A Bayesian nonparametric estimator of a multivariate survival function

Using reinforced processes related to beta-Stacy process and generalized Pَlya urn scheme jointly with a structure assumption about dependence, a Bayesian nonparametric prior and a predictive estimator for a multivariate survival function are provided. This estimator can be computed through an easy implementation of a Gibbs sampler algorithm. Moreover consistency of the estimator is studied.