Likelihood-based inference for probabilistic graphical models: Some preliminary results
Marco Cattaneo · 2010
A method for calculating some profile likelihood inferences in probabilistic graphical models is presented and applied to the problem of classification. It can also be interpreted as a method for obtaining inferences from hierarchical networks, a kind of imprecise probabilistic graphical models. 1