Probabilistic Foundations of Statistical Network Analysis (Chapman & Hall/CRC Monographs on Statistics and Applied Probability Book 157) 1st Edition by Harry Crane (PDF)

Description

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 author’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. Harry Crane is Associate Professor and Co-Director of the Graduate Program in Statistics and Biostatistics and an Associate Member of the Graduate Faculty in Philosophy at Rutgers University. Professor Crane’s research interests cover a range of mathematical and applied topics in network science, probability theory, statistical inference, and mathematical logic. In addition to his technical work on edge and relational exchangeability, relative exchangeability, and graph-valued Markov processes, Prof. Crane’s methods have been applied to domain-specific cybersecurity and counterterrorism problems at the Foreign Policy Research Institute and RAND’s Project AIR FORCE.

User’s Reviews

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐Book is a bit intimidating when you first page through as Crane goes into detail about much of the math involved with network analysis.But, as you read you’ll find the explanations are well thought out and thorough. I took copious notes throughout my reading and I must say this is one of the best books I’ve read on the subject.I recommend this book to anyone who has a strong surface level understanding but wants to read something that’s much more in depth.

⭐Excellent overview of some probabilistic models on graphs

⭐If you would like to practice network analysis by dynamical way, but not stagnate with statics, then this is the book for you. Alternatively, I leant a lot by following Harry Crane’s twitter feed. Highly recommend for anybody who prefer complex data analysis over classical statistics.

⭐This is a very nice book that cleanly explains how to use graphical networks and probabilistic tools to solve practical problems. Technical stuffs are nicely written.

⭐This is a fun book I recommend for any reader interested in learning about statistical tools for networks. Crane has an entertaining writing style that makes this one of the more enjoyable books you will find in statistics or probability.

⭐Insightful and well-written. A book that should litter the shelves of any mathematician, statistician, and data scientist worth their salt

⭐I was expecting more of a practical as opposed to a theoretical book. The concepts are hard to grasp.

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