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noisysbmGGM  

Noisy Stochastic Block Model for GGM Inference
View on CRAN: Click here


Download and install noisysbmGGM package within the R console
Install from CRAN:
install.packages("noisysbmGGM")

Install from Github:
library("remotes")
install_github("cran/noisysbmGGM")

Install by package version:
library("remotes")
install_version("noisysbmGGM", "0.1.2.3")



Attach the package and use:
library("noisysbmGGM")
Maintained by
Valentin Kilian
[Scholar Profile | Author Map]
First Published: 2024-03-07
Latest Update: 2024-03-07
Description:
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) .
How to cite:
Valentin Kilian (2024). noisysbmGGM: Noisy Stochastic Block Model for GGM Inference. R package version 0.1.2.3, https://cran.r-project.org/web/packages/noisysbmGGM. Accessed 17 Feb. 2025.
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