Exact and approximate sum representations for the Dirichlet process 论文

2002Canadian Journal of Statistics引用 275
Bayesian Methods and Mixture ModelsStatistical Methods and InferenceStatistical Methods and Bayesian Inference

摘要

Abstract The Dirichlet process can be regarded as a random probability measure for which the authors examine various sum representations. They consider in particular the gamma process construction of Ferguson (1973) and the “stick‐breaking” construction of Sethuraman (1994). They propose a Dirichlet finite sum representation that strongly approximates the Dirichlet process. They assess the accuracy of this approximation and characterize the posterior that this new prior leads to in the context of Bayesian nonpara‐metric hierarchical models.