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Statistical analysis of network data with R

By: Kolaczyk, Eric D.
Contributor(s): Csardi, Gabor [Co author].
Material type: materialTypeLabelBookSeries: Use R!. Publisher: New York Springer 2014Description: xii, 207 p.ISBN: 9781493909827.Subject(s): Statistical analysis | Programming language - R | Network dataDDC classification: 003.015195 Summary: Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It 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. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009). https://www.springer.com/in/book/9781493909827#aboutBook
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Slot 15 (0 Floor, West Wing) Non-fiction 003.015195 K6S8 (Browse shelf) Available 199568

Table of contents

1.Introduction
2.Manipulating Network Data
3.Visualizing Network Data
4.Descriptive Analysis of Network Graph Characteristics
5.Mathematical Models for Network Graphs
6.Statistical Models for Network Graphs
7.Network Topology Inference
8.Modeling and Prediction for Processes on Network Graphs
9.Analysis of Network Flow DataDynamic Networks
10.Dynamic Networks

Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It 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. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).

https://www.springer.com/in/book/9781493909827#aboutBook

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