Description Usage Arguments Author(s) References See Also Examples

Prints the information about the type of data, the sample size, the graph type, the number of nodes, number of links and sparsity of the true graph.

1 2 |

`x` |
An object of |

`...` |
System reserved (no specific usage). |

Reza Mohammadi a.mohammadi@uva.nl and Ernst Wit

Mohammadi, R. and Wit, E. C. (2019). BDgraph: An `R`

Package for Bayesian Structure Learning in Graphical Models, *Journal of Statistical Software*, 89(3):1-30

Mohammadi, A. and Wit, E. C. (2015). Bayesian Structure Learning in Sparse Gaussian Graphical Models, *Bayesian Analysis*, 10(1):109-138

Dobra, A. and Mohammadi, R. (2018). Loglinear Model Selection and Human Mobility, *Annals of Applied Statistics*, 12(2):815-845

Mohammadi, A. et al (2017). Bayesian modelling of Dupuytren disease by using Gaussian copula graphical models, *Journal of the Royal Statistical Society: Series C*, 66(3):629-645

Letac, G., Massam, H. and Mohammadi, R. (2018). The Ratio of Normalizing Constants for Bayesian Graphical Gaussian Model Selection, *arXiv preprint arXiv:1706.04416v2*

1 2 3 4 | ```
# Generating multivariate normal data from a 'random' graph
data.sim <- bdgraph.sim( n = 20, p = 10, vis = TRUE )
print( data.sim )
``` |

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