DIRICHLET PRIOR SIEVES IN FINITE NORMAL MIXTURES

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Generalized spatial dirichlet process models (2007, methodology): “almost sure continuity of the paths of a univariate spatial process, as defined in Kent (1989) or Banerjee et al.”
Generalized weighted Chinese restaurant processes for species sampling mixture models (2003, methodology): “In case P is a DP(αH) process, one can use the methods discussed in Gelfand and Kottas (2002), Ishwaran and Zarepour (2002a) and Muliere and Tardella (1998).”
Hybrid Dirichlet mixture models for functional data (2009, background): “As a prior on the space of DFs on Rm, the probability measure that almost surely selects distributions of the form (6) is usually called a (finite dimensional) Dirichlet prior ( Ishwaran and Zarepour, 2002 ).”
The Nested Dirichlet Process (2008, methodology): “…a truncation approximation to the stick-breaking representation of the process and then resort to methods for computation in finite-mixture models (Ishwaran and Zarepour 2002; Ishwaran and James 2001); and (c) use reversible-jump Markov chain Monte Carlo (RJMCMC) algorithms for finite mixtures…”
A Sticky HDP-HMM With Application to Speaker Diarization (2009, methodology): “One possibility is to consider split-merge algorithms similar to those developed in Jain and Neal (2004) for the DP mixture model.”