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  • 标题:A unifying framework for fast randomization of ecological networks with fixed (node) degrees
  • 本地全文:下载
  • 作者:Corrie Jacobien Carstens ; Annabell Berger ; Giovanni Strona
  • 期刊名称:MethodsX
  • 印刷版ISSN:2215-0161
  • 电子版ISSN:2215-0161
  • 出版年度:2018
  • 卷号:5
  • 页码:773-780
  • DOI:10.1016/j.mex.2018.06.018
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Graphical abstractDisplay OmittedAbstractThe Curveball algorithm is an efficient and unbiased procedure for randomizing bipartite networks (or their matrix counterpart) while preserving node degrees. Here we introduce two extensions of the procedure, making it capable to randomize also unimode directed and undirected networks. We provide formal mathematical proofs that the two extensions, as the original Curveball, are fast and unbiased (i.e. they sample uniformly from the universe of possible network configurations).•We extend the Curveball algorithm to unimode directed and undirected networks.•As the original Curveball, extensions are fast and unbiased.•We provide Python and R code implementing the new procedures.
  • 关键词:Binary matrices;Co-occurrence;Curveball algorithm;Food web;Null model
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