Modelling animal network data in R using STRAND
Modelling animal network data in R using STRAND
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DOI：
10.1111/1365-2656.14021
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发表时间：
2023-11-07
影响因子：
4.8
通讯作者：
Redhead，Daniel
中科院分区：
文献类型：
--
作者：
Ross，Cody T.;McElreath，Richard;Redhead，Daniel
最近有人呼吁在应用社会网络分析中更广泛地应用生成建模方法。然而，目前，对于典型的终端用户（例如，现场研究人员）来说，实现生成网络模型仍然很困难，因为缺乏公开可用的软件包，这些软件包使此类模型的应用与其他基于排列的方法一样简单。在这里，我们概述了STRANDR包，它提供了一套用于动物社交网络数据贝叶斯分析的生成模型，可以使用简单的，基础R语法。为了便于使用，我们提供了一个教程，演示如何使用随机块模型，社会关系模型或两个建模框架的组合，STRAND可以用于建模比例，计数或二进制网络数据。STRAND促进了生成网络模型的应用，以广泛的数据中发现的动物社交网络文献。
There have been recent calls for wider application of generative modelling approaches in applied social network analysis. At present, however, it remains difficult for typical end users—for example, field researchers—to implement generative network models, as there is a dearth of openly available software packages that make application of such models as simple as other, permutation‐based approaches.Here, we outline theSTRANDR package, which provides a suite of generative models for Bayesian analysis of animal social network data that can be implemented using simple, base R syntax.To facilitate ease of use, we provide a tutorial demonstrating howSTRANDcan be used to model proportion, count or binary network data using stochastic block models, social relation models or a combination of the two modelling frameworks.STRANDfacilitates the application of generative network models to a broad range of data found in the animal social networks literature.