Convergence of Dirichlet Measures Arising in Context of Bayesian Analysis of Competing Risks Models

In this paper, we study the weak convergence of Dirichlet measures on the class constituted by vectors of subprobability measures such that the sum of its components is a probability measure on a complete separable metric space. This vectorial class of subprobabilities appears in the context of the competing risks theory and the Dirichlet measures are considered as a prior family in a Bayesian approach. The weak convergence results are derived and used to study the convergence of the Bayes estimators of certain parameters in competing risks models.