Complex networks are key to describing the connected nature of the society that we live in.
This book, the second of two volumes, describes the local structure of random graph models …

Infectious disease incidence data are increasingly available at the level of the individual and
include high-resolution spatial components. Therefore, we are now better able to challenge …

These lecture notes are intended to be used for master courses, where the students have a
limited prior knowledge of special topics in probability. Therefore, we have included many of …

Real-world networks, like social networks or the internet infrastructure, have structural
properties such as large clustering coefficients that can best be described in terms of an …

This book focuses on percolation on high-dimensional lattices. We give a general
introduction to percolation, stating the main results and defining the central objects. We …

In the past decade, geometric network models have received vast attention in the literature.
These models formalize the natural idea that similar vertices are likely to connect. Because …

Networks with underlying metric spaces attract increasing research attention in network
science, statistical physics, applied mathematics, computer science, sociology, and other …

We investigate random graphs on the points of a Poisson process in d-dimensional space,
which combine scale-free degree distributions and long-range effects. Every Poisson point …

We study the propagation of susceptible-infectious-recovered (SIR) disease on random
networks with spatial structure. We consider random spatial networks (RSNs) with …

The study of real-life network modeling has become very popular in recent years. An
attractive model is the scale-free percolation model on the lattice\mathbb Z^ d Z d, d ≥ 1 d≥ …