Description Details Author(s) References See Also Examples

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.

Package: | MNS |

Type: | Package |

Version: | 1.0 |

Date: | 2015-10-14 |

License: | GPL-2 |

Ricardo Pio Monti

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

`MNS`

, `cv.MNS`

, `plot.MNS`

, `gen.Network`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
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)
``` |

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