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....

The asymptotic behavior in the right tail of the hazard rate function is considered to compare probability distributions. Using this tail ordering, the position of the posterior distribution with respect to the prior and the likelihood distributions is analyzed for a Bayesian location problem,...

We relate the classes of life distributions based on notions of aging with those that depend on the tail behaviour. This last classification introduces the concepts of outlier-neutral, outlier-prone and outlier-resistant distributions. We prove some results that connect IFR, IFRA, NBU and NBUE...