Conjugacy properties of time-evolving Dirichlet and gamma random measures

30 Aug 2016 Papaspiliopoulos Omiros Ruggiero Matteo Spanò Dario

We extend classic characterisations of posterior distributions under Dirichlet process and gamma random measures priors to a dynamic framework. We consider the problem of learning, from indirect observations, two families of time-dependent processes of interest in Bayesian nonparametrics: the first is a dependent Dirichlet process driven by a Fleming-Viot model, and the data are random samples from the process state at discrete times; the second is a collection of dependent gamma random measures driven by a Dawson-Watanabe model, and the data are collected according to a Poisson point process with intensity given by the process state at discrete times... (read more)

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Categories


  • STATISTICS THEORY
  • PROBABILITY
  • COMPUTATION
  • STATISTICS THEORY