Iterative reconstruction of high-dimensional Gaussian Graphical Models based on a new method to estimate partial correlations under constraints.
In the context of Gaussian Graphical Models (GGMs) with high-dimensional small sample data, we present a simple procedure, called PACOSE - standing for PArtial COrrelation SElection - to estimate partial correlations under the constraint that some of them are strictly zero. This method can also be e...
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Auteurs principaux: | Vincent Guillemot, Andreas Bender, Anne-Laure Boulesteix |
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Format: | article |
Langue: | EN |
Publié: |
Public Library of Science (PLoS)
2013
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Accès en ligne: | https://doaj.org/article/a0eb6a87f8a6470f890a0844907b465d |
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