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Statistics > Methodology

arXiv:2204.04291 (stat)
[Submitted on 8 Apr 2022 (v1), last revised 1 Dec 2022 (this version, v2)]

Title:Robustly fitting Gaussian graphical models: the R-package robFitConGraph

Authors:Daniel Vogel, Stuart J. Watt, Anna Wiedemann
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Abstract: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 this https URL
Subjects: Methodology (stat.ME); Computation (stat.CO)
MSC classes: 62H22, 62H15
ACM classes: G.3
Cite as: arXiv:2204.04291 [stat.ME]
  (or arXiv:2204.04291v2 [stat.ME] for this version)
  https://doi.org/10.48550/arXiv.2204.04291

Submission history

From: Daniel Vogel [view email]
[v1] Fri, 8 Apr 2022 20:44:33 UTC (291 KB)
[v2] Thu, 1 Dec 2022 17:37:32 UTC (205 KB)
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