Recently the class of normalized random measures with independent increments, which contains the Dirichlet process as a particular case, has been introduced. Here a new technique for deriving moments of these random probability measures is proposed. It is shown that, a priori, most of the appealing properties featured by the Dirichlet process are preserved. When passing to posterior computations, we obtain a characterization of the Dirichlet process as the only conjugate member of the whole class of normalized random measures with independent increments.

Conjugacy as a distinctive feature of the Dirichlet process

PRUENSTER, Igor
2006-01-01

Abstract

Recently the class of normalized random measures with independent increments, which contains the Dirichlet process as a particular case, has been introduced. Here a new technique for deriving moments of these random probability measures is proposed. It is shown that, a priori, most of the appealing properties featured by the Dirichlet process are preserved. When passing to posterior computations, we obtain a characterization of the Dirichlet process as the only conjugate member of the whole class of normalized random measures with independent increments.
2006
33
105
120
http://www3.interscience.wiley.com/journal/118520740/home
Bayesian non-parametrics; conjugacy; Dirichlet process; increasing Levy process; normalized random measure with independent increments; predictive distribution
L.F. JAMES; A. LIJOI; I. PRUENSTER
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/8535
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