Probabilistic foundations of statistical network analysis
Crane, Harry
creator
Network analysis
text
Boca Raton
CRC Press
2018
monographic
| 0
xx, 236 p. Includes bibliographical references and index
Probabilistic Foundations of Statistical Network Analysis presents a fresh and insightful perspective on the fundamental tenets and major challenges of modern network analysis. Its lucid exposition provides necessary background for understanding the essential ideas behind exchangeable and dynamic network models, network sampling, and network statistics such as sparsity and power law, all of which play a central role in contemporary data science and machine learning applications. The book rewards readers with a clear and intuitive understanding of the subtle interplay between basic principles of statistical inference, empirical properties of network data, and technical concepts from probability theory. Its mathematically rigorous, yet non-technical, exposition makes the book accessible to professional data scientists, statisticians, and computer scientists as well as practitioners and researchers in substantive fields. Newcomers and non-quantitative researchers will find its conceptual approach invaluable for developing intuition about technical ideas from statistics and probability, while experts and graduate students will find the book a handy reference for a wide range of new topics, including edge exchangeability, relative exchangeability, graphon and graphex models, and graph-valued Levy process and rewiring models for dynamic networks. The authorâ€™s incisive commentary supplements these core concepts, challenging the reader to push beyond the current limitations of this emerging discipline. With an approachable exposition and more than 50 open research problems and exercises with solutions, this book is ideal for advanced undergraduate and graduate students interested in modern network analysis, data science, machine learning, and statistics.
https://www.crcpress.com/Probabilistic-Foundations-of-Statistical-Network-Analysis/Crane/p/book/9781138630154
Table of Contents
Dedication
Preface
Acknowledgements
1. Orientation
2. Binary relational data
3. Network sampling
4. Generative models
5. Statistical modeling paradigm
6. Vertex exchangeable models
7. Getting beyond graphons
8. Relatively exchangeable models
9. Edge exchangeable models
10. Relationally exchangeable models
11. Dynamic network models
System analysis
Mathematical models
003 C7P7
Monographs on statistics and applied probability:157
9781138630154
190509