Sparse Gaussian Graphical Model Estimation, Visualization and Evaluation

A set of tools for performing sparse Gaussian graphical model (joint, multiple and difference) estimation from high dimensional dataset. It contains a general purpose visualization function as well as a specialized function for 3d brain network. Simulation and evaluation modules are available. It also contains a simple GUI built in shiny for easy graph visualization. Methods include SIMULE (Wang B et al. (2017) ), WSIMULE (Singh C et al. (2017) ), DIFFEE (Wang B et al. (2018) ), FASJEM (Wang B et al. (2018) ), JEEK (Wang B et al. (2018) ) and DIFFEEK (Wang B et al, under final review for publication).


Reference manual

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1.0.0 by Zhaoyang Wang, 2 months ago

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Browse source code at

Authors: Beilun Wang [aut] , Yanjun Qi [aut] , Zhaoyang Wang [aut, cre]

Documentation:   PDF Manual  

GPL-2 license

Imports MASS, brainR, misc3d, oro.nifti, shiny, rgl, methods

Depends on lpSolve, pcaPP, igraph, parallel

See at CRAN