A Bernstein-von Mises theorem in the nonparametric right-censoring model

dc.creatorKim, Yongdai
dc.creatorLee, Jaeyong
dc.date2004-10-05
dc.date.accessioned2026-07-07T08:06:31Z
dc.date.available2026-07-07T08:06:31Z
dc.descriptionIn the recent Bayesian nonparametric literature, many examples have been reported in which Bayesian estimators and posterior distributions do not achieve the optimal convergence rate, indicating that the Bernstein-von Mises theorem does not hold. In this article, we give a positive result in this direction by showing that the Bernstein-von Mises theorem holds in survival models for a large class of prior processes neutral to the right. We also show that, for an arbitrarily given convergence rate n^{-α} with 0<α\leq 1/2, a prior process neutral to the right can be chosen so that its posterior distribution achieves the convergence rate n^{-α}.
dc.descriptionPublished by the Institute of Mathematical Statistics (http://www.imstat.org) in the Annals of Statistics (http://www.imstat.org/aos/) at http://dx.doi.org/10.1214/009053604000000526
dc.identifierhttps://arxiv.org/abs/math/0410083
dc.identifierhttp://arxiv.org/abs/math/0410083
dc.identifierAnnals of Statistics 2004, Vol. 32, No. 4, 1492-1512
dc.identifierdoi:10.1214/009053604000000526
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130631
dc.subjectStatistics Theory
dc.subject62C10 (Primary) 62G20, 62N01. (Secondary)
dc.titleA Bernstein-von Mises theorem in the nonparametric right-censoring model
dc.typetext

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