Building blocks of QGeNIe > Components of GeNIe models

An arc in a Bayesian network denotes an influence, i.e., the fact that the node at the tail of the arc influences the value (or the probability distribution over the possible values) of the node at the head of the arc.

One remark about editing models is that QGeNIe does not allow moving arcs between nodes, i.e., it is not possible to select and drag the head or the tail of an arc from one node to another. If this is what you want, the way to accomplish this task is to first delete the original arc and then create a new arc.

QGeNIe displays also arcs between nodes and submodels. An arc from a node N to a sub-model S means that at least one node in S depends on N. An arc from a sub-model S to a node N means that N depends on at least one node in S. An arc from a sub-model S1 to a sub-model S2 means that there is at least one node in S2 that depends on at least one node in S1. Arcs between sub-models can be double-headed, in which case the relations listed above is reciprocal. For example, a double-headed arrow between a node N and a sub-model S means that there is at least one node in S that depends on N and that there is at least one node in S that influences N. QGeNIe does not show arcs that are coming from the outside of the current sub-model window. Existence of arcs coming from outside of the current sub-model and ending in a node in the current sub-model is marked by a small triangle on the left-hand side of the node. Existence of arcs originating in a node in the current sub-model and ending in a higher-level sub-models is marked by a small triangle on the right-hand side of the node. These links can be followed by right-clicking on the small triangles.

Cycles in the graph, i.e., directed paths that start and end at the same point, are forbidden (unless the graph is dynamic, such as a Dynamic Bayesian Network, which is covered in a separate section). QGeNIe will not allow you to draw cyclic graphs. Please note that even though QGeNIe will enforce that the underlying graph is acyclic, you may still be able to observe cyclic graphs involving submodel nodes. This is due to the meaning assigned to arcs between submodels.