Negative Binomial Process Count and Mixture Modeling

@article{Zhou2013NegativeBP,
  title={Negative Binomial Process Count and Mixture Modeling},
  author={Mingyuan Zhou and Lawrence Carin},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2013},
  volume={37},
  pages={307-320}
}
The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process. A gamma process is employed to model the rate measure of a Poisson process, whose normalization provides a random probability measure for mixture modeling and whose marginalization leads to an NB process for count modeling. A draw from the NB process consists of a Poisson distributed finite number of distinct atoms, each of which is associated with a logarithmic distributed number… CONTINUE READING
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