|
Product Description
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).
Customers Who Bought This Item Also Bought
- Probabilistic Foundations of Statistical Network Analysis (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
- Exponential Random Graph Models for Social Networks: Theory, Methods, and Applications (Structural Analysis in the Social Sciences)
- Understanding Social Networks: Theories, Concepts, And Findings
- Network Science
- An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
- R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
- Statistical Analysis of Network Data: Methods and Models (Springer Series in Statistics)
- Networks
- A User's Guide to Network Analysis in R
- Data Visualization: A Practical Introduction
*If this is not the "Statistical Analysis of Network Data with R (Use R!)" product you were looking for, you can check the other results by clicking this link. Details were last updated on Dec 8, 2024 03:59 +08.