Surviving fully Bayesian nonparametric regression models

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dc.catalogadorgjm
dc.contributor.authorHanson, Timothy E.
dc.contributor.authorJara Vallejos, Alejandro Antonio
dc.date.accessioned2024-06-28T13:11:47Z
dc.date.available2024-06-28T13:11:47Z
dc.date.issued2013
dc.description.abstractThis chapter compares two Bayesian nonparametric models that generalize the accelerated failure time model, based on recent work on probability models for predictor-dependent probability distributions. It begins by reviewing commonly used semiparametric survival models. It then discusses the Bayesian nonparametric priors used in the generalizations of the accelerated failure time (AFT) model. Next, the two generalizations of the accelerated failure time model are introduced and compared by means of real-life data analyses. The models correspond to generalizations of AFT models based on dependent extensions of the Dirichlet process (DP) and Polya tree (PT) priors. Advantages of the induced survival regression models include ease of interpretability and computational tractability.
dc.description.funderFONDECYT
dc.fuente.origenORCID
dc.identifier.citationHanson, T, Jara, A. Surviving fully Bayesian nonparametric regression models. In: Damien, P., Dellaportas P., Polson, N., Stephens, D.,editors. Bayesian Theory and Applications. Oxford, UK: Oxford University Press; 2013. p. 593-615.
dc.identifier.isbn978-0199695607
dc.identifier.urihttps://academic.oup.com/book/12043/chapter/161412127
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/86902
dc.information.autorucFacultad de Matemáticas; Jara Vallejos, Alejandro Antonio; 0000-0002-2282-353X; 127927
dc.language.isoen
dc.lugar.publicacionOxford, UK
dc.nota.accesocontenido parcial
dc.pagina.final615
dc.pagina.inicio593
dc.publisherOxford University Press
dc.relation.ispartofBayesian Theory and Applications
dc.rightsacceso restringido
dc.subjectBayesian nonparametric models
dc.subjectAccelerated failure time model
dc.subjectSemiparametric survival models
dc.subjectDirichlet process
dc.subjectPolya tree
dc.subjectInduced survival regression models
dc.titleSurviving fully Bayesian nonparametric regression models
dc.typecapítulo de libro
sipa.codpersvinculados127927
sipa.trazabilidadORCID;2024-06-24
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