Description Usage Arguments Details Value Author(s) References See Also Examples

Implementations of two methods through which to simulation multiple related networks. The first simulates networks from a three-class population described in Danaher et al. (2014). The second simulates networks according to method proposed in Monti et al. (2015). For further details see the package vignette.

1 2 3 | ```
gen.Network(method = "cohort", p,
Nobs, Nsub, sparsity,
REsize, REprob, REnoise)
``` |

`method` |
Network simulation method. One of either "Danaher" for the three-class method of Danaher et al. (2014) or "cohort" for the cohort method described in Monti et al. (2015) |

`p` |
Number of nodes in network (i.e., this will be dimensionality of the resulting precision matrices) |

`Nobs` |
Number of observations per subject (assumed constant across subjects). If this is missing then only the precision matrices will be returned (i.e., random data is not simulated) |

`Nsub` |
Number of subjects for which to simulate networks. Note that this is set to 3 if method="Danaher" |

`sparsity` |
Sparsity level of precision matrices |

`REsize` |
Number of random effects edges to add to each subject (only for method="cohort") |

`REprob` |
Probability with which a random edge added to each subject (only for method="cohort") |

`REnoise` |
Variability of random edges (only for method="cohort") |

See package vignette for further details. Alternatively see Danaher et al. (2014) or Monti et al. (2015)

`Networks` |
List containing simulated netowrks where ith entry is the ith random network for the ith subject |

`Data` |
List where ith entry is simulated data for ith subject |

`PopNet` |
Population precision matrix (only if method="cohort") |

`RanNet` |
Sparse support for random edges (only if method="cohort") |

Ricardo Pio Monti

Danaher, P., Wang, P. , and Witten, D. "The joint graphical lasso for inverse covariance estimation across multiple classes." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 76.2 (2014): 373-397.

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

1 2 3 4 5 6 7 8 9 10 11 | ```
# generate data according to cohort model of Monti et al. (2015)
set.seed(1)
Dat = gen.Network(p = 10, Nsub = 5,
sparsity = .2, REsize=10, REprob=.5,
REnoise = 1, Nobs=20)
## Not run:
# plot simulated networks:
plot(Net, view="pop")
## End(Not run)
``` |

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