BDgraph (version 2.23)

prob: Posterior probabilities of the graphs

Description

Provides the estimated posterior probabilities for the most likely graphs or a specific graph, 'G'.

Usage

prob( x, number.g = 4, G = NULL )

Arguments

x

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

number.g

The number of graphs with the highest posterior probabilities to be shown (default is 4). This option is ignored if 'G' is specified.

G

Adjacency matrix corresponding to a graph structure. It is an upper triangular matrix in which $g_{ij}=1$ if there is a link between notes $i$ and $j$, otherwise $g_{ij}=0$. It also can be an object of S3 class

Value

• selected_G
  The graphs with the highest posterior probabilities.
• prob_G
  A vector of the posterior probabilities of the graphs corresponding to 'selected_G'.

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 (2015). Bayesian Gaussian Copula Graphical Modeling for Dupuytren Disease, arXiv:1501.04849

See Also

bdgraph

Examples

# Generating multivariate normal data from a 'random' graph
data.sim <- bdgraph.sim( n = 50, p = 6, size = 6, vis = TRUE )
   
output   <- bdgraph( data = data.sim, save.all = TRUE )
   
# Estimated posterior probability of the true graph
prob( output, G = data.sim )
   
# Estimated posterior probability of the first and second graphs with highest probabilities
prob( output, number.g = 2 )