指数随机图模型
计算机科学
社会网络分析
单变量
多元统计
二部图
社交网络(社会语言学)
网络分析
数据科学
数据挖掘
图形
计量经济学
机器学习
随机图
理论计算机科学
数学
工程类
社会化媒体
万维网
电气工程
作者
Dean Lusher,Johan Koskinen,Garry Robins
出处
期刊:Cambridge University Press eBooks
[Cambridge University Press]
日期:2012-11-19
被引量:760
标识
DOI:10.1017/cbo9780511894701
摘要
Exponential random graph models (ERGMs) are increasingly applied to observed network data and are central to understanding social structure and network processes. The chapters in this edited volume provide a self-contained, exhaustive account of the theoretical and methodological underpinnings of ERGMs, including models for univariate, multivariate, bipartite, longitudinal and social-influence type ERGMs. Each method is applied in individual case studies illustrating how social science theories may be examined empirically using ERGMs. The authors supply the reader with sufficient detail to specify ERGMs, fit them to data with any of the available software packages and interpret the results.
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