.png){kind=icon}
返回
Representing Micro-Macro Linkages by Actor-based Dynamic Network Models
.png){kind=icon}
OA
AI
DOI：10.1177/0049124113494573.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro-macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by microspecifications of actor-based models.
Keyword:
statistical inference
agent-based simulation
social networks
micro-macro link
emergence
期刊
S
IF:
6.5
论文数:
1.2K
被引数:
8.6K
机构
引用论文
The 2.6 Angstrom Crystal Structure of a Human A2AAdenosine Receptor Bound to an Antagonist.png)
Science
OAAI
ScienceIF0
OAAI分享收藏分享收藏
查看更多内容