Community detection in directed acyclic graphs

Community detection in directed acyclic graphs

Some temporal networks, most notably citation networks, are naturally represented as directed acyclic graphs (DAGs). To detect communities in DAGs, we propose a modularity for DAGs by defining an appropriate null model (i.e., randomized network) respecting the order of nodes. We implement a spectral method to approximately maximize the proposed modularity measure and test the method on citation...

Generic Directed Acyclic Graphs

Copula directed acyclic graphs

We present a new methodology for selecting a Bayesian network for continuous data outside the widely used class of multivariate normal distributions. The use of bivariate copula densities to model connections between pairs of nodes in the network brings in flexibility in the choice of the distribution. Cand D-vines play a central role in dealing with the high-dimensional aspect of the data, due...

Seepage in directed acyclic graphs

In the firefighting and the graph searching problems, a contaminate spreads relatively quickly. We introduce a new model, on directed acyclic graphs, in which the contamination spreads slowly. The model was inspired by the efforts to stem the lava flow from the Eldfell volcano in ∗ Partially supported by grants from NSERC. 92 N.E. CLARKE ET AL. Iceland. The contamination starts at a source, onl...

Use of Directed Acyclic Graphs

This supplement describes how counterfactual theory is used to define causal effects and the conditions in which observed data can be used to estimate counterfactual-based causal effects. Basic definitions and language used in causal graph theory are then presented. The graphical separation rules linking the causal assumptions encoded in a diagram to the statistical relations implied by the cau...