Priors for Random Count Matrices Derived from a Family of Negative Binomial Processes

@inproceedings{Zhou2014PriorsFR,
  title={Priors for Random Count Matrices Derived from a Family of Negative Binomial Processes},
  author={Mingyuan Zhou and Oscar Hernan Madrid Padilla and James G. Scott},
  year={2014}
}
ABSTRACTWe define a family of probability distributions for random count matrices with a potentially unbounded number of rows and columns. The three distributions we consider are derived from the gamma-Poisson, gamma-negative binomial, and beta-negative binomial processes, which we refer to generically as a family of negative-binomial processes. Because the models lead to closed-form update equations within the context of a Gibbs sampler, they are natural candidates for nonparametric Bayesian… CONTINUE READING

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