发表机构
West Virginia University; EPFL（西弗吉尼亚大学; 洛桑联邦理工学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究人员推出R包nethist，该包在统一接口内实现网络直方图类型图子估计，适用于单层和多层网络，含图形摘要，助力理解关联顶点的复杂系统。
AI 中文摘要
理解现实世界网络的生成机制对分析连接模式和从网络数据中进行推断至关重要。图子（graphon）被广泛用于对这类机制进行建模。网络直方图方法是基于块模型近似的非参数方法，能为网络连接结构提供直观视图。然而，目前缺乏构建网络直方图的软件包。我们推出R包nethist，它在统一接口内实现了网络直方图类型的图子（graphon）估计器。该包适用于单层和多层网络，包含用于检查局部和全局网络结构的图形摘要。通过提供全面的网络分析工具，nethist有助于理解相互关联顶点的复杂系统。
英文摘要
Understanding the generative mechanism of real-world networks is crucial for analyzing connection patterns and making inference from network data. Graphons are widely used to model such mechanisms. Network histogram methods are nonparametric approaches based on blockmodel approximations that provide an intuitive view of network connection structures. However, there is a lack of software packages that construct network histograms. We introduce the R package nethist, which implements network histogram-type graphon estimators within a unified interface. This package is applicable to both single-layer and multilayer networks, and includes graphical summaries for examining both local and global network structures. By providing comprehensive network analysis tools, nethist facilitates understanding of complex systems of interrelated vertices.
