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Title:

Robust Bayesian Graphical Modeling Using Dirichlet $t$ -Distributions

Document type:
Zeitschriftenaufsatz
Author(s):
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...     »
Keywords:
Bayesian inference, Dirichlet process, graphical model, Markov chain Monte Carlo, t-distribution
Dewey Decimal Classification:
510 Mathematik
Journal title:
Bayesian Analysis
Year:
2014
Journal volume:
9
Year / month:
2014-09
Quarter:
3. Quartal
Month:
Sep
Journal issue:
3
Pages contribution:
521-550
Language:
en
Fulltext / DOI:
doi:10.1214/13-ba856
WWW:
Project Euclid
Publisher:
Institute of Mathematical Statistics
E-ISSN:
1936-0975
Date of publication:
05.09.2014
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