Adjusted regularization of cortical covariance (Vinci et al 2018)

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Accession:239741
Graphical Lasso with Adjusted Regularization (GAR) useful to estimate functional connectivity.
Reference:
1 . Vinci G, Ventura V, Smith MA, Kass RE (2018) Adjusted regularization of cortical covariance. J Comput Neurosci 45:83-101 [PubMed]
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Simulation Environment: R;
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GARggm
Readme.txt
GARggm_0.1.0.tar.gz
                            
The R-package "GARggm" contains two functions:

- "GAR.FB", which implements the full Bayes algorithm (Algorithm 3 of Vinci et al. 2018)
- "GAR.EB", which implements the empirical Bayes algorithm (Algorithm 4 of Vinci et al. 2018). 

Information about their use can be found in R with commands "?GAR.FB" and "?GAR.EB".


Reference:
Vinci G., Ventura V., Smith M.A., and Kass R.E. (2018). Adjusted Regularization of Cortical Covariance. Journal of Computational Neuroscience.