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Titel:

Robust Bayesian Graphical Modeling Using Dirichlet $t$ -Distributions

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Finegold, Michael; Drton, Mathias
Abstract:
Bayesian graphical modeling provides an appealing way to obtain uncertainty estimates when inferring network structures, and much recent progress has been made for Gaussian models. For more robust inferences, it is natural to consider extensions to t-distribution models. We argue that the classical multivariate t-distribution, defined using a single latent Gamma random variable to rescale a Gaussian random vector, is of little use in more highly multivariate settings, and propose other, more fle...     »
Stichworte:
Bayesian inference, Dirichlet process, graphical model, Markov chain Monte Carlo, t-distribution
Dewey Dezimalklassifikation:
510 Mathematik
Zeitschriftentitel:
Bayesian Analysis
Jahr:
2014
Band / Volume:
9
Jahr / Monat:
2014-09
Quartal:
3. Quartal
Monat:
Sep
Heft / Issue:
3
Seitenangaben Beitrag:
521-550
Sprache:
en
Volltext / DOI:
doi:10.1214/13-ba856
WWW:
Project Euclid
Verlag / Institution:
Institute of Mathematical Statistics
E-ISSN:
1936-0975
Publikationsdatum:
05.09.2014
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