马尔科夫蒙特卡洛
指数随机图模型
估计员
R包
计算机科学
集合(抽象数据类型)
马尔可夫链
指数族
拟合优度
数据集
蒙特卡罗方法
统计
数学
图形
随机图
人工智能
机器学习
理论计算机科学
程序设计语言
作者
David R. Hunter,Mark S. Handcock,Carter T. Butts,Steven M. Goodreau,Martina Morris
标识
DOI:10.18637/jss.v024.i03
摘要
We describe some of the capabilities of the ergm package and the statistical theory underlying it. This package contains tools for accomplishing three important, and inter-related, tasks involving exponential-family random graph models (ERGMs): estimation, simulation, and goodness of fit. More precisely, ergm has the capability of approximating a maximum likelihood estimator for an ERGM given a network data set; simulating new network data sets from a fitted ERGM using Markov chain Monte Carlo; and assessing how well a fitted ERGM does at capturing characteristics of a particular network data set.
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