In recent years there has been an explosion of network data – that
is, measu- ments that are either of or from a system conceptualized as
a network – from se- ingly all corners of science. The combination
of an increasingly pervasive interest in scienti c analysis at a
systems level and the ever-growing capabilities for hi- throughput
data collection in various elds has fueled this trend. Researchers
from biology and bioinformatics to physics, from computer science to
the information sciences, and from economics to sociology are more and
more engaged in the c- lection and statistical analysis of data from a
network-centric perspective. Accordingly, the contributions to
statistical methods and modeling in this area have come from a
similarly broad spectrum of areas, often independently of each other.
Many books already have been written addressing network data and
network problems in speci c individual disciplines. However, there is
at present no single book that provides a modern treatment of a core
body of knowledge for statistical analysis of network data that cuts
across the various disciplines and is organized rather according to a
statistical taxonomy of tasks and techniques. This book seeks to ll
that gap and, as such, it aims to contribute to a growing trend in
recent years to facilitate the exchange of knowledge across the
pre-existing boundaries between those disciplines that play a role in
what is coming to be called ‘network science.
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Produktdetaljer
ISBN
9780387881461
Publisert
2019
Utgiver
Vendor
Springer
Språk
Product language
Engelsk
Format
Product format
Digital bok
Forfatter