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  • Negative Binomial Process Count and Mixture Modeling - arXiv. org
    Abstract—The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process A A gamma process is employed to model the rate measure of a Poisson process, whose normalization provides a random probability
  • r - Negative Binomial Process - Cross Validated
    Several stochastic processes lead to marginal counts having a Negative Binomial (NB) distribution and can therefore be called NB processes
  • Augment-and-Conquer Negative Binomial Processes - NeurIPS
    By developing data augmentation methods unique to the negative binomial (NB) distribution, we unite seemingly disjoint count and mixture models under the NB process framework We develop fundamental properties of the models and derive efficient Gibbs sampling inference
  • Negative binomial processes | Journal of Applied Probability . . .
    This paper is concerned with negative binomial processes which are essentially mixed Poisson processes whose intensity parameter is given by the sum of squares of a finite number of independently and identically distributed Gaussian processes
  • Negative Binomial Autoregressive Process - hal. science
    We show that the NBAR process belongs to the class of Compound AutoRegressive (CaR) processes, 2 which facilitates: i) the analysis of stationarity; ii) the Laplace transform based GMM estimation; iii) the nonlinear probabilistic forecasting at any horizon
  • How to derive Negative Binomial process from Poisson process?
    We know that $Negative Binomial(r, p)\approx Poisson(\lambda)$ if $r(1-p)=\lambda$, and further that $r$ is large and $p$ is close to $1$ So if a Poisson process has rate $\lambda$ , then the negative binomial process that models arrivals in an interval of length $t$ as $Negative Binomial(rt, p)$ will be approximately the same as the poisson
  • Negative Binomial Process Count and Mixture Modeling
    It is shown that with augmentation and normalization, the NB process and gamma-NB process can be reduced to the Dirichlet process and hierarchical Dirichlet process, respectively These relationships highlight theoretical, structural and computational advantages of the NB process
  • Negative Binomial Process Count and Mixture Modeling
    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 lead …


















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