In this paper, we consider homogeneous normalized random measures with independent increments (hNRMI), a class of nonparametric priors recently introduced in the literature. Many of their distributional properties are known by now but their stick-breaking representation is missing. Here we display such a representation, which will feature dependent stick-breaking weights, and then derive explicit versions for noteworthy special cases of hNRMI. Posterior characterizations are also discussed. Finally, we devise an algorithm for slice sampling mixture models based on hNRMIs, which relies on the representation we have obtained, and implement it to analyze real data.

On the stick-breaking representation for homogeneous NRMIs

FAVARO, STEFANO;NAVA, CONSUELO RUBINA;NIPOTI, BERNARDO;PRUENSTER, Igor;
2016-01-01

Abstract

In this paper, we consider homogeneous normalized random measures with independent increments (hNRMI), a class of nonparametric priors recently introduced in the literature. Many of their distributional properties are known by now but their stick-breaking representation is missing. Here we display such a representation, which will feature dependent stick-breaking weights, and then derive explicit versions for noteworthy special cases of hNRMI. Posterior characterizations are also discussed. Finally, we devise an algorithm for slice sampling mixture models based on hNRMIs, which relies on the representation we have obtained, and implement it to analyze real data.
2016
11
697
724
http://projecteuclid.org/euclid.ba/1440594949
Bayesian Nonparametrics, generalized Dirichlet process, normalized generalized gamma process, normalized random measures with independent increments, normalized stable process, normalized inverse-Gaussian process, random probability measure, stick-breaking representation
Favaro, Stefano; Lijoi, Antonio; Nava, Consuelo; Nipoti, Bernardo; Pruenster, Igor; Teh, Yee Whye
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1591193
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