Title: Multiplex Network Regression: How do relations drive interactions?,
Abstract: We introduce a statistical method to investigate the impact of dyadic
relations on complex networks generated from repeated interactions. It is based
on generalised hypergeometric ensembles, a class of statistical network
ensembles 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. To
demonstrate the power of our approach and its broad applicability, we will
present examples based on synthetic and empirical data.