Robustly Fitting Gaussian Graphical Models—the R Package robFitConGraph

Daniel Vogel (), Stuart J. Watt and Anna Wiedemann ()
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Daniel Vogel: MEDICE Arzneimittel Pütter GmbH & Co. KG
Stuart J. Watt: Mirador Analytics
Anna Wiedemann: University of Cambridge, Department of Psychiatry

A chapter in Robust and Multivariate Statistical Methods, 2023, pp 277-296 from Springer

Abstract: Abstract This chapter gives a tutorial-style introduction to the R package robFitConGraph, which 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 theory is briefly explained, much of which has been developed by David Tyler.

Keywords: Covariance selection model; Deviance test; M-estimator; Music performance anxiety; Partial correlation (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-22687-8_13

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DOI: 10.1007/978-3-031-22687-8_13

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