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Here I illustrate how GGM selection methods work better in network hub and cluster detection when the false discover rate (FDR) control is ignored.
This R package is a wrapper around the popular "glasso" package with built-in cross validation and visualizations
All scripts/programs used for my master's thesis covering sparse graphical models, especially gLASSO and gSLOPE estimators.
The code is written in python language with necessary libraries and comments are there for every step to understand it better.