Bayesian generalized product partition model

@inproceedings{Park2007BayesianGP,
  title={Bayesian generalized product partition model},
  author={Ju-Hyun Park},
  year={2007}
}
Starting with a carefully formulated Dirichlet process (DP) mixture model, we derive a generalized product partition model (GPPM) in which the partition process is predictor-dependent. The GPPM generalizes DP clustering to relax the exchangeability assumption through the incorporation of predictors, resulting in a generalized Pólya urn scheme. In addition, the GPPM can be used for formulating flexible semiparametric Bayes models for conditional distribution estimation, bypassing the need for… CONTINUE READING