Description Usage Arguments Details Value Examples

View source: R/simulateBlockDiagNetwork.R

This function simulates a modular network with `p`

variables based on the partition of variables into blocks `labels`

.

1 |

`p` |
number of variables in the network |

`labels` |
vector indicating the partition of variables into blocks |

To simulate covariance matrices, we use the methodology detailed in Giraud, S. Huet, and N. Verzelen. Graph selection with GGMselect. 2009

http://fr.arxiv.org/abs/0907.0619 https://cran.r-project.org/package=GGMselect

`A` |
simulated adjacency matrix |

`C` |
simulated correlation matrix |

`Pcor` |
simulated partial correlation matrix |

`labels` |
vector indicating the partition of variables into blocks provided as input of the function |

1 2 3 4 5 6 7 8 9 | ```
## number of variables
p <- 100
## number of blocks
K <- 15
## vector of partition into blocks
labels <- factor(rep(1:K, length.out=p))
## simulate network
g <- simulateBlockDiagNetwork(p,labels)
``` |

shock documentation built on May 29, 2017, 11:06 p.m.

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