BDgraph (version 2.19)

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

Description

Print the information about the best graph which is the graph with the highest posterior probability. It provides adjacency matrix, size and posterior probability of the best graph.

Usage

## S3 method for class 'bdgraph':
print( x, round = 3, Khat = FALSE, phat = FALSE, ... )

Arguments

x

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

round

A value to round the probabilities to the specified number of decimal places (default is 3).

Khat

Logical: if TRUE you will see the estimation of the precision matrix. The default is FALSE.

phat

Logical: if TRUE you will see the posterior link probabilities. The default is FALSE.

...

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 Mohammadi, A., F. Abegaz Yazew, E. van den Heuvel, and E. Wit (2015). Bayesian Modeling of Dupuytren Disease Using Gaussian Copula Graphical Models, Arxiv preprint arXiv:1501.04849v2

See Also

bdgraph

Examples

# generating multivariate normal data from a 'random' graph
data.sim <- bdgraph.sim( n = 50, p = 6, vis = TRUE )

output   <- bdgraph( data = data.sim )

print( output )

print( output, Khat = TRUE, phat = TRUE )