matthiasm@8: function [int, persist, transient] = compute_interface_nodes(intra, inter)
matthiasm@8: % COMPUTE_INTERFACE_NODES Find the nodes in a DBN that represent a sufficient statistic
matthiasm@8: % [int, persist, transient] = compute_interface_nodes(intra, inter)
matthiasm@8: %
matthiasm@8: % The interface nodes are all those that has an incoming temporal arc,
matthiasm@8: % or which have a child which has an incoming temporal arc,
matthiasm@8: % where a temporal arc means one coming from the previous slice.
matthiasm@8: % (The parents of nodes with incoming temporal arcs are needed
matthiasm@8: % because moralization will bring them into the clique.)
matthiasm@8: %
matthiasm@8: % The persisent nodes are all those that have one or more incoming temporal arc.
matthiasm@8: % The transient nodes are all the non-persistent.
matthiasm@8: %
matthiasm@8: % See U. Kjaerulff, "dHugin: A computational system for dynamic
matthiasm@8: % time-sliced Bayesian networks", Intl. J. Forecasting (11) 89-111, 1995
matthiasm@8: 
matthiasm@8: n = length(intra);
matthiasm@8: int = [];
matthiasm@8: persist = [];
matthiasm@8: for u=1:n
matthiasm@8:   if any(inter(:,u))
matthiasm@8:     int = [int u];
matthiasm@8:     persist = [persist u];
matthiasm@8:   end
matthiasm@8:   if any(inter(:, children(intra, u)))
matthiasm@8:     int = [int u];
matthiasm@8:   end
matthiasm@8: end
matthiasm@8: int = unique(int);
matthiasm@8: persist = unique(persist);
matthiasm@8: transient = mysetdiff(1:n, persist);