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.

Author
Ricardo Pio Monti, Christoforos Anagnostopoulos and Giovanni Montana
Date of publication
2015-12-08 14:53:44
Maintainer
Ricardo Pio Monti <ricardo.monti08@gmail.com>
License
GPL-2
Version
1.0

View on CRAN

Man pages

cv.MNS
Select regularization parameters via cross-validation
gen.Network
Simulate random networks for a population of subjects
MNS
Mixed Neighbourhood Selection
MNS-package
Mixed Neighbourhood Selection package
plot.MNS
Plotting function for MNS objects

Files in this package

MNS
MNS/inst
MNS/inst/doc
MNS/inst/doc/vignette.Rnw
MNS/inst/doc/vignette.pdf
MNS/inst/doc/vignette.R
MNS/NAMESPACE
MNS/R
MNS/R/plot.MNS.R
MNS/R/genLargerBAnetwork.R
MNS/R/CVsequential.R
MNS/R/calculateNLL.R
MNS/R/generateJGLnetworks.R
MNS/R/CVparallel.R
MNS/R/genSmallNet.R
MNS/R/MNS.R
MNS/R/BuildRandomDesign.R
MNS/R/cv.MNS.R
MNS/R/PrepareData.R
MNS/R/genREnetworksEnforceTrans.R
MNS/R/PenalizedLMM_opt.R
MNS/R/gen.Network.R
MNS/vignettes
MNS/vignettes/vignette.Rnw
MNS/vignettes/PopPlot.pdf
MNS/vignettes/Plot22.pdf
MNS/vignettes/Plot11.png
MNS/vignettes/vignette.synctex.gz
MNS/vignettes/Subjects.pdf
MNS/vignettes/VarPlot.png
MNS/vignettes/Plot1.png
MNS/vignettes/Plot2.png
MNS/vignettes/ref.bib
MNS/vignettes/VarPlot.pdf
MNS/vignettes/Subjects.png
MNS/vignettes/PopPlot.png
MNS/vignettes/Plot22.png
MNS/vignettes/TSplot.pdf
MNS/MD5
MNS/build
MNS/build/vignette.rds
MNS/DESCRIPTION
MNS/man
MNS/man/gen.Network.Rd
MNS/man/plot.MNS.Rd
MNS/man/MNS-package.Rd
MNS/man/cv.MNS.Rd
MNS/man/MNS.Rd