A Predictive View of Bayesian Clustering

  title={A Predictive View of Bayesian Clustering},
  author={Fernando A. Quintana},
This work considers probability models for partitions of a set of n elements using a predictive approach, i.e., models that are specified in terms of the conditional probability of either joining an already existing cluster or forming a new one. The inherent structure can be motivated by resorting to hierarchical models of either parametric or nonparametric nature. Parametric examples include the product partition models (PPMs) and the model-based approach of Dasgupta and Raftery (1998), while… CONTINUE READING

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Publications referenced by this paper.
Showing 1-10 of 62 references

Detecting Features in Spatial Point Processes With Clutter via Model-Based Clustering

A. Dasgupta, A. E. Raftery
Journal of the American Statistical Association • 1998
View 17 Excerpts
Highly Influenced

Bayesian Clustering and Product Partition Models, Journal of The Royal Statistical Society Series B 65: 557–574

F. A. Quintana, P. L. Iglesias
35 • 2003
View 20 Excerpts
Highly Influenced

Nonparametric hierarchical Bayes via sequential imputations

J. S. Liu
The Annals of Statistics • 1996
View 7 Excerpts
Highly Influenced

Methods and applications of linear models: Regression and the analysis of variance

R. R. Hocking
View 7 Excerpts
Highly Influenced

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