Random Graphs and Complex Networks - Graphs and Complex Networks: Series Number

This classroom-tested text is the definitive introduction to the mathematics of network science, featuring examples and numerous exercises.

List of contents

Preface; Course outline; 1. Introduction; Part I. Preliminaries: 2. Probabilistics methods; 3. Branching processes; Part II. Basic Models: 4. Phase transition for the Erdos-Renyi random graph; 5. Erdos-Renyi random graph revisited; Part III. Models for Complex Networks: 6. Generalized random graphs; 7. Configuration model; 8. Preferential attachment models; Appendix; Glossary; References; Index.

About the author

Remco van der Hofstad is Full Professor of Probability at Eindhoven University of Technology and Acting Scientific Director of the European Institute for Statistics, Probability, Stochastic Operations Research and their Applications (Eurandom). He has authored over 100 research articles and has taught courses on random graphs at over ten institutions. He received the 2003 Prix Henri Poincaré (jointly with Gordon Slade) and the 2007 Rollo Davidson Prize, and he is a laureate of the 2003 Innovative Research VIDI Scheme and the 2008 Innovative Research VICI Scheme.

Summary

Network science is one of the fastest growing areas in science and business. This classroom-tested, self-contained book is designed for master's-level courses and provides a rigorous treatment of random graph models for networks, featuring many examples of real-world networks for motivation and numerous exercises to build intuition and experience.

Product details

• Authors: Remco Van Der Hofstad, Remco Van Der (Technische Universiteit Ei Hofstad, Remco van der (Technische Universiteit Eindhoven Hofstad
• Publisher: Cambridge University Press ELT
• Languages: English
• Product format: Hardback
• Released: 22.12.2016
• EAN: 9781107172876
• ISBN: 978-1-107-17287-6
• No. of pages: 236
• Series: Cambridge Series in Statistical and Probabilistic Mathematics; Cambridge Series in Statistica; Cambridge Series in Statistical and Probabilistic Mathematics; Cambridge Statistical and Prob
• Subject: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics