Statistical analysis of network data with R
Kolaczyk, Eric D.
creator
Csárdi, Gábor.
text
bibliography
nyu
2014
2014
monographic
eng
xiii, 228 pages : illustrations (some color) ; 24 cm.
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).--
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 data -- 10. Dynamic networks.
Eric D. Kolaczyk, Gábor Csárdi.
Includes bibliographical references (225-228) and index
System analysis
Statistical methods
R (Computer program language)
Data Interpretation, Statistical
R (Computer program language)
System analysis
Statistical methods
QA402 .K6483 2014
003.015195
Use R!
9783030441289 (pbk. : alk. paper)
2014936989
YDXCP
140331
20240123132707.0
18087732
eng