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.
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.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
Produktdetails
Cambridge Series in Statistical and Probabilistic Mathematics
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.
Inhaltsangabe
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.
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.
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