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Statistical Analysis of Network Data: Methods and Models (Springer Series in Statistics)

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Description

In up to date years there was 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 an increasing number of pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in more than a few 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 an increasing number of 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 in a similar way broad spectrum of areas, incessantly independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. Then again, there is at present no single book that provides a modern remedy of a core body of knowledge for statistical analysis of network data that cuts across the more than a few disciplines and is organized slightly 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 up to date 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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