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.
发表于2024-11-29
Statistical Analysis of Network Data with R 2024 pdf epub mobi 电子书
图书标签: R 统计 网络科学 社交网络分析 研究方法 统计模型 科普 社会网络
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).
4.5 两百页小册子,简洁快速总结了经济学之外的applied network analysis。R在network上的应用介绍得也周到。
评分4.5 两百页小册子,简洁快速总结了经济学之外的applied network analysis。R在network上的应用介绍得也周到。
评分本书已经由我译成中文并正式出版(https://book.douban.com/subject/26818368/)。从最简单的指标和作图,到最前沿的网络统计模型,本书可以带你用统计利器快速上手探索网络世界~
评分本书已经由我译成中文并正式出版(https://book.douban.com/subject/26818368/)。从最简单的指标和作图,到最前沿的网络统计模型,本书可以带你用统计利器快速上手探索网络世界~
评分比较一般都是r ergm 比较适合初学
Statistical Analysis of Network Data with R 2024 pdf epub mobi 电子书