论文标题
可靠拟合高斯图形模型：R-package RobfitCongraph
Robustly fitting Gaussian graphical models: the R-package robFitConGraph
论文作者
论文摘要
给出了R-Package RobfitCongraph的教程风格的介绍。后者为高斯图形模型提供了强大的合适性测试。它的用途在有关音乐性能焦虑的数据示例中证明了这一点，这也说明了为什么要适合高斯图形模型，以及为什么人们应该这样做。简要解释了基本的统计理论。本文介绍了4.4.1版的包装，可在2022年12月1日从Cran上获得。请参阅https：//cran.r-project.org/package=robfitcongraph
A tutorial-style introduction to the R-package robFitConGraph is given. The latter provides a robust goodness-of-fit test for Gaussian graphical models. Its use is demonstrated at a data example on music performance anxiety, which also illustrates why one would want to fit a Gaussian graphical model - and why one should do so robustly. The underlying statistical theory is briefly explained. The paper describes package version 0.4.1, available on CRAN from December 1, 2022. See https://CRAN.R-project.org/package=robFitConGraph
