Exponential Random Graph Models (ERGMs) are a method of social network analysis for building complex social network structures (Robins et al., 2007). The model assumes that the emergence of a ...

To capture the heterozygosity of vertex degrees of networks and understand their distributions, a class of random graph models parameterized by the strengths of vertices is proposed. These models have ...

Inspired by a huge amount of empirical study of real world networks such as the Internet, the Web, as well as various social and biological networks, researchers have in recent years developed several ...

Donald D. Koban, A Static Bernoulli Random-Graph Model for the Analysis of Covert Networks, Military Operations Research, Vol. 20, No. 4 (2015), pp. 39-47 ...

Incorporating structural features into random-graph calculations should bring theoretical models describing the properties and behaviour of complex networks closer to real-world systems.

Given these three concerns, we employ the exponential random graph model (ERGM) developed in network science literature (e.g. Snijders 2002, Robins et al. 2007), which can simultaneously account for ...

This lecture course is devoted to the study of random geometrical objects and structures. Among the most prominent models are random polytopes, random tessellations, particle processes and random ...

Within theoretical computer science, it is commonly referred to as a planted partition model [31], and in mathematical contexts, it is acknowledged as an inhomogeneous random graph model [32]. This ...

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 ...