Using reinforced processes related to beta-Stacy process and generalized Pólya 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. © 2009 Elsevier B.V.

A Bayesian nonparametric estimator of a multivariate survival function

MULIERE, PIETRO;
2009

Abstract

Using reinforced processes related to beta-Stacy process and generalized Pólya 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. © 2009 Elsevier B.V.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/54894
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