BDgraph (version 2.19)

summary.bdgraph: Summary function for S3 class "bdgraph"

Description

This function provides a summary of the result from BD-MCMC sampling algorithm.

Usage

## S3 method for class 'bdgraph':
summary( object, vis = TRUE, ... )

Arguments

object

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

vis

Logical: if TRUE (default) you will see the plot result.

...

System reserved (no specific usage).

Value

• best.graph
  The adjacency matrix corresponding to the selected graph which has the highest posterior probability.
• phat
  Upper triangular matrix corresponding to the posterior probabilities of all possible links.
• Khat
  The estimated precision matrix.

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 )

summary(output)

summary( output, vis = FALSE )