Selecting dynamic graphical models with hidden variables from data (Q1861598)

The authors consider a class of hidden Markov chain models in which the hidden chain depends on some covariates. Graphical representations of the structure of such dependence are described. Different algorithms of this structure selection for observed data are discussed, based on the Bayesian approach. A numerical example is considered.