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BDgraph (version 2.33)

summary.bdgraph: Summary function for

Description

Provides a summary of the results for function bdgraph.

Usage

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

Arguments

object
An object of S3 class "bdgraph", from function bdgraph.
vis
Visualize the results. The default value is TRUE.
System reserved (no specific usage).

Value

best.graph
The adjacency matrix corresponding to the selected graph which has the highest posterior probability.
p_links
An upper triangular matrix corresponding to the posterior probabilities of all possible links.
K_hat
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:1501.05108 Mohammadi, A., F. Abegaz Yazew, E. van den Heuvel, and E. Wit (2016). Bayesian modelling of Dupuytren disease by using Gaussian copula graphical models, Journal of the Royal Statistical Society: Series C

See Also

bdgraph

Examples

Run this code
## Not run: ------------------------------------
# # Generating multivariate normal data from a 'random' graph
# data.sim <- bdgraph.sim( n = 50, p = 6, size = 7, vis = TRUE )
#    
# bdgraph.obj <- bdgraph( data = data.sim )
#    
# summary( bdgraph.obj )
#    
# bdgraph.obj <- bdgraph( data = data.sim, save.all = TRUE )
#    
# summary( bdgraph.obj )
#    
# summary( bdgraph.obj, vis = FALSE )
## ---------------------------------------------

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