  In 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^{-\alpha} with
0<\alpha \leq 1/2, a prior process neutral to the right can be chosen so that
its posterior distribution achieves the convergence rate n^{-\alpha}.
