JointNets (1.0.0)

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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).

Maintainer: Zhaoyang Wang
Author(s): Beilun Wang [aut], Yanjun Qi [aut], Zhaoyang Wang [aut, cre]

License: GPL-2

Uses: brainR, igraph, lpSolve, MASS, misc3d, oro.nifti, pcaPP, rgl, shiny

Released 6 months ago.



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