The new edition of this book provides an easily accessible
introduction to the statistical analysis of network data using 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
central package is igraph, which provides extensive capabilities for
studying network graphs in R. The new edition of this book includes an
overhaul to recent changes in igraph. 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 book begins by covering tools for the manipulation of
network data. Next, it addresses visualizationand characterization of
networks. The book then examines mathematical and statistical network
modeling. This is followed by a special case of network modeling
wherein the network topology must be inferred. Network processes, both
static and dynamic are addressed in the subsequent chapters. The book
concludes by featuring chapters on network flows, dynamic networks,
and networked experiments. Statistical Analysis of Network Data with
R, 2nd Ed. has been written at a level aimed at graduate students and
researchers in quantitative disciplines engaged in the statistical
analysis of network data, although advanced undergraduates already
comfortable with R should find the book fairly accessible as well.
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Produktdetaljer
ISBN
9783030441296
Publisert
2020
Utgave
2. utgave
Utgiver
Vendor
Springer
Språk
Product language
Engelsk
Format
Product format
Digital bok
Forfatter