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On Consistency of Nonparametric Normal Mixtures for Bayesian Density Estimation
2005
Journal of the American Statistical Association
The past decade has seen a remarkable development in the area of Bayesian nonparametric inference from both theoretical and applied perspectives. As for the latter, the celebrated Dirichlet process has been successfully exploited within Bayesian mixture models, leading to many interesting applications. As for the former, some new discrete nonparametric priors have been recently proposed in the literature that have natural use as alternatives to the Dirichlet process in a Bayesian hierarchical
doi:10.1198/016214505000000358
fatcat:6nz2nwq55jcexcvex2kbvcdgde