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Bayesian Data Analysis, Third Edition, 3rd Edition by Donald B. Rubin, Aki Vehtari, David B. Dunson, Hal S. Stern, John B. Carlin, Andrew Gelman

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Chapter 23

Dirichlet process models

The Dirichlet process is an infinite-dimensional generalization of the Dirichlet distribution that can be used to set a prior on unknown distributions. Furthermore, these unknown densities can be used to extend finite component mixture models to infinite component mixture models.

23.1   Bayesian histograms

We start in this section and the next with the relatively simple setting in which yi f and the goal is to ...

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