2026-07-072026-07-07http://salesiana.dossiersoluciones.com/handle/123456789/130631In 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}.Published 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/10.1214/009053604000000526Statistics Theory62C10 (Primary) 62G20, 62N01. (Secondary)A Bernstein-von Mises theorem in the nonparametric right-censoring modeltext