Sensitivity to hyperprior parameters in Gaussian Bayesian networks
نویسندگان
چکیده
منابع مشابه
Sensitivity to hyperprior parameters in Gaussian Bayesian networks
Bayesian networks (BNs) have become an essential tool for reasoning under uncertainty in complex models. In particular, the subclass of Gaussian Bayesian networks (GBNs) can be used to model continuous variables with Gaussian distributions. Here we focus on the task of learning GBNs from data. Factorization of the multivariate Gaussian joint density according to a directed acyclic graph (DAG) p...
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ژورنال
عنوان ژورنال: Journal of Multivariate Analysis
سال: 2014
ISSN: 0047-259X
DOI: 10.1016/j.jmva.2013.10.022