Bayesian computational algorithms for social network analysis

A. Caimo, Isabella Gollini
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引用次数: 2

Abstract

In this chapter we review some of the most recent computational advances in the rapidly expanding field of statistical social network analysis using the R open-source software. In particular we will focus on Bayesian estimation for two important families of models: exponential random graph models (ERGMs) and latent space models (LSMs).
社会网络分析的贝叶斯计算算法
在本章中,我们将回顾使用R开源软件的统计社会网络分析领域中一些最新的计算进展。我们将特别关注两个重要模型族的贝叶斯估计:指数随机图模型(ergm)和潜在空间模型(lsm)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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