![]() ![]() The book concludes by featuring chapters on network flows, dynamic networks, and networked experiments. ![]() Network processes, both static and dynamic are addressed in the subsequent chapters. This is followed by a special case of network modeling wherein the network topology must be inferred. The book then examines mathematical and statistical network modeling. Next, it addresses visualization and characterization of networks. The book begins by covering tools for the manipulation of network data. The material in this book is organized to flow from descriptive statistical methods to topics centered on modeling and inference with networks, with the latter separated into two sub-areas, corresponding first to the modeling and inference of networks themselves, and then, to processes on networks. The new edition of this book includes an overhaul to recent changes in igraph. The central package is igraph, which provides extensive capabilities for studying network graphs in R. It has been fully revised and can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The new edition of this book provides an easily accessible introduction to the statistical analysis of network data using R.
0 Comments
Leave a Reply. |