Abstract
SUMMARYA class of parametric models, called splitting processes, is defined, by using de Finetti's concept of adherent mass. Such splitting processes give rise to complex mixtures of distributions. It is proved that the nonparametric Bayesian predictive procedure An, of Hill, holds exactly for a member of this class called a nested splitting process. The connection between An and the Dirichlet process is stated and proved. A multivariate version of An, based on splitting processes, is proposed.
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