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Likelihood-based inference for probabilistic graphical models: Some preliminary results

By Marco E. G. V. Cattaneo


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.

Year: 2010
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