Autorentext
A. D. Barbour is Emeritus Professor of Mathematics at the University of Zürich. He is also Honorary Professorial Fellow in Mathematics at the University of Melbourne and Fellow of the Institute of Mathematical Statistics. He previously co-authored the monographs 'Poisson Approximation' (1992) and 'Logarithmic Combinatorial Structures: A Probabilistic Approach' (2003). Gesine Reinert is Professor of Statistics and Fellow of Keble College at the University of Oxford. She is also Fellow of the Institute of Mathematical Statistics. Her research spans applied probability, network science, computational biology, and theoretical foundations of machine learning.

Klappentext
This text explains how to build and analyze plausible models for random networks, and how to use statistics for validating such models, for detecting unusual features in the data, and for making predictions. It uniquely balances mathematical rigour with accessibility, introducing readers to a topic with far-reaching applications.