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Modelling animal network data in R using STRAND.
Ross, Cody T; McElreath, Richard; Redhead, Daniel.
Affiliation
  • Ross CT; Department of Human Behavior, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.
  • McElreath R; Department of Human Behavior, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.
  • Redhead D; Department of Human Behavior, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.
J Anim Ecol ; 93(3): 254-266, 2024 03.
Article in En | MEDLINE | ID: mdl-37936514
ABSTRACT
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 the STRAND R 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 how STRAND can 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. STRAND facilitates the application of generative network models to a broad range of data found in the animal social networks literature.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software Limits: Animals Language: En Journal: J Anim Ecol Year: 2024 Document type: Article Affiliation country: Germany

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software Limits: Animals Language: En Journal: J Anim Ecol Year: 2024 Document type: Article Affiliation country: Germany