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MNS: Mixed Neighbourhood Selection

An implementation of the mixed neighbourhood selection (MNS) algorithm. The MNS algorithm can be used to estimate multiple related precision matrices. In particular, the motivation behind this work was driven by the need to understand functional connectivity networks across multiple subjects. This package also contains an implementation of a novel algorithm through which to simulate multiple related precision matrices which exhibit properties frequently reported in neuroimaging analysis.

Version: 1.0
Depends: igraph, MASS, glmnet, mvtnorm, parallel, R (≥ 2.10.1)
Imports: doParallel
Published: 2015-12-08
DOI: 10.32614/CRAN.package.MNS
Author: Ricardo Pio Monti, Christoforos Anagnostopoulos and Giovanni Montana
Maintainer: Ricardo Pio Monti <ricardo.monti08 at gmail.com>
License: GPL-2
NeedsCompilation: no
CRAN checks: MNS results

Documentation:

Reference manual: MNS.pdf
Vignettes: An R package for the MNS algorithm

Downloads:

Package source: MNS_1.0.tar.gz
Windows binaries: r-devel: MNS_1.0.zip, r-release: MNS_1.0.zip, r-oldrel: MNS_1.0.zip
macOS binaries: r-release (arm64): MNS_1.0.tgz, r-oldrel (arm64): MNS_1.0.tgz, r-release (x86_64): MNS_1.0.tgz, r-oldrel (x86_64): MNS_1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.