpersvinculados250660
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