A Gibbs sampling scheme to the product partition model: an application to change-point problems

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dc.contributor.authorLoschi, RH
dc.contributor.authorCruz, FRB
dc.contributor.authorIglesias, PL
dc.contributor.authorArellano Valle, RB
dc.date.accessioned2024-01-10T12:37:28Z
dc.date.available2024-01-10T12:37:28Z
dc.date.issued2003
dc.description.abstractThis paper extends previous results for the classical product partition model applied to the identification of multiple change points in the means and variances of time series. Prior distributions for these two parameters and for the probability p that a change takes place at a particular period of time are considered and a new scheme based on Gibbs sampling to estimate the posterior relevances of the model is proposed. The resulting algorithm is applied to the analysis of two Brazilian stock market data. The computational experiments seem to indicate that the algorithm runs fast in common PC-like machines and it may be a useful tool for analyzing change-point problems.
dc.fechaingreso.objetodigital2024-04-11
dc.format.extent20 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1016/S0305-0548(01)00111-3
dc.identifier.eissn1873-765X
dc.identifier.issn0305-0548
dc.identifier.urihttps://doi.org/10.1016/S0305-0548(01)00111-3
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/76854
dc.identifier.wosidWOS:000179418400010
dc.information.autorucMatemática;Arellano R;S/I;58107
dc.information.autorucMatemática;Iglesias P;S/I;100265
dc.issue.numero3
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final482
dc.pagina.inicio463
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD
dc.revistaCOMPUTERS & OPERATIONS RESEARCH
dc.rightsacceso restringido
dc.subjectchange points
dc.subjectproduct partition model
dc.subjectrelevance
dc.subjectstudent-t distribution
dc.subjectYao's cohesions
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleA Gibbs sampling scheme to the product partition model: an application to change-point problems
dc.typeartículo
dc.volumen30
sipa.codpersvinculados58107
sipa.codpersvinculados100265
sipa.indexWOS
sipa.trazabilidadCarga SIPA;09-01-2024
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