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Comparison of statistical procedures for Gaussian graphical model selection

P. 269–279.
Grechikhin I., Kalyagin V. A.

Graphical models are used in a variety of problems to uncover hidden structures. There is an important number of different identification procedures to recover graphical model from observations. In this paper, undirected Gaussian graphical models are considered. Some Gaussian graphical model identification statistical procedures are compared using different measures, such as Type I and Type II errors, ROC AUC.

Language: English
DOI
Keywords: statistical inferenceGaussian graphical modelIdentification procedure

In book

Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & Statistics
Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & Statistics
Valery A. Kalyagin, Panos M. Pardalos, Oleg Prokopyev, Irina Utkina Vol. 247. , Springer, 2018.
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