A flexible two-piece normal dynamic linear model

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dc.contributor.authorAliverti, Emanuele
dc.contributor.authorArellano-Valle, Reinaldo B.
dc.contributor.authorKahrari, Fereshteh
dc.contributor.authorScarpa, Bruno
dc.date.accessioned2025-01-20T20:14:21Z
dc.date.available2025-01-20T20:14:21Z
dc.date.issued2023
dc.description.abstractWe construct a flexible dynamic linear model for the analysis and prediction of multivariate time series, assuming a two-piece normal initial distribution for the state vector. We derive a novel Kalman filter for this model, obtaining a two components mixture as predictive and filtering distributions. In order to estimate the covariance of the error sequences, we develop a Gibbs-sampling algorithm to perform Bayesian inference. The proposed approach is validated and compared with a Gaussian dynamic linear model in simulations and on a real data set.
dc.description.funderUniversita degli Studi di Padova within the CRUI-CARE Agreement
dc.fuente.origenWOS
dc.identifier.doi10.1007/s00180-023-01355-3
dc.identifier.eissn1613-9658
dc.identifier.issn0943-4062
dc.identifier.urihttps://doi.org/10.1007/s00180-023-01355-3
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/92190
dc.identifier.wosidWOS:000978094600002
dc.issue.numero4
dc.language.isoen
dc.pagina.final2096
dc.pagina.inicio2075
dc.revistaComputational statistics
dc.rightsacceso restringido
dc.subjectTwo-piece normal distribution
dc.subjectSkew-normal distribution
dc.subjectBayesian inference
dc.subjectKalman filter
dc.subjectFFBS algorithm
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleA flexible two-piece normal dynamic linear model
dc.typeartículo
dc.volumen38
sipa.indexWOS
sipa.trazabilidadWOS;2025-01-12
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