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.

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`x` |
An object of |

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

Reza Mohammadi, Adrian Dobra, 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 preprint arXiv:1501.05108v2*

Dobra, A. and A. Mohammadi (2017). Loglinear Model Selection and Human Mobility, *arXiv preprint arXiv:1711.02623*

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

Mohammadi, A., Massam H., and G. Letac (2017). The Ratio of Normalizing Constants for Bayesian Graphical Gaussian Model Selection, *arXiv preprint arXiv:1706.04416*

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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