BDgraph (version 2.43)

print.sim: Print function for S3 class "sim"

Description

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.

Usage

# S3 method for sim
print( x, ... )

Arguments

x

An object of S3 class "sim", from function bdgraph.sim.

…

System reserved (no specific usage).

References

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

See Also

bdgraph.sim

Examples

# NOT RUN {
# Generating multivariate normal data from a 'random' graph 
data.sim <- bdgraph.sim( n = 20, p = 10, vis = TRUE )
   
print( data.sim )
# }