MNS-package: Mixed Neighbourhood Selection package

In MNS: Mixed Neighbourhood Selection

Description

An R package for estimating multiple, related grapical models using the Mixed Neighbourhood Selection algorithm. This package also includes two algorithm through which to simulate multiple, related graphical models which demonstrate some of the properties reported through empirical studies of functional connectivity networks.

Details

Package:	MNS
Type:	Package
Version:	1.0
Date:	2015-10-14
License:	GPL-2

Author(s)

Ricardo Pio Monti

References

Monti, R., Anagnostopolus, C., Montana, G. "Inferring brain connectivity networks from functional MRI data via mixed neighbourhood selection", arXiv, 2015

See Also

MNS, cv.MNS, plot.MNS, gen.Network

Examples

set.seed(1)
N=4
Net = gen.Network(method = "cohort", p = 10, 
                       Nsub = N, sparsity = .2, 
                       REsize = 20, REprob = .5,
                       REnoise = 1, Nobs = 10)
## Not run: 
# plot simulated networks:
plot(Net, view="pop")

# run MNS algorithm:
mns = MNS(dat = Net$Data, lambda_pop = .1, lambda_random = .1, parallel = TRUE)

# plot results from MNS algorithm:
plot(mns) # plot population network
plot(mns, view="var") # plot variance network
plot(mns, view="sub") # plot subject networks (note red edges here are variable edges!)

## End(Not run)

MNS documentation built on May 2, 2019, 9:33 a.m.