Multiplex Network Regression: How do relations drive interactions?

6 June 2017

Ever wondered how to apply regression to Multiplex Networks? In our preprint we introduce a new statistical method to investigate the impact of dyadic relations on complex networks generated from repeated interactions. The method is based on generalised hypergeometric ensembles (gHypEs), a class of statistical network ensembles we have developed recently.

We represent different types of known relations between system elements by weighted graphs, separated in the different layers of a multiplex network. With our method we can regress the influence of each relational layer, the independent variables, on the interaction counts, the dependent variables. Moreover, we can test the statistical significance of the relations as explanatory variables for the observed interactions.