noisysbmGGM
Noisy Stochastic Block Model for GGM Inference
Greedy Bayesian algorithm to fit the noisy stochastic block model to an observed sparse graph. Moreover, a graph inference procedure to recover Gaussian Graphical Model (GGM) from real data. This procedure comes with a control of the false discovery rate. The method is described in the article "Enhancing the Power of Gaussian Graphical Model Inference by Modeling the Graph Structure" by Kilian, Rebafka, and Villers (2024) doi:10.48550/arXiv.2402.19021.
- Version0.1.2.3
- R versionunknown
- LicenseGPL-2
- Needs compilation?Yes
- Last release03/07/2024
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Team
Valentin Kilian
Fanny Villers
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- Imports8 packages
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