On the small sample behavior of Dirichlet process mixture models for data supported on compact intervals

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dc.catalogadorgjm
dc.contributor.authorWehrhahn, Claudia
dc.contributor.authorJara Vallejos, Alejandro Antonio
dc.contributor.authorBarrientos, Andrés F.
dc.date.accessioned2024-06-26T20:23:37Z
dc.date.available2024-06-26T20:23:37Z
dc.date.issued2019
dc.description.abstractBayesian nonparametric models provide a general framework for flexible statistical modeling of modern complex data sets. We compare a rate-optimal and rate-suboptimal Bayesian nonparametric model for density estimation for data supported on a compact interval, by means of the analyses of simulated and real data. The results show that rate-optimal models are not uniformly better, across sample sizes, with respect to the way in which the posterior mass concentrates around a true model and that suboptimal models can outperform the optimal ones, even for relatively large sample sizes.
dc.fechaingreso.objetodigital2025-01-08
dc.fuente.origenORCID
dc.identifier.doi10.1080/03610918.2019.1568470
dc.identifier.eissn1532-4141
dc.identifier.issn0361-0918
dc.identifier.scopusid2-s2.0-85061446263
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/86873
dc.identifier.wosidWOS:000623765300004
dc.information.autorucFacultad de Matemáticas; Jara Vallejos, Alejandro Antonio; 0000-0002-2282-353X; 127927
dc.issue.numero3
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final810
dc.pagina.inicio786
dc.revistaCommunications In Statistics - Simulation And Computation
dc.rightsacceso restringido
dc.subjectDensity estimation
dc.subjectRandom Bernstein polynomials
dc.subjectMixture of beta distributions
dc.subjectBayesian nonparametrics
dc.subjectPosterior convergence rate
dc.subject.ods03 Good health and well-being
dc.subject.odspa03 Salud y bienestar
dc.titleOn the small sample behavior of Dirichlet process mixture models for data supported on compact intervals
dc.typeartículo
dc.volumen50
sipa.codpersvinculados127927
sipa.trazabilidadORCID;2024-06-24
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