A joint sparse partial correlation method for estimating group functional networks

Joint graphical models combined with stability selection (JGMSS)is a software toolbox that can be employed to robustly estimate both individual- and group-level sparse networks. The software:
(1) Reads time series from a group of subjects;
(2) Subsample data 100 times to estimate stability (i.e. stability
selection);
(3) Group graphical-lasso constraints are applied, including 2
regularization parameters;
(4) Ranges of regularization parameters are chosen to implement stability
selection;
(5) The alternating direction method of multipliers (ADMM) approach is
employed to solve the problem.

The Method is described in the following paper:
Xiaoyun Liang, Alan Connelly, Fernando Calamante. A novel joint sparse partial correlation method for estimating group functional networks. Human Brain Mapping 12/2015; DOI:10.1002/hbm.23092.
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Specifications

License:GNU General Public License (GPL)
Domain:MR
Other Keywords: Functional connectivity, Graphical models

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RE: How to input data? posted by Xiaoyun Liang on Jan 4, 2016

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How to input data? posted by Peter McColgan on Jan 4, 2016

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jgmss: JGMSS1.0 release

http://www.nitrc.org/projects/jgmss/ posted by Xiaoyun Liang on Dec 22, 2015

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jgmss: JGMSS1.0 release

JGMSS_Code_HBM.zip posted by Xiaoyun Liang on Dec 22, 2015

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