14:30
28/05/2025 - 14:30 - ISBA C115 -
Will give a presentation on :
Abstract:
Network data across various domains (e.g. social, political, biological) are commonly observed with additional node- and/or edge- specific attributes that may explain the intensity of interactions between nodes within the network. For example, in the study of international relations, attributes such as conflict intensity and volume of trade are observed for each country pair, and it is important to understand the extent to which these covariates explain the formation of military alliances between countries (nodes). We study the model where probabilities of edge formation between any two nodes in the network are given by the sum of a linear edge-covariate term and a residual term to model the remaining heterogeneity from unobserved factors. We approach estimation of the model via profile least squares and show how it leads to a simple algorithm to estimate the linear covariate term and the residual structure that is truly latent in the presence of observed covariates. Our framework lends itself naturally to a bootstrap procedure which is used to draw inference on model parameters, such as to determine significance of the homophily parameter or covariates in explaining the underlying network structure. We illustrate the usefulness of our methodology through simulations and application to four real network datasets.