http://www.cnr.it/ontology/cnr/individuo/prodotto/ID298403
A blocked Gibbs sampler for NGG-mixture models via a priori truncation (Articolo in rivista)
- Type
- Label
- A blocked Gibbs sampler for NGG-mixture models via a priori truncation (Articolo in rivista) (literal)
- Anno
- 2015-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1007/s11222-015-9549-6 (literal)
- Alternative label
Argiento R., Bianchini, I., Guglielmi, A. (2015)
A blocked Gibbs sampler for NGG-mixture models via a priori truncation
in Statistics and computing (Dordr., Online)
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Argiento R., Bianchini, I., Guglielmi, A. (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://link.springer.com/article/10.1007%2Fs11222-015-9549-6 (literal)
- Rivista
- Note
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- CNR-IMATI, CNR-IMATI, Politecnico di Milano (literal)
- Titolo
- A blocked Gibbs sampler for NGG-mixture models via a priori truncation (literal)
- Abstract
- We define a new class of random probability
measures, approximating the well-known normalized gen-
eralized gamma (NGG) process. Our new process is defined
from the representation of NGG processes as discrete mea-
sures where the weights are obtained by normalization of
the jumps of a Poisson process, and the support consists
of independent identically distributed location points, how-
ever considering only jumps larger than a threshold ?. There-
fore, the number of jumps of the new process, called ?-NGG
process, is a.s. finite. A prior distribution for ? can be elicited.
We assume such a process as the mixing measure in a mix-
ture model for density and cluster estimation, and build an
efficient Gibbs sampler scheme to simulate from the pos-
terior. Finally, we discuss applications and performance of
the model to two popular datasets, as well as comparison
with competitor algorithms, the slice sampler and a posteri-
ori truncation. (literal)
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