Polya Trees and Random Distributions 论文
1992The Annals of Statistics引用 226
Bayesian Methods and Mixture ModelsStochastic processes and statistical mechanicsAlgorithms and Data Compression
摘要
Trees of Polya urns are used to generate sequences of exchangeable random variables. By a theorem of de Finetti each such sequence is a mixture of independent, identically distributed variables and the mixing measure can be viewed as a prior on distribution functions. The collection of these Polya tree priors forms a convenient conjugate family which was mentioned by Ferguson and includes the Dirichlet processes of Ferguson. Unlike Dirichlet processes, Polya tree priors can assign probability 1 to the class of continuous distributions. This property and a few others are investigated.