Statistical Analysis of Network Data with R

Buch | Softcover
207 Seiten
2014
Springer-Verlag New York Inc.
978-1-4939-0982-7 (ISBN)

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Statistical Analysis of Network Data with R - Eric D. Kolaczyk, Gábor Csárdi
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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).

Eric D. Kolaczyk is a professor of statistics, and Director of the Program in Statistics, in the Department of Mathematics and Statistics at Boston University, where he also is an affiliated faculty member in the Bioinformatics Program,  the Division of Systems Engineering, and the Program in Computational Neuroscience. His publications on network-based topics, beyond the development of statistical methodology and theory, include work on applications ranging from the detection of anomalous traffic patterns in computer networks to the prediction of biological function in networks of interacting proteins to the characterization of influence of groups of actors in social networks. He is an elected fellow of the American Statistical Association (ASA) and an elected senior member of the Institute of Electrical and Electronics Engineers (IEEE).  Gábor Csárdi is a research associate at the Department of Statistics at Harvard University, Cambridge, Mass. He holds a PhD in Computer Science from Eötvös University, Hungary. His research includes applications of network analysis in biology and social sciences, bioinformatics and computational biology, and graph algorithms. He created the igraph software package in 2005 and has been one of the lead developers since then.

​Introduction.- Manipulating Network Data.- Visualizing Network Data.- Descriptive Analysis of Network Graph Characteristics.- Mathematical Models for Network Graphs.- Statistical Models for Network Graphs.- Latent Network Models.- Network Topology Inference.- Modeling and Prediction of Static Network Processes.- Dynamic Network Processes.- Analysis of Network Flow Data.

Reihe/Serie Use R!
Zusatzinfo 53 Illustrations, color; 2 Illustrations, black and white; XIII, 207 p. 55 illus., 53 illus. in color.
Verlagsort New York
Sprache englisch
Maße 155 x 235 mm
Gewicht 3868 g
Themenwelt Mathematik / Informatik Mathematik Computerprogramme / Computeralgebra
Mathematik / Informatik Mathematik Statistik
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Schlagworte network analysis • network topology • R • random graph models
ISBN-10 1-4939-0982-7 / 1493909827
ISBN-13 978-1-4939-0982-7 / 9781493909827
Zustand Neuware
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