We explore the asymptotic properties of strategic models of network formation in very large populations. Specifically, we focus on (undirected) exponential random graph models. We want to recover a ...

The growing availability of network data and of scientific interest in distributed systems has led to the rapid development of statistical models of network structure. Typically, however, these are ...

We study the asymptotics for sparse exponential random graph models where the parameters may depend on the number of vertices of the graph. We obtain exact estimates for the mean and variance of the ...

Abstract: With the growth of interest in network data across fields, the Exponential Random Graph Model (ERGM) has emerged as the leading approach to the statistical analysis of network data. ERGM ...

Venture capital firms use a variety of accumulated resources to inform their investment activities, but do the rely solely on their own resources or do they employ other firms' resources to complement ...

Applying the exponential random graph model (Robins et al. 2007) to the investment data of Japanese venture capital (VC) firms, we document the relationship between VC performance and the dynamics of ...

Understanding the dynamics of internal migration is essential for promoting regional resilience and sustainable development. This study applies a weighted Exponential Random Graph Model (ERGM) to ...