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.

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`x` |
An object of |

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

Abdolreza Mohammadi and Ernst Wit

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

Mohammadi, A. and E. Wit (2015). BDgraph: An `R`

Package for Bayesian Structure Learning in Graphical Models, *arXiv:1501.05108v2*

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

1 2 3 4 5 6 7 | ```
## Not run:
# Generating multivariate normal data from a 'random' graph
data.sim <- bdgraph.sim( n = 20, p = 10, vis = TRUE )
print( data.sim )
## End(Not run)
``` |

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